Your next customer may never open your app, scroll your homepage, or read a single product description. They’ll send an AI agent instead, and that agent will decide whether you exist based entirely on the quality of your data architecture.

Unfortunately, most Asian retailers aren’t ready for this, yet! Here’s how to find out if you are, and what to do about it.

The AI agent doesn’t browse. It queries. It doesn’t feel brand affinity. It parses attributes. It doesn’t abandon a cart, it simply never adds you to one if your product data doesn’t meet its criteria.

This is the Agentic Gap- the discrepancy between what retailers have built for human shoppers and what the next generation of autonomous purchasing agents actually needs.

The evidence is already in the numbers. A 2026 Visa and YouGov study across 14 APAC markets found that 74% of shoppers already use AI tools for product discovery but only 26% trust AI to complete the purchase.

What we see here is not about consumer psychology, it’s actually an AI infrastructure problem. It’s a gap in data architecture, API readiness, and identity infrastructure.

The handoff between discovery and transaction: is exactly where the Agentic Commerce value chain breaks down. Closing this gap is the most important and least glamorous technology decision Asian retailers will make in the next two years.

The retailers who close that gap first will capture a disproportionate share of the next wave of APAC commerce. The rest will be invisible to it.

In this article, I am not selling you the vision of Agentic Commerce. Agentic AI is already here. What I want to give you instead is a practical readiness playbook which tells you if you are ready to embrace this change, and more importantly, what to fix first.

APAC Is Ground Zero and Why the Stakes Are Higher Here

The infrastructure gap is real across all Asian markets, but it hits differently.

Digitally mature retailers with a super-app ecosystem have inadvertently been building the rails for agentic commerce, as a byproduct of doing something else entirely.

For example, WeChat Pay and Alipay’s delegated authentication infrastructure, JD.com’s structured product APIs, Taobao’s machine-readable catalogue - these weren’t designed for AI agents but for ensuring seamless human transactions at scale. But the outcome is an identity and data layer that an autonomous agent can navigate with minimal friction.

Hence, on these platforms, when a shopper uses an AI assistant to find and purchase a product, the current infrastructure largely cooperates. The agent can authenticate, query real-time inventory, compare structured attributes, and transact- all without a human in the loop at every step.

Now contrast that with some of the Southeast Asian markets.

The region’s platform landscape is dynamic, high-growth but deeply fragmented. Product data lives in different schemas across different platforms. APIs are inconsistent, often undocumented, and not designed for programmatic querying at scale. Identity infrastructure is fragmented by payment method, platform, and market. An AI agent trying to discover, compare, and purchase across these shopping platforms faces the complexity of unstructured data, which is difficult to navigate.

India on the other hand, presents an interesting opportunity. Here, the ONDC ( Open Network for Digital Commerce ) was built from inception on open API principles. UPI’s open infrastructure created a payment layer that is, by design, accessible to third-party agents and integrations. This interoperable commerce layer is a useful foundation for the agentic commerce era.

The Asian markets digital divide matters because it tells you something specific about the competitive timeline in these markets.

In China, the question is already “which retailers are winning in agentic commerce?” In SEA, the question is still “which retailers will even be findable when agents start shopping?” and India, it’s about “ which retailers will be the early adopters and plug into the agentic infrastructure already being built for commerce”.

The urgency in Asia is also structurally higher than in Western markets. Mobile-first consumers across Asian markets are among the most likely early adopters of AI shopping assistants globally. Retailers who assume they have time are likely mis-calibrating the urgency.

The window for retailers to get agent-ready is not five years. It’s closer to two.

The Agent Discovery Audit: Four Steps to Know Where You Stand

The reality today is that the retailers & brands, who are seeing meaningful AI ROI are those with clean integration infrastructure underneath it. The organisations layering AI on fragmented, siloed data architecture are simply failing at the prerequisites for agentic readiness.

Before we talk more about the Agent Discovery Audit, I just want to clarify what this audit is and isn’t. It’s not a comprehensive digital transformation roadmap. It won’t fix your data architecture in a week. What it will do is give you a clear, honest picture of your current agent-readiness across four dimensions and tell you which one to prioritise first.

Step 1: The LLM Test: Can an Agent Find You?

Start here, because it costs nothing and reveals almost everything.

Ask a general-purpose LLM ( Gemini, ChatGPT, Claude, your choice) to find and describe your top 10 SKUs without giving it your URL. Ask it to tell you where to buy them, what the key attributes are, and what the current price is. Treat the output as a data quality mirror, not a novelty experiment.

What you’ll typically find falls into three categories.

• Invisibility: the LLM can’t confidently identify your products and defaults to competitors or generic descriptions. This means your product data has low presence in machine-readable, publicly accessible formats.

• Inaccuracy: the LLM finds something, but the attributes are wrong - outdated specifications, incorrect pricing, missing variants. This means your structured data exists but isn’t being maintained.

• Reasonable accuracy: the LLM returns something close to correct. This is your baseline to build from.

What this test is actually measuring is the downstream effect of your structured data markup (schema.org implementation), the completeness of your product catalogue in formats that crawlers and APIs can parse, and whether your digital presence is designed for machines as well as humans. Most retailers have built for the latter. Very few have actively thought about the former.

In my experience, the response most common among leadership teams when they run this test is surprise- not at being invisible, but at being inaccurate. They assumed “we’re online, therefore we’re findable.” What they discover is that being findable for a human and being findable for an agent are two entirely different standards.

Step 2: The API Inventory: Are You Agent-Permissioned?

Being discoverable is necessary but not sufficient. An agent that can find your products also needs to be able to query them programmatically- in real time, at scale, without being blocked by rate limits or returning HTML that a human has to interpret.

The question to ask your technology team is specific: Can an authenticated third-party agent query your product catalogue and receive structured, real-time data, including availability, pricing, and variants- in a machine-readable format?

If the answer involves phrases like “we’d have to build that” or “it’s available through our website scraping,” you are not agent-permissioned.

Think about what this means in practice.

Product discovery is already happening at scale outside your owned channels. Consumers are learning about products, comparing options, and forming purchase intent in places your CRM has never seen and your analytics will never capture.

When an AI agent eventually acts on that intent (querying for real-time availability and price before completing a transaction), it will need an API to talk to. If you don’t have one that’s designed for that interaction, the agent routes to a competitor who does.

The checklist here is straightforward:

• Is your product API publicly documented?

• Does it return structured data or HTML?

• Does it include real-time inventory signals?

• Can it handle the query volume of programmatic access without throttling?

These are not complex engineering problems but they require your focus and attention.

Step 3: The Identity Readiness Check: Can Agents Transact on Your Platform?

This is where the 26% checkout trust gap becomes a design brief. Consumers don’t trust AI agents with their wallets, at least not yet. The answer isn’t better marketing. It’s Trusted Agent Protocols: the tokenisation and delegated authentication infrastructure that allows an agent to complete a transaction without the consumer feeling they’ve handed over their raw financial credentials to a black box.

The practical audit questions here are:

• Does your checkout infrastructure support tokenised payment flows that could be initiated by a non-human agent?

• Can a third-party system authenticate against your platform and complete a purchase within a defined permission scope, without requiring a human to be present at every step?

If your checkout is designed exclusively around a human filling in a form, the short answer is that you are not ready.

The work to build these trusted agent protocols is already gathering speed. Google’s Universal Commerce Protocol (UCP) is an open-source standard is being built exactly for this.

Protocols like UCP establish a common language which enables seamless commerce journeys between consumer surfaces, businesses, and payment providers. Further compatibility with Agent Payments Protocol (AP2), Agent2Agent (A2A), and the Model Context Protocol (MCP) is the key.

Google’s full protocol documentation is linked here

Step 4 : The Data Quality Scorecard: Are Your Attributes Machine-Grade?

The last step is the most foundational and frankly, the one that takes the longest to fix.

There is a critical difference between product data that is “good enough for a human” and product data that is “good enough for an agent.“

Human shoppers can look at an image and understand context. By nature, human’s infer. We read a vague description and fill in the gaps from experience.

Agents don’t infer. They parse explicit, structured attributes and make decisions based on what is actually present in the data, not what a reasonable person might assume.

So, here is what a machine-grade product data looks like in practice:

• Every attribute is explicit and consistent (not “available in multiple colours” but “Colour: Navy Blue, Forest Green, Slate Grey”).

• Taxonomy is standardised across your catalogue

• Variant logic is resolved at SKU level, not parent product level.

• Pricing and inventory are real-time, not batch-updated.

An agent querying a specific size and colour needs to know availability for that specific combination, not the parent product.

However, what I’ve seen so far across multiple customer engagements is that this is where the most significant gaps live and where the investment pays back beyond agentic commerce.

Clean, structured, machine-grade product data doesn’t just serve agents. It improves search ranking, personalisation accuracy, and feed quality across every channel. Here is a wonderful reference article from Google which reiterates this point: For companies to succeed with agentic AI, they must shift from an incremental approach to a comprehensive data strategy that is ready for AI’s needs

This agentic commerce readiness audit is, in a practical sense, a forcing function for data governance work that should have been prioritised years ago.

Quick-Start Checklist: Here is what you can do now.

A comprehensive audit may take weeks to complete rigorously. However, you can start with these five actions immediately.

1. Run the LLM Test on your top 10 SKUs. Ask a general-purpose LLM to find and describe them without a URL. Log what it gets right, wrong, and what it can’t find. This is your baseline.

2. Audit your product API documentation. Is it publicly accessible? Does it return structured data? Does it cover real-time inventory? If your technology team says “we don’t have one,” that is your first priority.

3. Map your checkout flow against delegated authentication requirements. Where are the gaps for agent-mediated transactions? Flag this for your payments and identity infrastructure owners.This is a 2026 roadmap item, not a 2028 one.

4. Assign a data quality owner for agent-readiness. This is a Data & AI problem, not a marketing problem. It needs an owner with the authority to enforce attribute standards across the catalogue.

5. Review your highest-volume SKUs for attribute completeness at the variant level. Start with your top 100. The gaps you find there will be representative of the catalogue-wide problem and fixing them first gets you the highest agent-discoverability return for the least effort.

The Agent Doesn’t Care About Your Brand Story

The retailers investing in agent-ready infrastructure today aren’t doing it because they have a mandate from the board or because a vendor sold them a roadmap. They’re doing it because they understand something fundamental about Agentic Commerce:

The next competitive advantage isn’t a better app, a more immersive loyalty programme, or a sharper campaign. It’s being discoverable, transactable, and trustworthy to a customer who will never visit your website.

The Agentic Gap is real. Whether you’ll close it on your own terms, or discover it when an agent routes to a competitor instead, is to be seen.

And a question for you: have you run the LLM Test on your top SKUs yet? What did you find? Drop it in the comments. I’d genuinely like to know what readers are seeing in their own markets.

It was only recently that brands & retailers were gaining confidence in diverting their investment dollars behind the concept of Unified Commerce- where every channel is stitched together on a unified platform, every inventory count is reconciled with an ultimate objective to have a “single source of truth.”

But almost overnight, the conversation shifted again.

What was hailed as the holy grail just a year ago now feels like regular plumbing. The spotlight has moved to something new, something much harder to grasp: Agentic Commerce.

This is the paradox of our fast-changing time. Unified Commerce was supposed to be the endgame. Instead, it has now become the starting point for a far bigger transformation. The question isn’t just what Agentic Commerce is, but why this shift is happening so fast, how many organisations are actually ready to adopt this new wave of commerce and most importantly, what can retailers and brands do right now to stay relevant.

But first, let's take a quick look at this fascinating evolution of commerce unfolding in-front of us.

The Great Leap Forward: 25 Years of Commerce Evolution

If you dig into the last 25 years, commerce has never stood still. We can clearly see 5 distinct eras, each built on the last, reshaping how consumers discover, decide, and buy.

1. 2000–2009: The E-Commerce Genesis
   The early 2000s were the era of the digital storefront. A simple relationship: a shopper sat at a computer, browsed a website, and completed a transaction. Amazon, eBay, and Alibaba established the model- digital carts, one-click checkouts, and global reach.

2. 2010–2015: The Omnichannel Expansion
   As smartphones and apps exploded, commerce broke out of the digital box and merged with physical stores. This was the era of the connected experience: buy online, pick up in-store; return in-store; browse an endless aisle from your phone. Retailers invested heavily in making experiences consistent across channels.

3. 2016–2020: The Headless Liberation
   Next came the architectural shift. The front-end storefront was decoupled from the back-end engine, unleashing agility. Brands could innovate faster, launching new touchpoints without being tied to monolithic platforms. Think of this as the Lego block era of commerce. The founding of the MACH Alliance in 2020 gave this movement its global manifesto: Microservices, API-first, Cloud-native, Headless.

4. 2021–2023: The Unified Consolidation
   Inevitably, the pendulum swung back. With complexity everywhere, retailers realized they needed a central nervous system. Unified Commerce became the infrastructure backbone- a single source of truth for orders, inventory, customers, and payments. CommerceTools, Shopify, Salesforce, Oracle, and Adyen championed this model. For a brief moment, it felt like we had arrived.

5. 2024–2025: The Agentic Emergence
   And then came the shockwave. Suddenly, AI agents -autonomous systems capable of browsing, comparing, negotiating, and even buying, burst onto the scene. This wasn’t a marginal feature; it was a new interface layer entirely.

   Text within this block will maintain its original spacing when published

   If Unified Commerce was the nervous system, Agentic Commerce is the autonomous concierge standing between your brand and your customer.

Enter the Agent: The New Player in Commerce

So what exactly is Agentic Commerce?

At its core, Agentic Commerce is about AI agents acting on behalf of consumers. Unlike a chatbot or recommendation engine, these agents don’t just assist; they act. They can take a simple prompt- “Find me the best running shoes under $150 that deliver by Friday” and execute it end-to-end.

End-to-end execution: what does it mean? Well, you can think of it as a combination of discovery, negotiation & purchase.

• Product Discovery: Agents can browse multiple sites, scan catalogues, check reviews, and filter options without human guidance.

• Negotiation & Purchase: They can compare prices, apply coupons, ensure availability, and complete a checkout seamlessly.

All this can be done via multimodal inputs, i.e. through voice, text, or image. With this, agents can understand natural intent and translate it into action.

What Agentic Commerce is NOT

There’s a lot of hype around the word agent right now, and it’s worth clarifying what doesn’t qualify as “Agentic”

• Not just automation. A scripted workflow that follows pre-coded rules isn’t an agent. Agents are adaptive and can make autonomous decisions.

• Not just a chatbot. Chatbots respond within fixed boundaries. Agents go further; they interact with systems, make choices, and execute tasks.

• Not just a recommendation engine. Personalisation is useful, but agents don’t just suggest; they decide and close the loop.

• Not “human-in-the-loop.” Agents don’t merely assist; once intent is given, they can act independently to complete the journey.

In short: Agentic Commerce isn’t about better interfaces; it’s about autonomous intermediaries that operate between customers and brands.

Why This Matters

• Shift in Power: The entry point for commerce is no longer the storefront. It’s now the agent. If your brand isn’t visible to the agent, you’re invisible to the customer.

• Redefinition of Loyalty: Winning over the agent may matter more than winning over the shopper. When agents optimise for speed, convenience, or price, brand loyalty risks erosion.

• Compressed Journeys: What once took multiple clicks and touchpoints now happens in a single intent-driven step. Shopping journeys are going to get majorly impacted.

• New Discovery Battleground: SEO won’t be enough. Commerce data will need to be structured, discoverable, and interpretable by agents. We now have to optimise for Agents.

Each of the above-mentioned implication is not small and will / can have a transformational impact on how we shop and engage with brands.

The Big Elephant in the Room: Are We Ready?

Here’s the uncomfortable truth: most retailers are not.

Even in 2025, a large percentage of retailers are still trying to solve Unified Commerce 101 - getting clean product data, ensuring real-time inventory visibility across channels, integrating payments, and stitching together a single customer view.

When you zoom out, you see three tiers of readiness emerging:

• Digital Natives (D2C, e-com first brands): These companies are closest to “agent-ready” because their data, APIs, and systems were born in the cloud.

• Omnichannel Retailers (large chains, mid-market brands): Many have invested in Unified Commerce platforms, but integration is patchy. Product data is inconsistent, and APIs are not mature.

• Traditional Retailers (legacy-heavy): For these, even basic digital plumbing is a struggle. Agentic adoption will take years without structural overhaul.

And yet, the Agentic wave won’t wait. Consumers won’t hold back their agents from shopping just because a retailer isn’t ready. Which brings us to the critical question: what can you do now to prepare without getting lost in the noise?

Your Agentic Action Plan: Two-Part Strategy

Step 1: Finish the Foundation (Unified as Plumbing)
Unified Commerce is not optional. It is the plumbing that makes you agent-ready.

• Clean, consistent product data: Agents can’t buy what they can’t understand.

• Real-time integration across orders & inventory: Agents require accuracy to transact.

• APIs & composable services: Without open, modular systems, you won’t be able to plug into agent-driven ecosystems.

Step 2: Build for the Agent (Future-Readiness)

This is not about gimmicks. It’s about deliberately shaping your business to be discoverable, interpretable, and actionable by agents.

Here are concrete plays you can start now:

• Agent-First Product Data: Audit your PIM (Product Information Management). Is your catalogue rich enough for machines? Can an AI parse your product images, videos, sizing, and attributes without human help?

• Machine-Readable Offers: Move beyond banner ads. Structure discounts, promotions, and bundles as API-exposed objects so agents can factor them into purchase decisions automatically.

• Agentic Pilots: Launch controlled pilots where AI agents handle narrow, low-risk use cases e.g., automated reordering of consumables, personalised replenishment reminders, or B2B procurement bots.

• Design for Dual Customers: Start reframing your CX. The “customer” is both the human and their agent. Loyalty programs may need APIs so agents can seamlessly access, redeem, and optimise rewards.

• Adopt an Agent Orchestration Platform: Don’t just react to external agents (Google Shopping, Klarna, JD.com). Bring agent orchestration in-house by experimenting with AI/ML platforms. For enterprises, solutions like Google Cloud’s Vertex AI and Agentspace, Azure AI Studio, or AWS Bedrock provide secure, scalable ways to build, orchestrate, and manage agents across commerce use cases. For prototyping and innovation, frameworks like LangChain or CrewAI let teams experiment rapidly with multi-agent workflows before scaling to enterprise-grade platforms.

The Next Chapter in Commerce Evolution is already being written.

Every era of commerce has created new winners. Amazon set the bar for e-commerce with the digital storefront. Walmart and Target showed what true omnichannel looks like by blending store and online seamlessly. Shopify and CommerceTools unlocked the headless, API-first era of flexibility. The Agentic era will be no different — it will create its own leaders, and the question is whether your business will be one of them.

The winners of the Agentic Era will be those who get two things right:

• Unified Commerce as the backbone. Without it, agents can’t plug into your business.

• Agentic readiness as a mindset. Building for discoverability, machine readability, and agent-first engagement.

The fact of the matter is that flashy apps won’t matter. Clean, connected, contextual data will.

The story of commerce is one of constant reinvention. The real question: will your business ride the Agentic wave or get left behind?

Suggested Further Readings

If you’d like to explore further:

• McKinsey (2025) – Seizing the Agentic AI Advantage

• Bain ( 2025) Agentic AI Commerce hinges on consumer trust

• MACH Alliance Open Data Model

• a16z Blog (2025) – AI X Commerce

• Artificial Lawyer (2025) – What Actually Is an Agent?

TL;DR: Win With Context, Not Models

As LLMs and open-source models race toward parity, one truth is emerging: Intelligence is becoming cheap. Interfaces, workflows and adoption are the new moats.

Retailers & brands don't need smarter AI. They need simpler, more embedded, less interruptive AI which intuitively enhances the shopper experience while simultaneously improving operational efficiencies. This means efficient, more contextual workflows and better user interfaces. The best AI won’t feel like software. It will feel like magic, showing up in workflows and interfaces so seamlessly that you forget the model even exists.

From Model Performance to Usability: A Quiet but Massive Shift

For much of the past year, the AI conversation has been a leaderboard game: parameter counts, benchmark scores, token windows. GPT-5 vs. Claude 3 vs. Gemini 2.5. Actually, what started as just a short list has now grown into a long list of thousands of models, each vying for your attention and claiming to be the best.

But in the real world- on store floors, in merchandising cycles, in fulfilment centres, none of that matters. Retailers and brands don’t need “smarter AI.” They need simpler, more embedded, less interruptive AI that fits into the way people already work.

What matters on the ground is intuitive user interfaces and contextual workflows. A model can be powerful, but if the store associate can’t use it or if your shopper won’t wait for it, then what’s the point?

That means the focus has shifted to

• Workflows that anticipate actions instead of adding steps.

• Interfaces that feel invisible, not like another tool.

• Infrastructure that silently optimises in the background.

This quiet shift from model performance to usability is now defining how retailers and brands are adopting AI in their respective organisations. This post explores how the AI advantage in real-world settings won’t come from better models but from efficient workflows embedded in better interfaces

Shift to Contextual Intelligence

In the real world, retailers don’t succeed because they picked the “smartest” model. They succeed when AI shows up in context, inside the flow of work, at the exact moment a decision is made, with just enough guidance to remove friction. That’s contextual intelligence. Not “How clever is your model?” but “Where does it live, what does it change, and will people use it without thinking about it?”

Three important factors are bringing this context to life.

1. Voice & Multimodal: the post-dashboard era for non-desk work.

2. Agentic Co-Pilots in Workflows: assistants that nudge the next best action right inside POS/OMS/CDP/CRM.

3. Invisible AI Infrastructure: intelligence woven into the stack so the workflow just… happens.

Let’s unpack each of these through a retail lens.

1. Voice & Multimodal: The Post-Dashboard Era

Typing is slow, and no one likes sitting at the desk looking at dashboards. If your associate is juggling customers, carts, and a radio, they’re not logging into a BI tool. The new interface is voice + vision: you talk, you show, you gesture, and the system understands.

How it lands on the ground

• Store ops: A floor lead says, “Create a 2 pm facing task for Aisle 7; we’re out of 2-litre orange.” The assistant confirms, assigns, and pings replenishment. No app hunting, no forms.

• Planogram & merchandising: A category manager points a camera at the shelf, asks “What’s off-plan and why?” and gets a visual map with suggested fixes: facings, price mismatch, missing label, poor adjacency.

• Shopper UX: “Show me breathable running shoes under $120 that fit like my last purchase” returns a curated set along with the size guidance from prior returns and gait data captured in-store.

• Retail associate demos: Show an item to a camera “What fertiliser for this plant?”, get an answer plus one-tap add-to-basket for BOPIS or delivery.

Why this matters: Non-desk workflows dominate retail. The fastest path from intent to action is not via a screen; it’s now with voice or gestures as multimodality is moving AI out of the back office and into the aisle.

2) Agentic Co-Pilots: Embedded Where Work Happens

The second layer is deceptively simple: Instead of “AI tools”, start shipping assistance where the work is happening.

Agentic co-pilots sit inside POS, OMS, CDP, or CRM. They perceive context (inventory, velocity, weather, promo calendar, ticket backlog), propose the next best action, and often execute with a human in or over the loop.

How it lands on the ground

• Category & pricing: The AI Agent flags a pricing gap vs. local competitors, simulates promo uplift, and proposes a 7-day markdown ladder in a few clicks, then pushes changes to the price engine and shelf labels.

• Growth & CRM: Inside the CDP, the agentic copilot highlights an emerging audience (“high-margin, low-frequency, coastal stores”), drafts a 3-step journey, and wires an A/B test to MarTech with holdouts and guardrails.

• Service & Returns: A returns agent sees a summary of a shopper’s journey (purchases, chats, store visits) and the recommendation: approve refund + issue size-fit voucher. It's a one-click, policy-compliant action.

• Catalogue Enrichment: Onboarding products, creating engaging descriptions, and enriching catalogues, all via multi-agent workflows that integrate LLMs directly inside existing content systems.

The above use cases are now getting prioritised amongst retailers & brands for agentic copilot applications. The majority of these agents are now integrated into the respective functional applications like POS, Order management, promotion engines, etc.

Why this matters: Co-pilots reduce switching costs. No new logins, no parallel systems. Just a right nudge, in the right system, at the right moment, creates a major impact.

3) Invisible AI Infrastructure: Workflows That Just… Happen

The third layer is the least visible and the most powerful: intelligence in the foundational pillars. No prompts. No UI. Just systems that learn and adapt, shifting from rules-based to signal-based execution.

How it lands on the ground

• Predictive inventory: The network quietly rebalances stock based on store-level velocity, substitute risk, and last-mile constraints, much before a human would flag an issue.

• Computer vision at the edge: Shelf-gap detection and price-label verification trigger tasks, not tickets. Compliance becomes continuous.

• Fulfilment & last mile: OMS allocates orders to stores that can pick cleanly and deliver reliably based on live capacity, traffic, and SLA risk.

• Ops reliability: Equipment-failure prediction schedules maintenance windows to minimise peak disruption; staffing plans adjust automatically to demand signals.

Why this matters: This is contextual intelligence at its purest: no training or no adoption campaigns. It’s just in the stack and makes the system smarter.

All this is great, but how do you build trust with your customers?

Models can be opaque, but interfaces are where trust is earned. That’s true for shoppers (recommendations, promotions, refunds) and for employees (pricing, tasking, performance cues).

Few things we can do to build trust.

Show your work (why AI is recommending this price/promo/product), give control (clear personalisation toggles and easy opt-outs), set visible guardrails (what the AI will and won’t do), and make escalation effortless with human hand-off plus context. Do this for shoppers (recs, refunds, promos) and employees (pricing, tasking, performance cues) in the exact moment of action.

Treat ‘tone’ as part of the product, and design for suggest-and-approve by default in high-stakes flows. If people can see the rationale, override gracefully, and reach a human without repeating themselves, they’ll use it again. In essence, trust becomes a feature, not a policy PDF.

However, this requires a lot of unseen work under the hood. You can't win this trust without orchestrating the logistics behind it. It requires plumbing: clean identity and user consent, high-quality product and store data, and composable event streams from POS, e-comm, sensors, and last-mile collating on a shared data platform, which the agent can “see.”

Wrapping this into a callable policy engine (pricing/refund/compliance), with a lightweight explainability service a (couple of lines per decision), and observability (latency, overrides, policy blocks, SLA breaches) further strengthens this foundational layer.

When you get this right, your AI feels consistent and safe at scale, and your brand is seen as respectful & reliable in every moment that matters.

So, What Does This Mean for the Three Stakeholders

For Retailers: You must stop asking, “Which model?” and start asking, “Which workflow?” Where will this sit? What will it replace? How many steps does it remove? What policy will it respect? How will we measure trust?

For SaaS vendors: Your moat isn’t the model; it is integrated inside existing systems: POS hooks, OMS overrides, CDP audiences, policy calls. Offer suggest-and-approve modes and enterprise-grade explainability out of the box.

For Investors: Models are getting commoditised. Value creation happens when there is usage & adoption. Look for products with embedded, policy-aware agents and quantifiable evidence of time saved and decisions improved. Interface defensibility > model bragging rights.

Contextual Intelligence as Brand

As interfaces take centre stage, they start to carry something deeper: your brand. The tone of the voice assistant, the helpfulness, the clarity of an explanation- they shape how customers and employees feel about you.

A brand used to be colour, copy, and campaigns. Now, it’s also the experience of your AI: how it speaks, what it knows, when it steps back, and how it earns trust. That is not a “feature.” That’s how customers will see you at any given moment

And the real AI war won’t be won on parameter counts, it will be won in moments: a cashier line that never forms, a promotion approved in seconds, a shopper who feels known (and respected), a shelf that never looks empty, an associate who ends a shift less tired.

These moments happen when intelligence is contextual, embedded inside the workflow, through interfaces that feel natural, and infrastructure that simply works. When that’s true, the model fades to the background, and the experience takes the lead.

What are your thoughts on this shift? How are you seeing the "interface war" play out in your industry? Share your insights in the comments below.

TLDR

In H1 2025, venture capital in Asia's Retail & CPG tech is laser-focused on "Execution-First AI." This means backing API-first, domain-specific AI agents and modular solutions that deliver tangible ROI, not just experimental tech. From intelligent store operations to autonomous commerce and monetisation-first platforms, investors are funding startups that solve immediate P&L problems and drive measurable productivity and engagement across the value chain.

In this edition of Capital Signals, I look at some of these strategic shifts and key thematic trends shaping VC investments. For founders, operators, and investors, this is your cheat sheet to what’s heating up, where VCs are leaning in, and who’s solving real execution problems. Let’s decode what’s next.

Thematic Signals: Retail & CPG through the lens of Venture Capital in Asia.

If 2024 was about platform dreams and generative AI hype cycles, then 2025 is all about getting real. Across Asia, early-stage VCs are tightening their filters, seeking startups that solve real P&L problems with domain-specific intelligence.

To get a pulse on thematic signals, I have looked at 60+ early & late-stage startups within the Retail & CPG tech domain which raised fresh capital across the Asia-Pacific region. To ensure representation across the entire value chain, my research focused on innovative startups across six solution clusters: Customer Engagement, Unified Commerce, Data & AI, Store Operations, Supply Chain & Logistics and lastly Back Office operations.

Here are the 3 key thematic signals emerging from the venture capital activity we have seen so far in the region.

1. Execution-First AI is replacing Foundational AI

"Execution-First AI" is the new mantra; investors are backing AI solutions that deliver immediate, quantifiable business value by streamlining existing workflows and enhancing decision-making.

As a result, AI is no longer infrastructure; it's now seen as an execution engine. Moving past the large model hype, investors are now backing startups deploying deeply vertical AI—not just horizontal analytics—across marketing, store execution, and “perfect store” automation. Funding is targeting those who can prove revenue lift, stock optimisation, or campaign precision for physical and omnichannel retailers with sector-specific AI/ML models

The key drivers for investment in these solutions are their composable, stackable nature, their ability to deliver instantaneous actions and feedback, and their capacity to provide measurable revenue leverage.

Examples of Execution-First AI Startups

• Almonds AI (India) – Secured $1.9M Seed (Feb 2025) to build AI-powered loyalty and partner engagement solutions.

• Populix (Indonesia) – Closed $4.3M Series B (Apr 2025) for AI-based consumer research and insights to optimise product launches.

• Wrtn Co (Korea) – Raised $73.5M Series B (Mar 2025) for an AI content creation and assistant platform integrating multiple LLMs to perform commerce and marketing tasks.

• SleekFlow (Singapore): ($7M Series A+, Aug 2024) – Omnichannel Conversation Suite for AI-automated customer interactions.

• Leylah (India): ($1.46M Seed, undisclosed recent date) – AI-led platform enabling creators to seamlessly monetise content with affiliate links on social platforms.

• ReShop (Australia): ($17M Series B, Jan 2025) – FinTech platform transforming refunds into instant, value-driven processes to drive rapid repeat purchases.

Complimenting this drive for execution, Trusted & Scalable AI is becoming a priority

As retailers and CPG manufacturers integrate dozens of AI models—from productivity tools to customer engagement agents—the risk of unsecured, opaque, or misused AI grows significantly. Investors now recognise the need for platforms that ensure safe, compliant, and auditable AI operations, especially as autonomous agents scale across workflows.

Example of AI Governance Platform:

• Singulr AI (India) – Raised $10M Seed (Feb–Mar 2025) from Nexus Venture Partners and Dell Technologies for its enterprise-grade AI governance platform. It enables real-time monitoring, risk detection, and policy enforcement across generative AI and LLM deployments in retail, finance, and supply chain.

Why This Matters:

• This shift unlocks operational ROI and defensible IP. Investors are now demanding rapid, use-case-specific returns—AI tools that solve real-world brand/retailer challenges, improve metrics, and deploy in weeks, not years.

• As a result, funding is moving from core “plumbing” (POS, order orchestration, unified commerce SaaS) toward startups developing AI agents and autonomous orchestration tools that proactively manage marketing, pricing, supply chain, and operations, delivering business outcomes (e.g., auto-replenishment, dynamic pricing, customer re-engagement) with minimal human touch.

• SingulrAI’s funding shows that retailers and CPGs can’t afford uncontrolled AI proliferation, investors see high value in solutions that enable safe, cost-efficient AI adoption for business-critical use cases

2. Shift to Agentic and Autonomous Commerce

The commerce landscape is undergoing a significant transformation, driven by the emergence of API-first Agentic platforms that are strategically solving narrow pain points within the commerce stack, rather than attempting to rebuild entire systems from the ground up. This focused approach allows for rapid, precise innovation by building modular, autonomous AI agents. These agents plug seamlessly into existing retail stacks, handling everything from customer support to supply chain adjustments with minimal human intervention, focusing purely on outcome-oriented, self-learning execution.

This shift is reflected in venture capital trends, which now decisively target these AI-driven, agentic commerce solutions. This field is still rapidly evolving, attracting significant activity from global tech giants like Google Shopping (e.g., AI Mode, virtual try-ons, agentic checkout), OpenAI (exploring in-chat commerce and payment systems), and Perplexity (integrating AI-powered shopping and agentic browsing). In Asia, investors are particularly aggressive in hunting for such opportunities, recognising the immense potential for agentic solutions to redefine the region's dynamic retail landscape.

Startup Examples of Agentic & Autonomous Commerce (Asia, Recently Funded):

• Manus (China/Singapore): ($75M Series A, May 2025) – Automating e-commerce store management and merchandising via AI agents.

• Omnichat (Hong Kong/SEA): ($10M Series A+, Feb 2025) – Piloting fully agentic customer journeys, evolving conversational AI into autonomous engagement agents.

• Krutrim (India): ($44M early 2025) – Consumer-level agentic AI for productized autonomous workflows like booking or ordering.

• Antom Copilot (Ant International, China): (July 2025 upgrade) – AI agent for merchant payment services, expanding capabilities across integration, onboarding, and risk.

• ShopOS (India): ($20M Seed, June 2025) – AI-based OS using agents for core e-commerce tasks like listings and marketing

Why it matters:

• Rather than backing giant, monolithic platforms, VCs are supporting composable, stackable commerce solutions that plug into existing workflows, not rip and replace tech.

• Startups attracting the most funding are those that enable instantaneous actions and feedback (e.g., instant refunds, real-time recommendations, creator-triggered checkouts) versus those offering only incremental process improvement.

3. Operational ROI is the new benchmark.

Amidst tougher market conditions, VCs are converging around startups that promise and deliver clear, quantifiable improvements in operational ROI, especially across in-store execution, supply chain efficiencies, and back-office automation. What matters most to both founders and investors is proof of efficiency, cost takeout, and productivity improvements, not just digitising old processes.

Store Operations: Automating for Labour Efficiency & Consistency

What’s Shifting: VCs are backing platforms that minimise workforce complexity and automate staff-intensive tasks. Robotics, AI-driven scheduling, visual merchandising, and loss prevention are attracting capital due to measurable labour savings and improved compliance.

• Example Startups:

  • Flagship (Australia) — Digital visual merchandising SaaS for retail ($3.75M Seed, Coreline Ventures).

  • Deeping Source (Japan) — Vision AI for in-store process optimisation (Series B, KDDI).

  • Auror ( Australia ) -Crime / Loss prevention platform for retail.( $45M Series C, Reinventure Group)

  • StaffAny (Singapore) — AI-driven workforce scheduling, regionally expanding (Seed, Angel Central/Iterative).

Why This Matters: These solutions let retailers do more with less, boosting operational consistency while reducing staffing headaches and shrinkage.

Supply Chain: AI-Native, Platform-Led Orchestration

What’s Shifting: Investment is moving from asset-heavy or manual processes to cloud-native, automated, and highly visual supply chain platforms that offer real-time control and end-to-end transparency.

• Example Startups:

  • CapGrid (India) — AI-driven manufacturing supply chain traceability ($5M Series A, Nexus/Axilor).

  • CADDI (Japan) — AI-powered manufacturing procurement, global scale ($38M Late Stage, Atomico).

  • Locad (Singapore) — Cloud-native, API-led logistics orchestration for Southeast Asia ($9M Pre-Series B, Reefknot/Global Ventures).

  • BackOps AI ( India )- A supply chain automation startup focused on bringing AI into logistics and procurement workflows ( 46M, Seed, Construct Capital, Gradient, 10VC)

Why This Matters: These platforms enable brands and retailers to reduce/ optimise their supply chain & procurement costs and access to flex capacity, directly impacting margin and resilience.

Back Office: Intelligent Infrastructure and Agentic Automation

What’s Shifting: Funding now clusters around intelligent AI platforms for HR, payroll, finance, and IT Ops—moving beyond siloed digitisation toward agentic co-pilots, auto-finops, and collaborative SaaS.

• Example Startups:

  • HR Tech is very hot.

    • BrioHR (Malaysia) — HR SaaS platform streamlining workforce management and compliance ($6.5M Series A, Openspace Ventures).

    • OmniHR Singapore (Seed $7.4M Picus Capital, Alpha JWC, January Capital)

    • Darwin Box India -AI HRMS platform (Late Stage $140M Partners Group, KKR)

  • Lucidity (India) — FinOps platform optimising cloud costs for retail infrastructure ($21M Series A, Elevation Capital).

  • Hyperbots (Singapore) — Agentic AI for finance/accounting automation ($6.5M Series A, Arkam/Athera Ventures).

Why This Matters: Intelligent ops tools free up teams, highlight cost savings automatically, and enable fast, accurate decisions in complex operations, crucial for scale and profit discipline.

Bottom line is this: efficiency, automation, and ROI are now the core criteria for early-stage funding in Asian retail and CPG tech.

Final thoughts

This edition of Capital Signal scan clearly shows venture funding is prioritising execution-first innovation in Asian retail and CPG tech.

The era of generic platforms and theoretical AI is over. Instead, capital is flowing into composable, API-first solutions that artificial intelligence is directly embedded into operations. Investors are demanding sharper ROI, faster go-to-market, and measurable productivity and engagement gains.

The startups securing funding are those delivering these precise, verticalized tools – from AI agents enabling autonomous commerce to platforms driving monetisation and operational efficiency. Ultimately, the new benchmark for success in this space is operational ROI, demonstrating a clear shift from hype to tangible business value

AI in retail is evolving. But the next leap forward won’t happen in the cloud. It’s happening at the edge: on store shelves, POS systems, mobile apps and more. Stores are becoming intelligent.

Before the latest buzz and excitement around "Agentic AI" took centre stage, there was a growing conversation around ‘Edge AI’; a concept that promises to transform industries by bringing intelligence closer to where the action happens, rather than relying solely on distant data centres. Now, with the release of lighter, more efficient AI models, the conversation is back. We now have the ability to run cost-effective AI directly on in-store platforms, unlocking unprecedented levels of efficiency, personalisation and competitive advantage. For retailers and brands, this is a game-changer.

But what exactly is Edge AI, and why does it matter now?

The concept of "edge computing" isn't entirely new. Many of us, particularly those with a background in the tech domain (like my own), will recall conversations about pushing computation closer to the data source to reduce latency. For a long time, this vision was primarily about optimising data transfer and running traditional software locally. It was largely the domain of hardware specialists focused on network efficiency. This is no longer the case, as the launch of highly efficient and specialised AI models has now added true intelligence to these edge devices.

It's crucial, though, to distinguish between general Edge Computing and Edge AI. Let's look at this first.

• Edge Computing (Broader Concept): This involves processing data near the source (at the "edge" of the network) to reduce latency, conserve bandwidth, and enhance reliability. It can involve simple data filtering, aggregation, or even running traditional software applications locally. Think of it as the foundational infrastructure that enables Edge AI. For example, a local server in a store that caches product information so POS systems can access it faster than going to the cloud, or a sensor that sends aggregated temperature data from a freezer, but doesn't interpret that data.

• Edge AI (Specific Application of AI at the Edge): This specifically involves running AI models ( like machine learning, deep learning, or generative AI models) directly on edge devices to perform tasks that require intelligence, pattern recognition, and decision-making locally. It's not just moving data processing; it's moving the smart part of the processing to the edge.

So, while "Edge Computing" provides the proximity and local processing power, "Edge AI" adds the brain, allowing for truly automated, intelligent responses at the source.

What's different today, and what makes Edge AI truly potent, is the advent of lighter, more efficient AI models. The emergence of compact yet powerful models like Google's Gemma, alongside other optimised frameworks ( such as TensorFlow Lite, PyTorch Mobile, and ONNX Runtime ) and smaller language models (SLMs) like Meta's Llama 3 (8B) or Microsoft Phi, has fundamentally shifted the landscape.

These innovations mean that sophisticated AI capabilities are no longer exclusively tied to massive cloud data centres. They can now run effectively on less powerful, more cost-effective edge devices – from in-store cameras and POS systems to robotics and smart interactive devices. This is a game changer as it finally enables retailers to truly "raise the bar for in-store execution and shopper experience" by embedding intelligence directly where it matters most.

The Business Case: Is Edge AI Worth the Investment?

The short answer is yes, and the Return on Investment (ROI) can be substantial. Reports from industry leaders like KPMG and Google Cloud's 'The ROI of Gen AI in Retail and CPG' consistently show strong returns, with Google's research indicating that 74% of enterprises leveraging Gen AI are seeing ROI within the first year, and 86% of those achieving revenue growth estimate gains of 6% or more. While this isn't exclusively Edge AI, it speaks to the broader value AI brings, and Edge AI specifically targets many high-value use cases that drive these returns.

The benefits around cost savings, increased revenue potential and improved operational efficiencies are reasons enough as to why retailers and CPGs should seriously consider investing in this capability. Let me explain this.

• Significant Cost Savings:

  • Costs associated with cloud infrastructure and bandwidth can be significantly reduced

  • Labour costs can be reduced through automation of in-store tasks like inventory checks, merchandising audits, and even checkout. In addition, reduced losses from shrinkage and improved inventory management make a significant impact. For instance, industry reports and case studies show Edge AI surveillance has been instrumental in reducing theft-related losses by up to 25% (or even higher in some instances)

• Increased Revenue Potential:

  • Improved product availability due to real-time stock management can prevent lost sales.

  • Effective personalisation and targeted promotions can drive higher conversion rates and basket sizes; Edge AI for personalised marketing has been shown to increase conversion rates by approximately 10-15%.

• Operational Efficiency:

  • Faster decision-making and response times to in-store events can directly lead to better in-store execution.

  • Streamlined workflows for store associates allow them to focus on higher-value customer interactions.

Early adopters of Edge AI can gain a significant edge by delivering superior customer experiences and operating with greater efficiency than their competitors. A better shopping experience leads to higher customer satisfaction, loyalty, and repeat business.

For a 500-store retail chain, for example, a mere 30-basis-point reduction in shrinkage could translate to millions in annual cost savings. Likewise, preventing persistent stockouts could unlock significant incremental sales. Benefits from such investments are compelling.

While the benefits are clear, let's take a realistic view of Edge AI adoption as it comes with its own set of challenges.

Often, these challenges revolve around hardware limitations, data management complexities, and integration with existing systems. Edge devices may have limited processing power, memory, and battery life, requiring careful model optimisation. Managing data across distributed edge devices and ensuring seamless updates can also be complex. Furthermore, a shortage of AI skills and concerns about data privacy and security (despite Edge AI's inherent benefits) need to be addressed.

While I say this, it's not just doom and gloom as continuous innovation is happening as companies look to develop edge AI platforms to simplify deployment, monitoring and upgrades across a large set of devices, much like cloud software deployments.

So, how do Retailers & Brands adopt Edge AI? Where to start from?

Adopting Edge AI doesn't necessarily mean a complete overhaul of existing infrastructure. It's more about a strategic re-think and incremental steps.

Start by pinpointing specific pain points or opportunities where real-time, localised intelligence can deliver the most significant value. Loss prevention, out-of-stock prevention, or enhancing customer service at peak times are often good starting points.

Once you understand your high-value use cases, begin with small-scale pilot deployments in a few stores or a specific product category. This allows for testing, learning, and refining the solution before a broader rollout. Focus on proving the ROI in these initial pilots.

While Edge AI aims to reduce reliance on the cloud, it still requires capable hardware at the edge (e.g., smart cameras, edge servers, robust Wi-Fi). Evaluate existing infrastructure and make necessary upgrades to support AI processing on-device. And remember: Edge AI isn't about completely abandoning the cloud. A robust strategy involves a hybrid cloud approach:

1. Edge: Real-time data processing and immediate decision-making.

2. Cloud: Long-term data storage, model training and refinement, enterprise-wide analytics, and remote management of edge devices. This allows for the continuous improvement of AI models based on aggregated insights.

While the above-mentioned points around infrastructure are important, don't forget about data governance and privacy. Establish clear policies for data collection, processing, and storage, especially concerning customer data. Transparency in how AI systems use data will be key to building customer trust.

Invest in talent and train staff on how to interact with and leverage Edge AI systems, ensuring they understand the benefits and how these tools augment their roles. Lastly, choose solutions which offer flexibility- by that I mean, opt for solutions that offer modular architectures and can easily integrate with existing retail systems (POS, ERP, CRM) via APIs. This ensures that as your AI strategy evolves, your technology can adapt.

Edge is where the action is.

The conversations around agentic AI are exciting, pointing to a future where AI systems act with greater autonomy. Yet, for industries like retail and CPG, the true immediate impact often lies closer to the ground, at the "edge."

If generative AI is about creating intelligence, Edge AI is about translating that intelligence into immediate, tangible action.

The global Edge AI market is projected to grow significantly, with retail being one of the leading sectors for adoption. The convergence of Edge AI with 5G networks, for instance, promises even more seamless and powerful applications in smart retail spaces.

The next wave of AI-driven innovation in retail won't just reside in massive data centres. It will live on the shelf, in the hands of associates, and within connected experiences where milliseconds matter. By embracing this shift. Retailers & brands gain more than just speed; they gain control, context, and a powerful competitive advantage in an increasingly dynamic market.

TL;DR

The last few months were full of energy and momentum. NRF Singapore brought the industry together around store transformation, automation, and the future of AI in retail. In parallel, Agentic AI moved closer to real-world deployment, while embedded AI gained traction inside POS, OMS, and supply chain tools. Voice-first interfaces and open-source agentic frameworks are gaining traction— with serious implications for how retail gets built and run.

Meanwhile, across Asia, retailers are making bold tech bets: Reliance and Central Retail are deepening unified commerce infrastructure, FairPrice and Mecca are reimagining store formats, and BigBasket is going all in on Q-commerce. Add a $120M raise by Jumbotail, new funding across the Indian retail stack, and award-winning loyalty innovations in Singapore, and you’ve got an interesting pulse check that’s more than just noise. Let’s look into it.

TECH WATCH

* Agentic AI moves into product territory
We’re seeing early signs of Agentic AI frameworks becoming part of real-world applications. Google’s Agentspace, LangChain’s LangGraph launch, and Shopify’s AI agent co-pilot experiment hint at the future of autonomous workflows in commerce.

In addition, open-source Agentic frameworks like LangGraph (LangChain), CrewAI, and Autogen are enabling the next generation of agentic applications. These frameworks allow developers to build AI assistants for planning, workflow automation, and intelligent orchestration. Google Cloud has also entered the space with its new Gemini Agent Builder CLI, designed to help teams create custom agents with multi-step reasoning and tool orchestration capabilities..

Why it matters: Agentic AI could transform retail operations — from autonomous merchandising suggestions to fully automated marketing workflows and predictive service automation. Plus, Retailers can now prototype AI agents — from marketing planners to dynamic merchandising assistants, using low-cost, open-source or cloud-native tools that support intelligent automation and orchestration.

* Voice interfaces are heating up
Google is pushing the boundaries with Project Astra and Gemini Live, moving toward intelligent assistants with ambient context and fluid interactivity. Add to that, Apple Intelligence and OpenAI’s GPT-4o release show the next battlefront: voice + multi-modal.

Why it matters: Expect new customer experiences, including voice-led search, guided discovery, and shoppable agents to become a reality by the end of 2025. It will change the way customers search, discover, and transact.

* Embedded Retail AI is becoming the preference
Instead of standalone tools, we’re seeing AI features being embedded directly into POS, OMS, and merchandising platforms. Tools like Salesforce AI, Google Vertex AI Search, Blue Yonder and SAP Joule are making AI ambient and native to retail workflows.

Why it matters: AI adoption will accelerate when it’s invisible - embedded into tools retailers already use, not layered on top as an extra platform. This “native AI” approach is what retailers will prefer.

SIGNALS FROM THE FIELD

A scan across 4 Innovation clusters + StartUps making waves.

Unified Commerce

• Central Retail Thailand just announced a USD 1.38B expansion plan with major investments in their unified tech platform for omnichannel experiences and AI integration. Big push on unified commerce capabilities.

• Reliance Retail (India) is doubling down on its unified commerce play through the continued rise of JioMart -integrating digital commerce, kirana partnerships, and its offline network into one seamless ecosystem

Store Transformation

• FairPrice Singapore showcased its Next-Gen Store of Tomorrow at NRF Singapore with smart shelves, mobile checkout, and RFID-powered replenishment.

• Mecca Brands, Australia is launching their biggest beauty store incorporating new shopping experiences and tech innovations. New Store format for beauty retailing.

Supply Chain & Fulfillment

• BigBasket India is doubling down on Quick Commerce with new micro-fulfillment centers across major metros. The goal: reduce delivery times to under 20 minutes while optimizing last-mile logistics using real-time demand signals.

• Libiao Robotics & Botsync at CeMAT SEA (Singapore) rolled out "T-Sort" box-sorting robots and AMRs (autonomous mobile robots) for tote handling and inventory replenishment in urban logistics hubs, showing robotics moving beyond prototypes to real deployment

Customer Engagement / Martech

• Lotte Korea launched a cross-brand loyalty app integrating hyper-personalised offers.

• NTUC Link (Singapore) Their revamped loyalty program, integrated into the FairPrice Group app, won Loyalty Programme of the Year and Retail App of the Year at the 2025 Retail Asia Awards. They now allow users to earn and redeem points across grocery, F&B, and lifestyle partners, powered by gamification and deeper digital pathing

Startups Making Waves

India startup ecosystem especially in the area of commerce is red hot right now.

• Jumbotail (India) raised $120M to expand its B2B retail platform and supply chain infrastructure.

• ShopOS (India), an AI-powered e-commerce “operating system” enabling brands to automate listings, marketing, and store setups, raised $20M led by Flipkart co-founder Binny Bansal’s fund.

• Zilo (India), a fashion-tech startup focused on quick-commerce for urban apparel retail, raised $4.5M in seed funding co-led by Info Edge Ventures.

ICYMI

Here are some interesting weekend reads - related & super relevant content.

• Future of Retail: Six Disruptions (Bain & Co.)
  A forward-looking scan of six structural shifts, from AI to platforms that will redefine global retail over the next decade.

• The Race to Become a System of Action (Tidemark Capital)
  Explores how modern SaaS companies are moving beyond data visibility to become platforms that drive real-time decisions and execution.

• Emerging Developer Patterns for the AI Era(a16z)
  A deep dive into how the AI-native stack is changing software development, with new roles for agents, orchestration layers, and feedback loops.

TL;DR:

Stop just counting cloud costs! To truly master cloud economics, retailers must move beyond basic cost tracking, embrace FinOps and focus on business-centric metrics. And as AI gets embedded into business operations, leverage it, especially Agentic AI, to optimise cloud investments and drive ROI. It's about shifting from cost-centric to value-driven spending, ensuring your cloud strategy directly fuels business growth.

The ROI Riddle: Why Retailers Struggle with Cloud Investment Value

Cloud bills often hit retailers like a ton of bricks, leaving many wondering if—or how much—of that cost is actually justifiable. For retail companies, where margins are notoriously tight and every dollar counts, cloud expenses rank among the largest expenditures.

Globally, retailers are pouring billions into cloud adoption year after year, drawn by promises of agility, enhanced security, and rapid innovation. As AI adoption continues to accelerate, cloud spending has gained even greater urgency. Just look at the projected growth of the global retail cloud market: it's expected to more than double from $47 billion in 2023 to a staggering $115 billion by 2028.

Yet, despite these skyrocketing annual expenditures, most retailers genuinely struggle to quantify the actual return on these massive investments. A recent PwC survey laid bare the extent of this industry-wide problem: nearly half of companies have no clear understanding of their cloud ROI, leaving billions in technology spending without proper financial justification.

This highlights a critical gap between digital promise and measurable value. And that’s precisely where cloud economics steps in. Many retailers still mistakenly link it solely with cutting cloud infrastructure costs. But true cloud economics isn't just about saving money; it's about value-driven cloud spending. It's about strategically investing in the right cloud capabilities that unlock new revenue streams, vastly improve customer experiences, enable faster innovation, and accelerate your time-to-market. As AI rapidly becomes an integral part of retailers' operational fabric, the stakes are even higher.

The real question retailers need to ask is not how much they are spending but rather, "How can we move beyond basic cost tracking and start measuring cloud investments directly in terms of business outcomes?" And, "What does it truly take to shift from a cost-centric to a value-driven cloud strategy?"

In this article, we'll explore cloud economics in a retail world where every decision must demonstrate impact and examine how retailers can adopt a more holistic approach focused on measurable business outcomes. Let's dive in.

Understanding Cloud Economics in the Retail Context

Cloud economics is far more than just optimising cloud spending. While cost-cutting is important, it's never the sole objective. At its core, cloud economics is about finding the sweet spot: balancing cost efficiency with the ability to scale resources on demand and the realisation of tangible business value from every cloud investment.

When retailers move to the cloud, they shift from huge, upfront capital expenditures (CAPEX) on hardware to an operational expenditure (OPEX) model, paying for computing resources as they use them. While this offers greater financial flexibility, it also demands far more intentional management of usage, intelligent scaling, and meticulous expense tracking. Without effective governance, cloud spending can quickly spiral, leading to wasted resources and reduced profitability.

Consider those hidden costs: data egress fees (moving data out of the cloud) and API calls often go unnoticed until they hit your monthly bill. Or think about peak shopping seasons like Singles' Day or Diwali. They cause sudden usage spikes, but if you don't efficiently scale down resources afterwards, you'll incur unnecessary spending during quieter periods.

Another major challenge is the sheer lack of visibility into which departments or services consume the most cloud resources. Without clear accountability and granular insight, teams might unintentionally overuse or underutilise infrastructure, missing optimisation opportunities. A flexible pay-as-you-go model can easily become a complex, fragmented cost centre if not actively managed.

Given this complex landscape, a sound understanding of cloud economics isn't just important—it's absolutely mandatory. It's your best defence against rude shocks and business breakdowns. Every retailer needs a clear strategy for measuring the digital ROI of their cloud investments.

Key Metrics to Measure Digital Investments in the Cloud

Most major Asian retailers have developed comprehensive cloud and data strategies designed to enhance agility and collaboration across their operations. For instance, Singaporean retail chain FairPrice has heavily invested in cloud-based systems for real-time decision-making, ensuring product availability and affordability. They've deployed automated warehouse systems to boost efficiency, implemented inventory tracking to minimise stockouts and waste, and are optimising in-store technology with cloud solutions.

But the real question is, as a retailer, how can you determine if your investment in cloud solutions is truly paying off?

The starting point for evaluating your cloud investments involves cost efficiency and optimisation metrics, which help you minimise cloud expenses without compromising performance.

There are various KPIs for evaluating cost-effectiveness in the cloud. The most fundamental is taking a comprehensive view of the Total Cost of Ownership (TCO) of running applications in the cloud versus maintaining them on-premises. This gives you a complete picture, accounting for often-hidden expenses like maintenance, infrastructure upgrades, and staffing.

Another increasingly popular metric is calculating the cloud cost per transaction. Assessing earnings against cloud expenditure for every transaction provides a granular lens to examine unit economics and helps you make smarter decisions.

Additionally, tracking cloud infrastructure costs relative to customer acquisition and growth can better assist in achieving scalability and cost-efficiency. For instance, Tokopedia, the Indonesian e-commerce giant, manages its cloud spend by utilising autoscaling features. This allows their infrastructure to automatically expand to handle the massive traffic spikes during Indonesia's huge online sales events (like Ramadan or national shopping days) and then shrink back down during low-traffic periods. This dynamic adjustment directly prevents them from paying for unnecessary infrastructure that would otherwise sit idle.

However, cost metrics alone don't paint the full picture. A more strategic approach to measuring cloud ROI requires linking technical initiatives directly to business impact and value metrics.- revenue impact, customer growth, retention and engagement, faster market entry, and supply chain efficiency.

These critical but often overlooked metrics demonstrate how cloud investments truly drive business growth and customer satisfaction. For instance, Flipkart uses cloud solutions to personalise recommendations and run targeted marketing campaigns while leveraging analytics to improve customer segmentation and promotion effectiveness.

Tracking improvements in repeat purchases and customer lifetime value shows the direct revenue impact of cloud-enabled features like personalised recommendations. Additionally, measuring how cloud platforms accelerate the development and deployment of products, services, and campaigns or enhance inventory accuracy and demand forecasting can prove invaluable in quantifying cloud ROI.

The third approach to digital ROI measurement revolves around performance and agility metrics. These metrics focus on the operational responsiveness of cloud-based systems.

In a digital-first world where even milliseconds matter, page load speed and latency have a direct impact on user experience and, by extension, conversion rates. Retailers operating in mobile-first Asian markets understand this acutely. Being able to remain consistently fast and responsive across markets, adjusting & adapting to demand fluctuations and ensuring a quick disaster recovery time are crucial metrics to measure as well.

Essentially, measuring digital investments in the cloud isn’t just about watching the bottom line. It’s about understanding how these investments fuel business growth, provide operational agility, and fulfil customer satisfaction. To truly unlock the value of cloud computing, retailers must shift focus from mere cost-cutting to the strategic priorities that drive long-term growth.

So, what are the actionable Insights for Retailers & Brands?

Well, it’s no longer viable to treat cloud costs as an afterthought. Passive tracking doesn't work anymore, hence retailers need to have a more intentional & proactive approach—one that actively aligns cloud investments with tangible business outcomes. Here's how you can get started:

Adopt a FinOps-Driven Cloud Strategy for Cost Optimisation

Understanding your cloud bill is only the beginning. What truly moves the needle is shifting from passive cost tracking to active cost optimisation, ensuring that your cloud investment is powering actual growth.

That’s where FinOps comes in. Think of it as the financial operating model for the cloud. It brings finance, IT, and operations teams together to keep a constant eye on costs, make quicker, smarter calls, and avoid those dreaded surprise bills. When every team is on the same page, it’s far easier to ensure cloud spending aligns with business goals and gets the most out of every dollar. This isn’t a one-time exercise. As your operations evolve and grow, creating a systemic way of monitoring, analysing, and adjusting cloud spends that suits your business needs becomes non-negotiable.

Retailers often miss out by ignoring built-in cloud tools—either because they’re unaware or find them too intimidating. Yet, utilising tools provided by cloud providers or third-party solutions can help you gain real-time visibility into cloud spending, pinpoint areas for optimisation, and flag anomalies before they balloon into wasteful spending.

Apart from cost monitoring, look at automating workflows, which can help in identifying and shutting down idle instances and diverting workloads to more cost-effective environments. Set up automated alerts for budget thresholds, real-time dashboards for detailed visibility, and AI-powered forecasting tools that anticipate future expenses based on past trends and market behaviour.

Going a step further, implementing a chargeback model by allocating cloud costs to specific teams, departments, or projects can create ownership and accountability. When each team understands their cloud spend and how it ties to business outcomes, they’re more likely to be proactive in managing it.

Then comes the problem of having to manage a multi-cloud or hybrid cloud deployment, which, if not managed strategically, can spiral out of control.

To make it work, you need to carefully evaluate which workloads are best suited for different cloud environments, balancing cost, performance, and security requirements. Not every cloud is equal; some tasks might run faster or more efficiently on one platform, while others could be more secure or easier to integrate elsewhere.

Before making a decision, consider how each cloud handles performance, security, and compatibility with existing systems. Because what looks like a cost-saving move on paper could end up creating bottlenecks or hidden expenses down the line.

Focus on Business-Centric Metrics to Drive Value

Beyond active cost optimisation, the most important question a retailer needs to ask is, “What business value is the cloud actually delivering?”

The answer to this lies in moving beyond simply tracking spends and looking at how your cloud investments are driving key business outcomes. For instance, are your personalised recommendations improving conversion rates? Is real-time inventory tracking reducing stockouts? Is your AI-based demand forecasting helping you optimise supply chain decisions?

Measuring these might feel a bit outside your comfort zone, but it’s where the real value lies. Your cloud strategy should ultimately support key business goals, whether that’s faster time to market, vastly better customer experiences, or significantly increased operational efficiency.

Lastly, create a holistic view of cloud value by combining metrics that show the combined impact of different cloud implementations. Bring it all together—how AI-powered personalisation is lifting customer satisfaction, how demand forecasting is improving inventory turnover, how predictive maintenance is cutting downtime, how dynamic pricing models are boosting margins, and how scalable infrastructure is enabling faster market expansion. When you connect these outcomes, you tell a powerful story: the cloud is not just another cost but a true growth engine.

At the end of the day, cloud success for retailers doesn’t come from simply spending less but from spending smarter. With the right FinOps mindset and a sharp focus on business impact, you can ensure your cloud investments are driving real, measurable value.

Future Trends in Cloud Economics: AI-Powered FinOps and the Rise of Agentic AI

With AI transforming every facet of execution, cloud economics is also becoming smarter, faster, and more autonomous than ever before.

We’re already seeing AI-powered FinOps reshape how businesses approach cloud cost management. Where traditional FinOps often relies on teams manually digging through dashboards and reports, AI steps in as your always-on analyst. It can scan massive datasets in real time, pinpointing hidden inefficiencies, accurately forecasting trends, and making intelligent suggestions.

Let’s say you're running a major promotional campaign. Instead of waiting until the end of the month to see how much you overspent, AI can flag unexpected spikes in usage as they happen, recommend ways to adjust workloads on the fly, and even initiate corrective actions automatically. This kind of real-time optimisation simply wasn’t possible before. Even better, machine learning models can analyse historical usage patterns to predict future cloud spending with a surprising degree of accuracy. That’s a game-changer for budgeting and resource planning. Rather than relying on estimates, you'll have data-driven forecasts that adapt to your actual usage trends, such as seasonality, peak demand days, and more.

But we’re only scratching the surface here. The next big leap is something even more transformative: Agentic AI.

Beyond simply analysing, predicting, and suggesting, agentic AI takes action. These AI agents can monitor your entire cloud environment in real time, identify inefficiencies, and then implement changes on their own, often without waiting for human approval. They’re like your cloud-finance autopilot that is always optimising in the background, relentless and tireless.

Imagine an AI agent that not only scales your infrastructure dynamically but also actively negotiates better pricing tiers with your cloud provider based on real-time usage trends. Or one that enforces FinOps policies dynamically across different teams, automatically adjusting workloads, shutting down idle resources, or reallocating budgets in the blink of an eye.

So, if you're planning your next wave of cloud transformation, now is the time to start thinking about how AI can augment your FinOps strategy. Begin by adopting AI-driven analytics and forecasting tools. Then, as your team matures in its FinOps practice, explore more autonomous solutions that can scale with your ambitions. Cloud economics is rapidly evolving, and the retailers who embrace AI early will be the ones who truly turn cloud cost management into a competitive advantage.

Moving from a Cost-driven to Value value-centric approach

There is no doubt that the Cloud infrastructure has truly emerged as the backbone of modern retail operations. But just being in the cloud isn’t enough anymore. The real differentiator—and the key to unlocking its full potential—lies in how you manage it.

The retailers that will lead in the coming years are the ones who stop looking at the cloud purely as an expense and start seeing it as a powerful driver of business value. That means fundamentally shifting your mindset from "How much are we spending?" to "What are we getting for that spend?" The difference might sound subtle, but it’s absolutely transformational.

Customer data is the new currency of retail. And everyone wants a piece of it !

From the moment we browse a product online to the loyalty points we accrue in-store, our every interaction is being recorded and analysed. This is the battleground of the Retail Data Wars, where brands, retailers, and consumers are locked in a high-stakes struggle for control over customer data, a resource as valuable as any product on the shelf. This conflict isn't just about ownership; it's about power, trust, and the very future of personalised commerce.

This insatiable hunger for customer data, where 'everyone wants a piece', is fueling a growing consumer frustration. Consider the opaque data collection practices, the constant stream of retail data breaches, and the pervasive feeling of being tracked across every online platform. The result? A surge in consumer distrust, a growing demand for ethical data practices, and a push for greater accountability, forcing a rethink of the way retail data is being managed.

The stakes are high. For brands, data translates to product innovation and customer loyalty. For retailers, it drives targeted marketing and operational efficiency. And for consumers, it's about reclaiming control over their personal information and ensuring a secure, personalised shopping experience.

This blog delves into the core of this conflict: who truly owns customer data, how brands, retailers, and shoppers can coexist in a data-driven ecosystem, and, more importantly, what’s the best way to navigate this contentious landscape. Let’s explore these competing claims, the legal and ethical grey areas, and how we can work towards building a viable and trustworthy data ecosystem for all.

The Battle Lines: Defining Data Ownership

The evolving retail landscape is a battleground for consumer data, with each stakeholder claiming rightful ownership. Retailers assert their control over transaction data and customer journey insights, arguing these are generated within their physical and digital environments. They rely on this data for targeted and personalised marketing, inventory optimisation, operational efficiency, and competitive advantage.

Brands, however, counter that consumer relationships revolve around their products, not retail platforms. They emphasise brand loyalty and reputation as the true drivers of purchases, arguing that customer insights are essential for product innovation and meaningful customer connections.

Consumers, on the other hand, are becoming more aware of their central role in this puzzle. Empowered by data privacy regulations, they are now beginning to insist on their inherent ownership of personal information. They demand transparency and control over data collection and usage, seeking personalised and convenient shopping experiences without compromising their privacy.

This conflict reflects the complex reality of modern commerce, where data simultaneously represents business intelligence, competitive advantage, and personal privacy. The viable path forward likely involves a balanced framework acknowledging the legitimate interests of all parties rather than an absolute victory for any single stakeholder.

Achieving this, however, is particularly challenging in Asia's diverse markets, each with its unique technological, cultural, and regulatory landscape.

The Erosion of Trust: Legal, Ethical, and Experiential Consequences

The battle for data ownership has far-reaching consequences, impacting not only legal and ethical considerations but also the fundamental relationship between retailers, brands, and consumers.

1. The Reshaping of Ownership: Data Privacy Regulations

First, let's examine how data privacy regulations are reshaping ownership dynamics. Key markets across Asia have implemented stringent frameworks—India's Digital Personal Data Protection Act, China's Personal Information Protection Law (PIPL), and Singapore's Personal Data Protection Act (PDPA), among others—all shifting power towards consumers by requiring greater transparency and explicit consent."

Traditional implied consent models—where customer approval was assumed through passive actions—are being rapidly phased out. Regulators now deem implied consent insufficient, especially for sensitive data, and demand explicit, informed consent through active opt-ins and specific permissions, reinforcing consumer rights, transparency, and data security. Consequently, privacy policies and terms of service have become critical tools. Though enforcement varies by region, non-compliance carries significant penalties.

This shift has forced Asian retailers and brands to redesign customer journeys, consent interfaces, and data collection methods, adding friction but building trust. Prioritising transparency and ensuring compliance with regional regulations has become inevitable, not just for legal protection, but to maintain consumer trust in an increasingly privacy-conscious marketplace.

2. The Core Challenge: Data Silos and Erosion of Trust

However, the core challenge remains: data silos and the resulting erosion of trust. Building a collaborative ecosystem grounded in legal and ethical data-sharing practices among retailers, brands, and consumers is easier said than done.

Data silos, where customer information is isolated within different departments or systems, create disconnected and frustrating experiences. For example, a customer who buys an item online but decides to return it in-store often encounters staff who lack access to their online purchase history, resulting in confusion and delays. While some retailers like Sephora Asia and Central Group have advanced unified commerce strategies, most traditional retailers still grapple with fragmented systems.

Equally important is the growing consumer distrust driven by hidden data collection practices and opaque data usage. For instance, many large retailers have come under scrutiny for collecting vast amounts of user data, including detailed browsing behaviours and purchase histories. In addition, frequent data breaches make things worse for retailers and brands, leading to consumer anxiety and erosion of trust.

3. The Added Complexity: Data Localisation

To further complicate matters, data localisation requirements in many Asian countries force companies to store data within specific regions. This adds complexity, increases operational costs, and challenges retailers to maintain consistent customer experiences while safeguarding data privacy across different regions.

Navigating these challenges requires a careful balance of integrated data practices, transparent communication, and rigorous compliance with evolving regulations.

Building a Mutually Beneficial Ecosystem: Strategies for Collaboration

The future of retail data hinges on building a mutually beneficial ecosystem that empowers consumers, builds trust, and creates a win-win scenario for all stakeholders. Achieving this collaborative vision requires a multi-layered approach, including:

1. Leveraging Zero-Party Data: Prioritizing data explicitly and willingly shared by consumers to build trust and personalize experiences.

2. Secure Data-Sharing Agreements: Establishing clear and robust agreements between brands and retailers to govern data exchange.

3. Customer-Centric Data Platforms: Empowering consumers with control over their data through innovative platforms.

4. Transparency and Consent: Adhering to transparent data practices and obtaining explicit consent from consumers.

Underpinning these strategies must be stricter data laws and legal policy frameworks that ensure accountability and protect consumer rights. Let's explore each of these in detail.

1. Leveraging Zero-Party Data

Zero-party data is information that customers willingly and explicitly provide through quizzes, surveys, social media polls, campaigns and other methods. The potential here is immense as it allows retailers & brands to deliver personalized experiences and build stronger customer relationships while respecting consumer privacy

It's also a relatively straightforward way for brands and retailers to start building trust and demonstrating respect for consumer privacy. Over 90% of marketers in the Asia-Pacific region are actively collecting zero-party data, recognizing its value in creating more relevant and respectful interactions.

For example: Beauty retailer Sephora uses interactive quizzes and preference centers to gather customer preferences for personalized product recommendations and enhanced engagement. Similarly, Southeast Asian retailers like Lazada and Tokopedia encourage users to specify their interests and preferences for customized product suggestions and promotional offers, improving user satisfaction and loyalty. This not only provides valuable data but also creates a more interactive and enjoyable customer experience.

2. Secure Data-Sharing Agreements

Traditionally, secure data sharing was complex and costly. However, advancements in technology, particularly cloud-based data platforms and APIs, have streamlined this process. Modern data-sharing platforms allow brands and retailers to establish secure, controlled connections for data exchange, enabling them to share specific datasets while maintaining data governance and regulatory compliance.

However, this requires detailed and effective data-sharing agreements with clear guidelines on data usage, access controls, security protocols and termination clauses.

Brands and retailers are increasingly collaborating through the sharing of purchase data. Analyzing this shared data allows brands to significantly improve demand forecasting, optimize inventory management, and minimize stockouts.

For example, consider a scenario where a grocery retailer and a food brand want to collaborate on a targeted marketing campaign. To do this effectively, they need a secure data-sharing agreement that specifies- what data will be shared, how it will be used, who will have access to the data and how it will be protected. Finally, it needs to include liability & compliance in case of any potential breaches.

3. Customer-Centric Data Platforms

As consumers become increasingly aware of their data rights, the concept of data wallets or personal data stores (PDS) is gaining momentum. These digital tools empower consumers to securely store, manage, and control their personal information, such as purchase histories, preferences, contact details, and browsing habits.

These PDS form the foundation of customer-centric data platforms. These platforms shift power dynamics by enabling consumers to control who accesses their data, how it's used, and under what circumstances.

Retailers and brands can then leverage consumer-approved data to offer personalized recommendations, discounts, and rewards that resonate with individual preferences and make shoppers feel understood and valued

However, the customer-centric data platform space is still in its early stages, and there is no single dominant platform. Global non-profit initiatives like MyData are working to standardize these platforms, advocating user empowerment through personal data stores, interoperability, and ethical data usage practices.

4. Transparency and Consent -explicit opt-ins

Ultimately, the effectiveness of consumer data usage relies on transparency and trust. Clear and concise privacy policies are essential, ensuring customers fully understand how their information is collected and used.

To cultivate trust among users, brands and retailers must adopt explicit opt-in data collection practices, actively seeking consent rather than assuming it. Giving customers complete visibility and control over their data is the only way to strengthen trust and encourage greater engagement.

Where the future lies

Looking ahead, the future of retail is increasingly customer-centric, with a shift towards shoppers owning, controlling, and actively managing their personal data. While still in its early stages, the emergence of new data marketplaces and platforms promises to reshape traditional dynamics, placing customers firmly at the heart of data exchange.

However, to fully realize the potential of this collaborative data ecosystem, a fundamental transformation is needed. Brands and retailers must embrace transparency and prioritise ethical practices. The central question they must address is this: How can we collectively build an ecosystem rooted in trust, transparency, and shared value?

While there is no easy solution, the key to resolving the Retail Data Wars lies in empowering consumers, starting with an unwavering commitment to ethical, consent-driven data practices that genuinely benefit all parties involved. Only then will it lead to a more transparent and consumer-centric retail experience.

I’m Sameer Dhingra, and this is my personal blog where I write about the shifts shaping technology, retail, and digital innovation across Asia.

By day, I lead Retail & Consumer industry at Google Cloud for Asia Pacific & Japan. But this is my space to step back — just as someone trying to make sense of what’s next. It’s a place to spot signals from a technology lens, share frameworks and document what I’m seeing in the field

If you work in tech, retail, SaaS, consumer industries, or just think about how digital creates value — you’ll probably find something useful here.

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Ever feel like you're throwing money away on software you barely use? If you're a retailer, chances are you've experienced the frustration of subscription fatigue. Let's face it, your business isn't static. You have seasonal peaks, unpredictable demand, and a constant need to adapt. So, why should your software costs be fixed?

Think about it: Your typical mid-sized retail operation might juggle 20-50 different SaaS applications. Larger enterprises? Easily over 200! From e-commerce platforms and POS systems to CRM and AI-powered analytics, the list goes on. Research suggests that the average annual recurring revenue (ARR) for such a retailer on SaaS subscriptions can easily reach $50,000 - $200,000 or more, depending on the specific solutions and vendors involved.

But are you really getting your money's worth? The truth is, many retailers are trapped in rigid, high-cost subscription plans, paying for features they rarely touch. Studies indicate that many retailers are only using a fraction of the features they're paying for in their SaaS subscriptions. Some estimates suggest that utilization rates for certain SaaS applications can be as low as 30-40%, meaning businesses are essentially wasting a significant portion of their software investment. That's money that could be reinvested in your business, your team, or your customers.

Moreover, retailers often use a patchwork of SaaS solutions—POS systems, inventory management platforms, CRM tools, and even AI-powered personalization engines. Traditional subscription models not only make it difficult and expensive to integrate these disparate systems, but complex subscription tiers and hidden costs make it hard for retailers to understand the true cost of their software.

The speed of technological change adds to the problem, as retailers struggle to keep up with the latest software updates and integrations. All of this has led to an acute subscription fatigue. It is a lose-lose situation, where retailers are burdened with unnecessary costs while struggling with operational inefficiencies and the growing complexity of managing an overwhelming number of SaaS subscriptions

In the Asia Pacific region, with its pace of digital adoption and growth, these challenges are particularly pronounced. Let's dive into what's happening with SaaS pricing models and explore the smarter, more flexible ways you can pay for your retail tech.

The Shift Toward Fair and Scalable SaaS Pricing

The shift towards newer pricing models is palpable. Between 2022 and 2024, enterprise SaaS witnessed alarming churn rates, with retailers actively pursuing alternatives offering genuine flexibility. As SaaS costs eat into profit margins, retailers are increasingly exploring Usage based pricing- paying only for the features they use, providing better cost control and scalability, particularly for businesses with fluctuating demand. This includes Pay-As-You-Go (PAYG) models, where retailers pay directly for the resources they consume, as well as credit-based pricing, a prepaid form of usage-based pricing where retailers purchase credits that are then used for services like AI-powered features or API calls.

However, Tiered pricing structure still remains one of the most common flat rate models offering a features based pricing structure- lower priced tiers for fewer features going up to a comprehensive access to the platform’s full capabilities at premium tiers. Another option is Credit based pricing which allows retailers to pre-purchase consumption credits giving them better visibility and predictability for their SaaS spends.

The hybrid pricing model represents perhaps the most innovative approach, with SaaS players combining elements of subscription, credit, and usage-based pricing. This multifaceted strategy offers retail brands unprecedented flexibility to adapt their technology investments to their unique business cycles and growth trajectories.

All this flexibility however, comes with another dilemma. How does one choose the right pricing strategy? What works best and when? Now that we've explored the various pricing models, let's delve into how to choose the right one for your business.

Finding the Right Fit for Your Retail Business- navigating the pricing maze

Retail businesses are evolving at warp speed. If retailers are expected to adapt and change continuously, then why get stuck in rigid subscription cycles? Answering the "what works when" question requires a granular look at your business needs. Before committing to any pricing model, retailers need a thorough assessment of their unique usage patterns, future scalability requirements, and existing budget constraints.

This means considering your sales volume and seasonality, the features you genuinely require, your growth trajectory, budget flexibility, and technology integration strategy. Are your sales consistent or fluctuating? Do you need all the features offered, or just the essentials? Are you rapidly scaling, or aiming for steady growth? Can your budget handle variable costs, or do you need predictability? And finally, how critical is seamless integration with your existing systems?

Once you have clarity on the above, let's look at what might work best for you.

For early stage retailers or businesses facing highly unpredictable sales volumes or seasonal spikes, usage-based pricing is definitively the answer. Take, for instance, an emerging online grocery venture still building its customer base amid unpredictable demand patterns. In such a case, paying precisely for each order processed, delivery route optimised, and API call to external suppliers can really help in managing your cashflows during slower periods while scaling technology costs during explosive growth phases.

In fact, a tier-based pricing structure is also suitable for young retail brands growing at their own pace. In the initial days, opting for a basic tier pricing could suffice for their needs. As they grow and add more customers, they can upgrade to a higher tiers to unlock powerful features. Although not optimal, this has now become a default option in most SaaS platforms.

Despite the surging movement towards flexible pricing options, it's crucial to recognise that subscription models continue to dominate the retail SaaS landscape, particularly for sophisticated enterprise-level solutions and comprehensive operational platforms.

Consider a retail giant managing both expansive online commerce and numerous physical locations—such an operation demands a robust SaaS-based inventory management system capable of tracking inventory across all channels, seamlessly synchronising online and offline transactions, and driving intelligent restocking decisions. With relatively consistent year-round demand punctuated by predictable seasonal surges, these established retailers prioritise stable, predictable cost structures over the ability to micromanage minor fluctuations in expenses.

Lastly, when it comes to retailers with complex business models that entail serving both high-volume recurring customers and smaller, irregular buyers, a hybrid model for their SaaS needs is the optimal solution.

A hybrid billing option seamlessly integrating subscription and usage-based pricing allows these businesses to perfectly balance predictability for core recurring operations while maintaining crucial flexibility for high-demand periods. So, maintain operational stability and pay for premium features only when genuinely necessary. As a result, turning their SaaS investments into cost-efficient, infinitely scalable solutions, perfectly suited to accommodate fluctuating wholesale demand patterns.

So, is Hybrid the way to go and if yes, then what stops every SaaS retailer from offering this as a default option?

While the hybrid model appears to offer the best of both worlds, it's not a one-size-fits-all solution, nor is it always simple to implement. A few things to understand here

Firstly, hybrid models require significant complexity in billing and usage tracking. SaaS vendors must develop sophisticated systems to accurately measure and bill for both subscription-based and usage-based components. This complexity can increase development costs and potentially lead to billing errors or disputes. Secondly, offering a hybrid model requires a deep understanding of the customer's usage patterns, and without the necessary data and analytical capabilities to accurately predict and track usage, implementation can lead to revenue unpredictability or leakage, or customer dissatisfaction.

Therefore, implementing Hybrid models requires careful consideration, a solid technology infrastructure, and a deep understanding of your customers.

Ultimately, the right pricing model depends on the specific needs of both the retailer and the SaaS vendor, and what is optimal for one may not be for another.

The Beginning of Breaking Free from One-Size-Fits-All

The era of rigid, one-size-fits-all SaaS subscriptions is fading. Retailers are demanding flexibility, transparency, and pricing models that align with their unique business needs. But how do you ensure you're making the right choice? It starts with asking the right questions across the following lines.

• Pricing Transparency:

  • Can you provide a detailed breakdown of all costs, including implementation, training, and support?

  • Are there any hidden fees or overage charges? Can you provide real life examples of how other retail businesses similar to mine have been charged using this model?

• Flexibility and Scalability:

  • Can I easily scale my usage up or down based on my needs?

  • What are the contract terms and cancellation policies? What are the options for changing my pricing plan as my business evolves?

• Usage Tracking and Reporting:

  • How is usage tracked and measured?

  • Can I access detailed usage reports? Can I set up alerts for when I am approaching usage limits?

• Integration and Customization:

  • Does your platform integrate with my existing systems?

  • Can I customize the features to fit my specific needs? and what are the costs associated with customization?

  • Do you offer open APIs that allow for third party integrations?

• Support and Service Levels:

  • What levels of customer support are offered?

  • Do you offer service level agreements (SLAs) for uptime and performance?

It is not a choice, but critical for retailers to make an informed decisions that align with their business goals.

What’s Next

The shift towards flexible SaaS pricing models is not just a trend; it's a fundamental change in how retailers consume technology. While subscription-led pricing has long been the standard, it no longer suits the diverse and dynamic needs of retailers. By embracing usage-based, tiered, credit-based, or hybrid models, retailers can break free from the constraints of rigid subscriptions and unlock new levels of agility and efficiency. However, the key is to understand your business needs, evaluate your options carefully, and partner with SaaS vendors who prioritize transparency and flexibility.

At the end of the day, retailers want pricing that makes sense for their actual needs. They want to pay for real value, not potential value. The retail tech providers who will dominate tomorrow's market will be those who understand that alignment with business outcomes isn't just a nice-to-have feature — it's becoming the price of admission to the retail technology ecosystem.

The lines between retail and technology are blurring faster than ever. Asian retailers, no longer content with the traditional storefront, are strategically pivoting towards becoming SaaS powerhouses. This isn't a whimsical shift; it's a calculated move to monetize the substantial investments they've poured into building sophisticated technology stacks and supply chain infrastructures. Why limit these assets to internal operations when they can be leveraged to generate new, recurring revenue streams?

This strategic transformation, where retailers adopt B2B SaaS models to offer services like e-commerce enablement, supply chain technology, and digital marketing solutions to smaller brands and fellow retailers, is particularly pronounced across Asia. A perfect storm of converging factors is driving this evolution: the explosive growth of e-commerce markets, the rapid digitization of SMEs, the widespread adoption of cloud technologies, and the rise of data-driven retail operations. This potent combination has created a fertile breeding ground for retail SaaS to flourish. With digital adoption on the rise, Asian retailers are eager to emulate the platform dominance of giants like Amazon, Walmart by offering cost-effective, scalable software solutions to a market hungry for innovation.

This strategic embrace of ‘platform thinking’ is fundamentally reshaping the landscape of retail SaaS innovation across the region. In this blog post, let’s explore how forward-thinking Asian retailers are capitalising on this trend and evolving into SaaS players reshaping the regional retail landscape.

From Retailers To SaaS Vendors

The transformation of retail behemoths into SaaS providers is a global spectacle, with trailblazers like Amazon, through AWS and FBA, and Walmart, with GoLocal and Luminate, demonstrating the immense potential of monetizing internal technology investments.

This model validated a disruptive business concept: that Retail expertise, when properly systematized and packaged, can become valuable technology products in their own right—creating new recurring revenue streams while empowering other businesses with enterprise-grade capabilities.

The allure is undeniable. Traditional retail, often navigating thin and volatile margins, finds a golden opportunity in SaaS solutions. By offering subscription-based services, retailers secure recurring revenue, which is more stable and scalable. SaaS promises higher margins and diversification away from the unpredictable nature of pure product sales, all while leveraging existing infrastructure and expertise to tap into a rapidly expanding market.

In Asia, tech-forward companies like Alibaba, JD.com, Reliance, Flipkart, Coupang, Woolworths and a growing number of others have recognized and capitalized on this growing retail SaaS game. While not every retailer can establish cloud infrastructure on Amazon's scale (barring Chinese giants like Alibaba or JD.com), they're offering a diverse array of specialized services, ranging from dynamic pricing solutions and POS systems to powerful adtech platforms and sophisticated analytics tools, each tailored to the unique needs of the Asian market

The Retail-to-SaaS Shift: Five Functional Frontiers

As retailers make their moves, we can cluster this shift in 5 key functional domains, each representing a critical area where retailers are leveraging their expertise and technology to empower others

1. Data & AI Powered Solutions

Given that data is the ultimate currency, this is usually the first road retailers are taking towards building their SaaS offerings. They are providing smaller merchants with access to sophisticated data and AI/ML solutions, once the exclusive domain of large corporations. These SaaS solutions integrate data from both online and offline channels, harnessing AI and ML to analyse customer behavior, optimize inventory, and tailor marketing including pricing & promotion strategies in real time.

A great example would be Woolworths Group—a leading retailer in Australia and New Zealand—which has been at the forefront of this transformation. In 2021, Woolworths acquired a controlling stake in Quantium and established Woolies iQ (wiq) to develop joint advanced retail analytics capabilities to transform customer and supplier experiences. While initially deployed across Woolworths' extensive ecosystem, they have now commercialised these capabilities, offering it to retailers worldwide.

2. Unified Ecommerce Solutions: Integrated digital ecosystems.

Unified e-commerce solutions are another fertile ground for innovation. These comprehensive offerings encompass omnichannel retail platforms, modern Point of Sale (PoS) systems, and robust e-commerce enablement tools.

India's Reliance is a prime example of a retailer leveraging its technological investments to build an expansive digital ecosystem. A key part of this vision involves digitizing traditional Kirana stores through JioMart, its ecommerce platform. At the same time, Reliance also offers SaaS-based solutions through its Jio Commerce Platform, which provide comprehensive order management, catalog management, marketing and promotional, and data analytics tools.

Another Indian online retailer that has evolved as a SaaS player is Flipkart. Its Flipkart Commerce Cloud offers a range of solutions ( digital commerce, retail media platform, pricing engine etc) helping store owners connect their online and offline operations. These cloud-based services are flexible, allowing retailers to choose what works best for them.

3. Supply Chain Logistics & Fulfillment SaaS: Backbone of Retail

A robust and efficient supply chain is fast becoming the linchpin of success in Asian retail. As a result, retailers with strong logistics capabilities are monetising it by offering supply chain and fulfillment SaaS solutions covering warehousing, delivery, and last-mile logistics.

For instance, South Korea’s Coupang provides comprehensive logistics services through its subsidiary, Coupang Logistics Services (CLS). Their offerings are designed to support both large brands and SMEs, facilitating efficient order fulfillment and last-mile delivery.

Yet another example of a retailer-cum-logistics and fulfillment SaaS is India’s food delivery company Swiggy. Through its subsidiary, Scootsy Logistics, Swiggy is now extending its expertise to other businesses offering warehouse management, in-warehouse processing, and order fulfillment as SaaS solutions.

4. Digital Payments & Fintech SaaS: Powering financial inclusion

Retailers are increasingly offering Fintech SaaS solutions, driving financial inclusion by enabling smaller businesses with accessible digital payment systems and crucial financial services. By providing access to digital payment gateways, microloans, and investment opportunities, retailers are fostering frictionless customer experiences that build loyalty and boost sales.

In India, PhonePe, initially launched within Flipkart and subsequently spun off as an independent entity, has become a dominant player. PhonePe offers a comprehensive suite of merchant services, including payment gateways, POS solutions, QR code payments, and business loans, enabling even the smallest retailers to participate fully in the digital economy. While now independent, PhonePe's origins within Flipkart highlight how major retail platforms can leverage Fintech to expand their ecosystem and empower their merchant partners

5. Martech Capabilities: Democratizing Advanced Marketing

These SaaS offerings offer smaller businesses enterprise-level capabilities across MarTec, including CRM, digital loyalty programs, social commerce tools, and advanced adtech platforms.

Japanese e-commerce giant Rakuten stands as a prime example of this trend. Evolving from its roots as an online marketplace, Rakuten has developed a comprehensive suite of digital services, notably the Rakuten Advertising Platform. which provides a range of marketing and advertising solutions. Similarly, as mentioned earlier, FlipKart offers Retail Media Platform capabilities as a SaaS offering as well.

Will this bold vision work?

The pivotal question remains: Will this ambitious strategy succeed for Asian retailers? While the opportunities are undeniably compelling, there are also significant challenges and the answer, as always, is nuanced and depends heavily on execution.

Retailers, traditionally rooted in product-centric and operational paradigms, often lack the inherent "SaaS DNA" required for success. They face fierce competition in a saturated SaaS market and must navigate the complexities of balancing transactional retail with subscription-based models. Building scalable SaaS platforms often demands substantial investment, and establishing credibility as a trusted technology provider, distinct from their retail brand, is not easy.

However, retailers possess a unique set of advantages. Biggest of them all is their domain understanding of retail operations which allows them a powerful value proposition. Having experienced the pain points firsthand, retailer-SaaS vendors can build products that address real-world challenges with practical, relevant features. In addition, retailers are data goldmines, which gives them a distinct competitive advantage given their insights into consumer behaviour, preferences and trends that extend far beyond basic transaction data.

However, for this transition to SaaS platforms to be successful, retailers must take several strategic actions to position themselves for success in the SaaS market.

Developing a clear value proposition that leverages their unique perspective is first and foremost. By identifying specific niches where their retail background provides advantages, retailers can create compelling differentiation in the market. This targeted approach allows them to compete effectively against broader platform providers.

Of course, investing in dedicated SaaS expertise and building secure & scalable technology foundations is essential. This means hiring talent with proven experience or forming strategic partnerships with established technology companies.

The relationship-based nature of SaaS differs from transactional retail, requiring a shift in mindset. But beyond operational and mindset changes, retailers planning a SaaS business must effectively communicate their dual identity as they build trust as a tech provider. This careful brand management is critical to allow them to leverage their retail credibility while establishing a reputation in the SaaS marketplace.

Asian retailers venturing into SaaS is both a fascinating and potentially disruptive trend. This is more than just a shift in business models; it's creating a more innovative and interconnected industry where specialised knowledge translates into technological solutions benefiting the entire sector.

What's fueling the rapid transformation of Asia's retail landscape? Hint: It's not just online shopping. While e-commerce continues to grow, the real revolution is happening behind the scenes, powered by artificial intelligence, advanced logistics, and a wave of innovative RetailTech solutions.

In 2024 alone, over $127 billion flowed into Asia's retail sector, with a clear focus on technologies that enhance the customer experience, optimize operations, and drive growth. This blog post will analyze the flow of RetailTech investments in Asia, examining how funding in 2024 shaped the landscape and revealed the evolving priorities and growth areas in this dynamic market.

In this post, I look at how funding flowed to technology-driven retailers and innovative RetailTech vendors in addition to also reviewing some strategic mergers & acquisitions in this domain in 2024. By connecting these dots, we can see the evolving priorities and growth areas in this dynamic market, giving us valuable insights on how retail, technology & innovation is evolving in Asia. We'll also look ahead to where the where the focus is likely to be in 2025 and beyond.

Following the Money: RetailTech Investments in 2024

2024 was a year of significant investment in Asia's RetailTech sector, with funding flowing into a diverse range of solutions designed to enhance the customer experience, optimize operations, and drive growth. While AI-powered solutions continued to dominate, we also saw substantial investment in quick commerce, B2B retail technologies, and omnichannel solutions. Let's take a closer look at the key investment trends that shaped the Asian RetailTech landscape in 2024.

AI & Personalization: Asian AI startups are experiencing exponential growth as they develop innovative solutions to address the evolving needs of retailers and brands. These companies are at the forefront of AI innovation in areas like AI agents, conversational commerce, vision AI, and marketing automation, transforming how businesses interact with customers, manage operations, and make decisions. For example, Yellow.ai, an Indian company providing a conversational AI platform for building AI agents, has seen significant adoption across various industries. LimeChat, also based in India, is gaining traction with its conversational commerce platform focused on messaging apps. In the realm of vision AI, Visenze, a Singaporean company, and Vue.ai, an Indian company, are helping retailers and brands leverage AI for product discovery, personalization, and customer engagement. These startups, along with companies like Pencil (acquired by Brandtech) and Invideo in the marketing and content creation space, are attracting significant attention from investors. The rapid rise of these Asian AI startups and their speed to market is truly astounding as they drive innovation in their respective solution areas.

Omnichannel Solutions: Investments in omnichannel solutions remained strong in 2024, as retailers continued to seek ways to bridge the gap between online and offline channels and provide seamless customer experiences. For instance, the Indian SaaS platform Single Interface, which helps retailers boost customer engagement and e-commerce offerings, raised $30 million. Ace Turtle, an Indian company offering omnichannel technology solutions for retailers, raised $34 million in Series B funding. Growsari, a B2B e-commerce company serving over 1.3 million mom-and-pop stores in the Philippines, raised $5 million to expand its operations, demonstrating the growing importance of omnichannel strategies for small businesses.

Quick Commerce & Logistics: The demand for fast and efficient delivery continued to surge in 2024, driven by factors such as rising consumer expectations, rapid urbanization, and the growth of a digital-first middle class. Quick commerce startups like Zepto ($1.35 billion in funding) and Blinkit ($34.5 million investment from Zomato) are at the forefront of this trend, promising delivery within minutes and reshaping the grocery shopping experience. This intense competition is fueling innovation in last-mile delivery, with companies leveraging AI-powered logistics solutions to optimize delivery routes, manage fleets, and improve efficiency. Investments in logistics platforms like Shadowfax Technologies ($100 million), Ninja Van ($50 million), Delhivery (IPO), Locus, and Porter ($100 million+) underscore the importance of technology in meeting the growing demand for speed and convenience.

Social commerce continued its rapid rise in Asia in 2024, fueled by the region's high social media penetration, the popularity of influencer marketing, and the increasing comfort level of consumers with making purchases through social media platforms. This trend is driving innovation in how brands and individuals connect with customers and sell products online. A good example would be platforms like Meesho (which raised $250-270 million in a secondary round) which are enabling resellers to leverage social media for sales. Established e-commerce players like Shopee, Lazada, Flipkart etc are also incorporating social commerce features, such as live streaming, shoppable video content and in-app social sharing, into their platforms. In China, Xiaohongshu, a popular social commerce platform, received an undisclosed amount from DST Global as it prepares for an anticipated initial public offering, further demonstrating the strong growth and potential of this sector.

Just a disclaimer- the above mentioned 4 areas are by no means the only ones. In addition to these key areas, other domains like sustainability, AR/VR and Retail Media Networks (RMNs) also attracted significant attention from investors in 2024. In the RMN space, almost every major retailer with significant shopper traffic sought to build its own adtech platform, leading to a surge in third-party RMN solutions. Startups like OnlineSales.ai have been actively gaining ground as they help retailers with the tools and technology to create and manage their own retail media networks

M&A Activity: Strategic Moves and Market Consolidation

While venture capital and private equity investments played a significant role in shaping the Asian RetailTech landscape in 2024, strategic mergers and acquisitions (M&A) were equally important in driving industry consolidation and expansion. These M&A deals demonstrate how companies are going beyond simply investing in new technologies and are actively seeking to bring innovative capabilities in-house.

Several factors fueled this M&A activity. Firstly, it was the rush to acquire businesses with proven expertise in areas like AI and data analytics. For instance, India's leading e-commerce data platform, Intelligence Node, was acquired by New York-based Interpublic Group, highlighting the value of AI-driven data analysis for online brands and retailers.

Secondly, the explosion of e-commerce in APAC led to increased competition and a need for companies to expand their reach and capabilities. This is evident in Alibaba's merger of its South Korean operation with E-Mart, a move aimed at strengthening its presence in the South Korean market and competing with local players like Coupang and Naver Corp. This deal also exemplifies the trend of integrating online and offline retail, as Alibaba sought to combine its online expertise with E-Mart's offline network to create a more comprehensive retail offering.

Thirdly, the pandemic accelerated digital adoption, pushing retailers to embrace omnichannel strategies and hybrid models. This led to M&A deals focused on acquiring technologies and capabilities that support seamless online and offline integration. For example, Vietnamese e-commerce enabler OnPoint acquired CREA, a Thailand-based company, to expand its reach and enhance its omnichannel marketing solutions for brands in Southeast Asia.

Finally, the slowdown in China's global expansion, partly due to regulatory challenges, created opportunities for companies in other Asian markets, such as India and Southeast Asia, to attract more investment and expand their operations. This also led to some Chinese companies, like Alibaba, divesting from non-core businesses and focusing on their core strengths in their domestic market. Alibaba's sale of its stakes in Sun Art Retail Group and Intime Retail Group reflects this trend, as the company sought to streamline its operations and focus on its core e-commerce business.

Overall, the Asian M&A activity in 2024 has been a good indicator about the strategic moves companies are making to adapt to the changing market dynamics, acquire key technologies, and expand their reach.

So, what can we expect in 2025 with respect to RetailTech Investments?

In 2025, investments in retail technology across Asia will continue to be driven by the need to enhance customer experience, optimize operations leveraging Data & AI. Here are some key areas where we can expect to see significant investment activity:

• AI-driven Automation: Retailers will increasingly invest in AI-powered solutions to automate various aspects of their operations, from customer service and inventory management to marketing and logistics. This will help them improve efficiency, reduce costs, and enhance the customer experience.

• Data Monetization: First-party data will become even more valuable, and retailers will focus on monetizing this data through retail media networks (RMNs) and other data-driven strategies.

• Unified Commerce Platforms: Investments in unified commerce platforms will continue, as retailers seek to provide seamless customer experiences across online and offline channels. This will include investments in next-generation ERP systems and other technologies that enable seamless integration.

• Hyper-Personalized Shopper Experience: Retailers will focus on creating hyper-personalized shopping experiences to enhance customer engagement and foster loyalty. This will involve leveraging AI, data analytics, and social commerce strategies to tailor the shopping journey to individual preferences and create a more interactive and engaging experience.

• Supply Chain Resilience: Given the ongoing volatility in global supply chains, retailers will invest in technologies that improve supply chain visibility, efficiency, and resilience. This will include AI-driven inventory management, logistics automation, and ESG tracking technologies.

Suffice to say that 2024 was a year of significant transformation. Investment in Asia's RetailTech landscape, with AI, quick commerce/ logistics and omnichannel solutions took center stage. As we look ahead to 2025, it's clear that these trends will continue to shape the industry, driving innovation and creating new opportunities for retailers, technology providers, and investors alike.

The rapid adoption of AI-powered solutions, the increasing focus on data monetization, and the ongoing evolution of social commerce and unified commerce platforms will redefine the retail experience for consumers and businesses. However, challenges remain, such as ensuring data privacy, navigating complex regulations, and addressing sustainability concerns. Having said that, retailers who are able to leverage the technology innovations integrated in their respective operations will continue to attract fresh investments in 2025. Staying ahead of the curve will require agility, innovation, and a deep understanding of the forces shaping the future of retail.

What are your thoughts on these trends and their potential impact? Share your insights and join the conversation!

Asia Pacific commands over 60% of the global e-commerce market. By 2026, the region’s retail e-commerce sales are projected to breach the $4 trillion mark, contributing over one-third to total retail sales. But what’s truly fascinating isn’t just the scale of the market—it’s the innovative approaches driving its growth.

Did you know that a single livestream in China can generate over a billion dollars in sales? Or that platforms like Xiaohongshu allow users to co-create products? These examples highlight the power of the 'C3' revolution – the convergence of content, community, and commerce, which is transforming the Asian retail landscape. The C3 model represents a new era of retail where brands create engaging content, foster vibrant communities, and seamlessly integrate commerce into the experience. It's about building an ecosystem where customers, especially those in Asia's mobile-first and community-driven culture, don't just buy products; they connect, engage, and become part of a brand's story.

In this blog post, let's explore further how the C3 model is transforming Asian retail, why it works so well in this region, and what the future holds for this exciting new approach to commerce.

Understanding the Convergence

The Content-Community-Commerce (C3) model represents a fundamental shift in how brands approach retail, particularly in the dynamic Asian market. It's about creating a holistic ecosystem where these three elements work together to drive engagement and sales.

At the heart of C3 is the understanding that content is the new storefront, and unlike traditional advertising, brands are using content to build communities and foster authentic connections with consumers

Platforms like Xiaohongshu and TikTok thrive on user-generated content, where product reviews, recommendations, and lifestyle posts become powerful drivers of commerce. In Indonesia, for example, beauty brand P Louise sold $2 million worth of products in just 12 hours during a TikTok live event, highlighting the growing popularity of live commerce and influencer marketing in Southeast Asia.

Moreover, Asian consumers are increasingly relying on communities—both online and offline—to guide their shopping choices. Platforms like Shopee and Lazada have integrated chat features and community forums, allowing shoppers to discuss products and share feedback in real-time. This fosters a sense of trust and belonging, turning shopping into a shared social experience. Consequently, brands are actively cultivating communities around their products and leveraging social media & online forums to connect with their consumers.

This interconnectedness of content and community creates a powerful flywheel effect that drives commerce. Engaging content attracts new audiences and fosters a sense of community. Strong communities, in turn, generate more content and drive purchasing decisions. And the data generated from commerce provides valuable insights that can be used to further refine content and community-building strategies.

Commerce is the ultimate goal here for retailers, but it is not just that. In a price-sensitive market like Asia, loyalty is paramount. C3 lays the foundations for deeper connections with customers beyond just product offerings.

Valuable content and strong communities cultivate emotional connections and brand advocacy. It turns shopping experiences into an informative and enjoyable experience, and in the process becomes a powerful tool for customer acquisition and retention.

Ultimately, the C3 Model makes one thing crystal clear- Commerce is about more than just transactions. It's about building relationships, fostering trust, and creating valuable experiences for consumers.

Why Does C3 Work Well In Asia?

The C3 model's power lies in how content, community, and commerce interlock and amplify each other. Engaging content attracts new audiences, while strong communities and relevant commerce keep them coming back.

This strategy has seen remarkable success in Asia due to a unique confluence of cultural, technological, and economic factors.

First of all, culturally, Asian consumers put more emphasis on trust built through relationships and social connections. Platforms like Xiaohongshu, for example, tap into the importance of word-of-mouth marketing and community endorsements by allowing users to share product reviews and recommendations, which heavily influences purchasing decisions.

In addition, the region's diversity feeds into the need for creating highly localised content with niche communities that resonate with specific cultural nuances. Moreover, the mobile-first behavior along with widespread e-commerce adoption and digital payments provide the ideal technical foundation for C3 implementation.

The success of this integrated approach in Asian retail isn't just a passing trend; it's becoming essential for businesses to thrive. Consequently, this is now becoming an inherent part of the go-to-market strategy. This integrated approach is evident in the strategies of numerous successful Asian retailers.

For instance, let's take Shopee as an example. The Singapore-based ecommerce company has a synergistic ecosystem where content, community, and commerce seamlessly intertwine. With social features like Shopee Live for live streaming, Shopee Feed for sharing user-generated content, and Shopee Games for in-app gaming, the retailer allows users to interact with each other beyond just transactions, effectively building a platform where shopping feels like a social experience. Additionally, Shopee leverages local influencers and tailored campaigns to further engage users and foster a sense of community within the platform. Ultimately, all these efforts converge to drive commerce within Shopee's core marketplace, enhanced by features like ShopeePay, making the platform an engaging shopping destination.

Another interesting example is Japan’s Uniqlo.

The fast fashion giant collaborates with influential artists, designers, and celebrities to create limited-edition collections that generate buzz and excitement. Alongside, Uniqlo fosters a community of loyal customers through its UTme! platform, where fans can design their own t-shirts before buying them, and that builds a sense of ownership and creativity. The cherry on top is Uniqlo’s seamless online and offline integration that allows customers to browse and purchase products both in-store and online, with options for home delivery or store pickup.

Similarly, Zalora uses influencer marketing and user-generated content to promote products and build brand awareness. But what stands out the most is the retailer’s community influencer program that encourages its customers to become influencers, endorsing brand products to their friends, family, and followers on social media and earning commission for every successful purchase.

In fact, there is a long list of prominent Asian companies that are devising new strategies to converge content, community, and commerce. Other notable examples include TikTok China, where short videos drive sales, Pinduoduo, which has brought together group buying and social sharing to make shopping viral, and Mercari, the peer-to-peer marketplace that integrates social content, live auctions, and gamification.

What's Next for C3 in Asia?

While the C3 model offers tremendous potential, Asian retailers also face unique challenges in implementing it effectively. The diversity of Asian markets requires retailers to have a deep understanding of each target market's culture, technology, and economy to effectively create content, build communities, and adapt commerce strategies.

However, these challenges are also driving innovation and shaping how retailers are leveraging content & communities to drive commerce in Asia.

The need for authenticity and trust is leading to a greater focus on micro-communities and niche focus, where brands can build genuine connections with consumers who share common interests and values. Furthermore, AI is rapidly being integrated into business operations thereby increasingly playing an important role in personalizing content, community interactions, and shopping experiences, helping brands cater to individual preferences and build stronger relationships.

Moreover, as the lines between online and offline retail blur, a more unified commerce approach is creating opportunities for the seamless integration of content & communities with commerce. Physical stores are transforming into content hubs, community gathering spaces, and experiential showrooms, enhancing the overall customer journey. Immersive experiences, such as virtual showrooms and augmented reality applications, are further enriching the shopping experience and creating new avenues for engagement.

Looking ahead, as this evolves further, data ethics, transparency, and consumer empowerment will become even more paramount. Brands will need to prioritize ethical data collection, transparent data practices, and robust data security measures to build and maintain consumer trust.

Having said that, I think the C3 model offers exciting new possibilities for brands to connect with consumers and drive growth. By understanding the challenges and embracing the emerging trends, retailers can leverage the power of content, community, and commerce to create truly engaging and successful retail experiences

The Asian retail scene is buzzing with innovation. It's like a lively marketplace, but instead of haggling over spices and silks, retailers are vying for shopper’s attention and loyalty in the digital realm. Recent quarterly and annual reports from industry giants offer a fascinating glimpse into this transformation. Beyond just numbers, these reports provide a sneak peek into the boardroom discussions and the strategic bets these retailers are making- a front-seat view into their world - strategies, focus areas, challenges, and triumphs. Last month, we saw a few of these coming out (Woolworths, Wesfarmers, Fast Retailing, Central Retail, etc.).

Looking at this from a technology lens and decoding the digital DNA of these retailers, one thing is clear: Asian retail is in the midst of a major digital transformation. Everything points to retailers embracing technology to navigate a new era of shopping behaviour and competitive pressures. It is also interesting to see the different digital strategies & initiatives based on the focus areas, maturity, and markets.

So, what insights and lessons can we draw from Q2 '2024 results? Let's peel back the layers of these quarterly reports and uncover the key tech trends, challenges, and opportunities reshaping the Asian retail landscape.

Beyond the Balance Sheet: Tech Trends from Asian Retailer’s Q2 2024 Results

The digital movement sweeping across the Asian retail industry is far from uniform. Retailers are charting their course and adopting strategies to their unique strengths, challenges, and target markets. While the overarching goals of enhancing shopper experience and improving operational efficiency remain consistent, the paths to achieve them are diverse and multifaceted. Here are the 5 key trends we can see today.

1. Omnichannel: Rush to deliver an integrated shopping experience.

The boundaries between online and offline shopping are blurred. Most retailers have published strong growth numbers for their online sales, highlighting the importance of their omnichannel strategies in their financial reports. Central Retail reported that 19% of its total gross sales in Q1 '24 came from omnichannel strategy. Woolworths Group saw their eCommerce sales grow by approximately 35% on a 4-year CAGR, reflecting a significant shift towards online shopping and convenient delivery options. Their WooliesX platform, which includes e-commerce, digital media, and rewards programs, plays a crucial role in driving this digital growth. Even Fast Retailing (UNIQLO), with its strong physical presence, reported that online sales represented 15% of their total global sales in FY2023. This online penetration varied by region, reaching about 20% in the Greater China region and South Korea.

There is a rush to implement capabilities to ensure an integrated shopping experience. Fast Retailing plans to further integrate its physical stores and e-commerce operations to enhance convenience and information sharing through services like UNIQLO LIVE STATION. Matahari, on the other hand, is actively integrating its inventory systems to enable fulfilment from any store, aiming to have 80% of its Consignment Vendor brands available for fulfilment from any location. Such moves can dramatically expand traditional retailer’s reach, offering greater convenience to customers.

All indicators highlight the growing importance of this strategy to promote integrated commerce. While the specific percentages and growth rates vary across companies and regions, the overall trend indicates a significant shift towards digital integration and unified shopping experiences.

2. Data, AI and Automation: The Fuel for Personalization and Efficiency

As data is the centre of any transformation, retailers are building capabilities in analytics and AI to unlock its potential. For example, Wesfarmers is investing heavily in building a ‘Data and Digital Ecosystem’ to support its diverse retail businesses. This includes their flagship initiative- OneDigital, which brings together Wesfarmers' digitally native businesses, including the OnePass membership program, the shared data asset ( OneData ), and the online marketplace Catch. Both OneData and OnePass are fantastic platforms which are helping Wesfarmers not only have a single view of their customers but also leverage this data to optimise pricing, personalised promotions, customer service and, of course, operational efficiencies.

Also, AI and automation are no longer futuristic concepts; they are rapidly becoming integral to retail operations. For example, Rakuten is leveraging AI to power its semantic search engine for its fashion platform, enhancing search accuracy and providing customers with a more intuitive shopping experience. JD.com's AI-powered digital representative, which attracted over 20 million views during its debut livestream, showcases the innovative ways retailers are using AI to engage customers and create unique shopping experiences.

It's fair to say that AI and automation are not just about cost savings; they're about creating smarter, more responsive, and customer-centric retail experiences.

3. Supply Chain Digitization: Building a Transparent and Efficient Backbone

Retailers are turning to technology to revamp their supply chains in the search for operational efficiencies and to meet consumer expectations for transparency. Fast Retailing, the parent company of UNIQLO, is building systems to trace the origin and flow of materials used in its products. This commitment to transparency resonates with the growing consumer demand for ethically and sustainably sourced products. JD.com has built a Supply Chain Emission Management Platform ( SCEMP) to monitor, report and verify carbon emissions throughout its logistics and transportation process. Woolworths Group has been investing heavily in their supply chain to support its e-commerce growth, including the launch of 11 Customer Fulfillment Centers (CFCs) since 2014. Matahari has built a Centralised Logistics Hub to streamline its warehousing, pick-pack-ship process and e-commerce fulfilment. In addition, ‘Fulfillment from Store’ is a big initiative for Matahari- it expanded to 56 stores across 44 cities by the end of 2023, fulfilling 51% of online orders directly from stores.

Most retailers are now looking to implement data-driven solutions to optimise their supply chains, aiming to reduce waste, improve product availability, and minimise environmental impact. The message is clear: a digitally enabled, transparent, and efficient supply chain is a key pillar of any technology strategy.

4. Delivering Value: The Currency of Customer Loyalty

Retailers deliver value to their customers through a multi-pronged approach that prioritises convenience, attractive promotions, competitive pricing, and rewarding loyalty programs. These initiatives are often integrated into broader strategic initiatives aimed at improving shopping experiences, driving loyalty, and achieving profitable growth

Let's start with ‘Convenience’ first- 3 things are evident - First, offering services like Click & Collect, Chat & Shop, Shop & Drive Thru to integrate online with offline shopping is now on everyone's radar. Second, optimised store layouts and navigation to improve the in-store shopping experience is another key element of convenience. Third, enhanced delivery options like same-day delivery and on-demand delivery propositions are being integrated into the platforms.

At the same time, retailers are strategically intertwining targeted promotions, pricing, rewards, and loyalty to cultivate strong customer relationships and drive sales. A key aspect of this approach is offering competitive pricing and value-driven promotions, such as everyday low prices and targeted discounts, to attract value-conscious consumers ( a good example here is the rewards program offered by Wesfarmers and Woolworths). This is then complemented by robust loyalty programs with tiered structures, gamification, etc., that reward repeat purchases and build long-term customer relationships.

Integrating promotions, pricing, and loyalty programs creates a compelling value proposition that resonates with customers, encourages repeat business, and drives brand loyalty.

5. Sustainability: From Trend to Table Stakes

Sustainability is no longer a niche concern; it's a mainstream expectation. Consumers, particularly younger generations, increasingly prioritise environmentally and socially responsible brands. Woolworths is setting a high bar with its ambitious net-zero emissions target, commitment to renewable energy, and efforts to promote regenerative agriculture and sustainable sourcing.

As mentioned before in the supply chain section, Fast Retailing is enhancing transparency by disclosing its production partners and tracing the origin of its materials, building trust with eco-conscious consumers. JD.com is tracking its emissions, and Wesfarmers is also taking action to promote circular economy principles within its operations and supply chain.

The message is clear: sustainability is not just a buzzword anymore; it's now a CEO agenda.

A Patchwork of Digital Strategies

While the digital movement is sweeping across the Asian retail industry, there's no one-size-fits-all approach. Retailers are adopting diverse strategies based on their size, business model, target market, and competitive landscape. Despite these differences, there are common threads as most are adopting digital to enhance the customer experience through personalisation, integrated shopping experiences, and convenient services. They're also leveraging technology to improve operational efficiencies, streamline the supply chain, and reduce costs.

However, the paths to these goals can diverge, each tailored to a retailer's unique context and goals. Some retailers, like Wesfarmers, have opted for a centralised approach with its OneDigital division, consolidating its data and digital capabilities under one umbrella. In contrast, Woolworths is weaving technology into every aspect of its business to achieve specific goals like enhancing its fresh food offerings. Central Retail is laser-focused on omnichannel excellence in Southeast Asia, while Fast Retailing is championing supply chain transparency on a global scale.

As you can see, approaches and digital strategies differ based on their unique circumstances, business models, target markets, and competitive landscapes.

The Digital Balancing Act: Cautious Optimism, Risk & Rewards.

The digitisation of Asian retail is a story of both promise and careful consideration. From the Q2 results, one can sense the prevailing sentiment of cautious optimism. While retailers express optimism about the potential of technology to drive growth and enhance shopper experiences, they are also acutely aware of the challenges posed by rapid technological change and economic uncertainties. Cybersecurity threats and data privacy concerns are also major potential risks. Woolworths Group, for instance, openly acknowledges the complexities of the evolving digital landscape, particularly regarding cybersecurity and data privacy. The company emphasizes the need for robust security measures and continuous adaptation to address these challenges.

However, amidst these risks lie significant opportunities. The potential to enhance customer experiences through personalization, integrated shopping, and innovative technologies is immense. Data-driven insights, automation, and AI can streamline operations, reduce costs, and improve productivity. Moreover, digital adoption also opens doors for new business models, such as subscription services, reuse, etc., offering avenues for growth and innovation.

The Digital Imperative and the Road Ahead.

The digital window to Asian retail shows us a resilient ecosystem evolving, adapting, and innovating simultaneously. With e-commerce giants and startups constantly raising the bar, this market is more competitive than ever. To win, retailers must stay ahead of the curve, anticipate customer needs, and deliver exceptional experiences across all channels. And technology plays a huge part in all this!

Despite all the challenges, the future of retail is bright. With all the advancements in technology ( especially AI), we can expect even deeper personalization and a more integrated commerce experience. The early adopters who embrace this digital imperative and leverage these technologies will win in this exciting new era.

In the fast-paced world of Asian retail, customer loyalty is the holy grail. But as consumer behaviour evolves at lightning speed, traditional Loyalty Programs are struggling to keep up. Imagine a Loyalty Program that doesn't just reward past purchases but anticipates your next craving—a program that feels less like a transaction and more like a conversation with your favourite brand. This isn't wishful thinking—it's the future of loyalty, powered by AI.

Advancements in AI have been a game-changer set to redefine customer engagement and loyalty across the continent. The power of artificial intelligence (AI) to analyse vast datasets and offer actionable insights is now beginning to reshape traditional loyalty schemes. This AI revolution isn't just hype—it's happening right now. Global AI in the retail market is projected to explode from $7.14 billion in 2023 to a staggering $85.07 billion by 2032. Forward-thinking retailers and early adopters are already reaping the rewards of AI-powered loyalty programs, witnessing increased shopper engagement, retention, and revenue.

This article delves into how AI is enhancing the effectiveness of loyalty programs and redefining shopper engagement in one of the world's most dynamic and diverse markets: Asia. From predictive analytics to hyper-personalised offers, let's take a deeper look at how AI is empowering retailers to build stronger connections with their customers across Asia.

But before we explore the potential of AI, let's first examine the challenges of traditional loyalty programs.

The Challenges of Traditional Loyalty

Traditional loyalty programs have evolved from simple coupon distribution to leveraging digital tools for better customer understanding and targeted discounts. However, despite these advancements, most programs still lack personalization or meaningful engagement, hence failing in today's dynamic retail landscape.

Here are four common challenges often encountered in loyalty programs. The first and biggest one is the lack of personalization. In today's world, customers expect tailored offerings that cater to their individual preferences and behaviours. A generic, one-size-fits-all approach simply won't cut it, leading to disengagement and, ultimately, customer churn.

Second, many retailers overlook the importance of meaningful customer interaction. Merely awarding points isn't enough to foster a genuine connection, and shoppers are less likely to redeem their rewards without regular communication and engagement.

Third is the reactive nature of most reward programs. Traditionally, these programs are designed to reward shoppers after they've made a purchase. This reactive mechanism has a minimal impact on incentivising and motivating customers to make repeat purchases.

Finally, the difficulty of measuring the effectiveness of loyalty programs remains a persistent problem. Retailers often struggle to directly link customer retention and increased repeat purchases to their loyalty initiatives. Without clear ROI measurement and dwindling redemptions, the cost of providing rewards, particularly premium ones, can become unsustainable as loyalty programs scale.

AI to the Rescue: How It's Transforming Loyalty

AI, armed with advanced analytics and data processing capabilities, can empower retailers to overcome these challenges today. Leveraging AI to identify patterns, preferences, and shopping intent, retailers can today design highly personalized, real-time engagements, rewards, and retention campaigns.

There are four key pillars of any loyalty program- Personalisation, Engagement, Rewards and Measurement. Let's look at them with a few examples to see how retailers are beginning to use AI to transform loyalty programs.

1. Personalization: Knowing Your Customers Intimately

Retailers are now trying to move beyond generic offers and discounts. Using AI, they are able to analyse vast datasets to understand individual shopping behaviour, allowing for product recommendations & hyper-personalised promotions that truly resonate. Sephora's Beauty Insider program, for example, leverages AI to provide tailored product recommendations, exclusive rewards, and even personalised beauty consultations, creating a unique experience for each member. Similarly, The Coffee Bean & Tea Leaf employs AI to track customer preferences and suggest new beverages or discounts on favourite items, making each interaction feel special.

Tiered loyalty programs cater to different customer segments based on their real-time spending habits. This ensures rewards match individual customer value and prevents over- or under-rewarding. Central Group's The 1 Program in Thailand exemplifies this approach, offering exclusive benefits and personalised rewards to its top-tier members.

Omnichannel personalization is another key advantage of AI. It ensures customers receive a consistent and personalised experience regardless of whether they interact with your brand in-store, online, or on their mobile devices. Woolworths- Everyday Rewards Program in Australia utilises AI to offer personalised discounts, targeted promotions, and digital coupons to its members, fostering engagement and loyalty across all touchpoints. In India, Tata Neu's super app- rewards program leverages AI to provide personalised recommendations and deals across its various brands, creating a seamless experience for customers within the Tata ecosystem.

2. Boost Engagement and Build Relationships

From being just ‘transactional’ to becoming ‘relational’- that's where the loyalty programs are headed. Regardless of the customer's preferred channel, today, technology allows retailers/ brands to track shopper buying behaviour across multiple formats, enabling them to continue the conversation seamlessly. This kind of proactive engagement is often powered by AI chatbots like Uniqlo App, providing real-time customer support and personalised recommendations, making every interaction feel valued. More on Uniqlo digital engagement strategy here.

Gamification adds a layer of fun and excitement to loyalty programs. GrabRewards in Southeast Asia uses gamified elements to boost engagement, encouraging users to earn points, complete challenges, and unlock rewards, making loyalty feel like a game. Tokopedia's TokoPoints program in Indonesia also incorporates gamification while utilising AI chatbots for personalised engagement and recommendations.

3. Reward Smartly, Reward Often

Instant gratification has become a critical element to a successful loyalty program. Real-time rewards, automatically applying discounts and points at checkout, create a sense of delight and surprise for the shoppers. Dynamic rewards, tailored to individual behaviour, can further enhance the shopper experience. AI analyses customer actions and offers timely rewards, such as a free shipping offer for an abandoned cart.

Tiered reward systems, like Starbucks Rewards, create a sense of aspiration and exclusivity. AI can help determine the optimal tiers and rewards for different customer segments, ensuring long-term engagement and loyalty. Watsons' loyalty program in Asia, Shopee Coins in Southeast Asia, Flybuys in Australia, and Paytm First in India also leverage tiered rewards and dynamic benefits to drive customer loyalty.

4. Measure, Analyze, Optimise

Measuring the effectiveness of your loyalty program is crucial for ongoing success. AI's predictive analytics capabilities enable retailers to forecast churn risk, empowering them to take proactive steps to retain valuable customers. Customer lifetime value (CLTV) analysis identifies high-value segments, enabling targeted strategies to foster long-term relationships.

AI also helps track key metrics like customer acquisition cost, retention rate, and purchase frequency etc providing insights into program performance and ROI. For instance, Sephora's Beauty Insider program has seen significant increases in CLTV thanks to AI-powered personalization. Similarly, Central Group's The 1 program in Thailand has improved retention rates by leveraging AI to predict churn risk.

Having the ability to measure the direct impact of loyalty programs and to be able to optimise strategies to increase ROI is priceless.

So, what's next for Loyalty in Asia?

AI is paving the way for a new era of customer engagement and loyalty in Asia. Brands are now trying to focus on emotional loyalty, building deeper connections with customers through shared values and personalised experiences. Multi-brand loyalty programs are also gaining traction, offering customers a wider range of rewards and benefits. At the same time, gamification and social media integration are becoming more prevalent, creating interactive and shareable loyalty experiences.

In Asian retail, it would suffice to say that AI-powered loyalty programs are no longer a luxury - they're a necessity. But where can you start? How do you build a program which promises to scale the shopping experience? Well, you start with building a strong customer data foundation- bringing together your customer/shopper's data across multiple channels, creating unique customer identities, clear segmentation and shopper insights. Without this foundation, not even AI can help you! Once you understand who and where to target, then leverage the power of AI to take the loyalty programs to the next level.

Once you have built your system of insight, the next decision is whether to build or buy. This is a whole new discussion but for simplicity sake, I would always recommend that you go with expert technology platforms like Eagle Eye, Talon.One, LoyalGuru etc who have specialised in this domain and have multiple success stories to tell.

While AI presents a powerful solution for loyalty programs, it's not without challenges. Careful handling of customer data is critical to ensure privacy and regulatory compliance. Additionally, the successful implementation and optimization of AI-powered programs often require investments in specialised resources and skill sets.

There is no doubt that it is time to embrace the AI advantage and as this technology advances, we can expect even more innovative approaches to loyalty and shopper engagement. So, why wait? Time to start exploring the AI-powered loyalty engagements and start building strong, more profitable customer relationships. The future of loyalty in Asia is AI-powered!

The Commerce landscape in Asia has transformed dramatically in recent decades. No longer confined to traditional brick-and-mortar stores and linear supply chains, Commerce in Asia now thrives in a dynamic, digital-first environment. This shift has been fueled by rapid technological advancements, changing consumer behaviours, and the increasing interconnectedness of global markets.

Amidst this transformation, a new breed of enablers, known as "as-a-service" companies, has emerged. These companies stand behind brands, providing them with the tools, infrastructure, and expertise to navigate this complex new landscape. From establishing a physical presence to managing online sales, marketing, and logistics, as-a-service models are redefining how brands operate and grow in the Asian market.

This article explores the evolution of commerce in Asia, specifically focusing on various as-a-service models that have emerged to support brands in this new era. I also discuss the benefits and challenges of using these models and how brands can leverage these solutions to achieve sustainable growth in the dynamic Asian market. But first, let's look at what's driving this change.

Challenges of Traditional Commerce in a Digital Age

In the past, establishing a commerce presence in Asia meant investing heavily in physical stores, navigating complex supply chains, and managing many operational challenges across fragmented markets - each with its own complexities. The ever-changing shopping behaviour, fuelled by the shift towards online platforms, has added another layer of complexity as it now demands a new level of agility and customer-centricity from brands. Today's Asian consumers are more discerning than ever, expecting personalized experiences, seamless shopping journeys, and fast, reliable delivery.

At the same time, access to technology and resources has dramatically shortened product innovation life cycles, leading to a plethora of new brands and concepts entering the market every day, each vying for consumer attention and shelf space. Traditional retail models struggle to keep up in this dynamic and fragmented market characterized by diverse cultures, languages, and consumer preferences.

As-a-service models have emerged as a powerful solution, offering brands the flexibility, scalability, and localized expertise needed to navigate this complexity and thrive in the new era of commerce.

Commerce as a Service ( CaaS): The key to unlocking a brand potential

In response to the challenges and opportunities in the Asian ecosystem, a range of as-a-service models have emerged, each catering to specific needs and providing brands with the flexibility and scalability needed for growth. Here are four models which reflect how Commerce As a Service has evolved over time.

1. Retail-as-a-Service (RaaS): Agile Physical Presence

RaaS is where providers offer brands a flexible and cost-effective way to establish a physical presence without the traditional burdens of long-term leases, high upfront costs, and complex operations. Think of it like a WeWork in the retail world, where brands can strategically adjust their presence in terms of space, duration and services utilized, enabling them to scale their operations up or down as needed. By offering shared retail spaces, pop-up shops, staffing, inventory management and in-store technology solutions, large department stores have started using RaaS to help brands test new markets and easily engage with customers.

For instance, GoPopUp, a Singapore-based RaaS provider, enables brands to open pop-up stores in high-traffic areas across Asian markets. This provides a low-risk way to test product-market fit and gather valuable customer insights. Large department stores in many locations have begun opening their floor spaces to this model.

2. E-commerce-as-a-Service (EaaS): Simplifying Online Commerce

EaaS providers offer a comprehensive suite of e-commerce solutions, from e-commerce platform setup and management to digital marketing, logistics, and customer service. This allows brands to focus on their core competencies - product development, brand management, and customer engagement - while leveraging the expertise and infrastructure of their EaaS partners to navigate the complexities of digital commerce. As a result, brands can quickly launch their products online in new categories or markets without extensive development efforts, reducing time-to-market substantially.

This model has experienced rapid growth in Asia, with multiple players in different geographies—aCommerce, Leap Commerce, Intrepid in SEA, Baojun in China, ANS Commerce, and GreenHonchos in India, to name a few. These providers offer end-to-end e-commerce solutions, including store management, performance marketing, customer care, and fulfillment, enabling brands to expand their online presence quickly and efficiently.

Beyond RaaS and EaaS: Modern Distributors and House of Brands

Beyond the traditional RaaS and EaaS models, other as-a-service solutions have emerged to cater to the diverse needs of brands in the Asian market.

3. Modern Distributors: Enabling Omni-Channel Commerce

Modern retail distributors are omnichannel enablers. As evident from the name, they enable brands to sell across multiple channels—online marketplaces, branded e-commerce stores, social media platforms and physical stores. They provide a combination of RaaS and CaaS services to help brands navigate the complex retail landscape, including physical and digital stores, inventory management and logistics, and marketing and consumer insights.

Singapore-headquartered Luxasia, as well as Hong Kong’s Bluebell, exemplify this model by helping brands enter and expand in new markets in Asia Pacific through their multi-channel, multi-category and multi-model approach

4. House of Brands: Consolidating and Scaling Brands

Consider this model as a combination of ‘Modern Distributor + Venture Capital’. House of Brands, also known as roll-up companies, essentially acquire and consolidate multiple smaller e-commerce brands, typically niche D2C brands or those selling online. By leveraging economies of scale, operational expertise, and shared resources, they accelerate the growth of the acquired brands and help them expand their reach across new channels and markets.

These roll-up firms have been thriving in Asia for the last few years, given the region’s large fragmented market, which provides acquisition opportunities, increasing e-commerce adoption, which creates a huge customer base, and ample venture capital, which enables rapid expansion.

India’s Mensa Brands and GlobalBees and Singapore’s Una Brands and Rainforest are prime examples of roll-up companies in Asia. They acquire D2C brands across various categories and provide them with capital, marketing expertise, and operational support to scale their businesses.

Navigating this 'As a Service' landscape and choosing a suitable model is extremely important. The optimal AaS model will depend on a brand's unique needs, target audience, product categories, and growth objectives. Brands must carefully assess their priorities, conduct thorough research, and choose partners that align with their long-term vision.

The Future of Commerce in Asia: A Customer-Centric, Technology-Driven Approach

Technology lies at the heart of this evolution of commerce. E-commerce platforms, social media, and mobile apps have empowered consumers to shop anytime, anywhere, while data analytics and AI have enabled brands to gain deeper insights into consumer preferences and personalize their offerings.

As-a-service models represent a paradigm shift, empowering brands to adapt to the changing commerce landscape. By leveraging the provider's technology infrastructure, operational capabilities, and strategic partnerships, brands can navigate the complexities of modern commerce, unlock new growth opportunities, and build lasting relationships with their customers.

The rise of 'Commerce as a Service' in Asia signifies a move towards a more customer-centric, technology-driven, and agile approach. Brands embracing these models are well-positioned for success in this ever-evolving commerce landscape of the future.

The Asian retail landscape is undergoing a seismic shift, driven by a wave of high-profile mergers and acquisitions. Just recently, Canadian convenience store giant Alimentation Couche-Tard made an informal offer to acquire Seven & I Holdings, the Japanese owner of 7-Eleven. If successful, this cross-border deal could significantly expand Couche-Tard's presence in Asia and reshape the convenience store sector in Japan.

M&A in Asian retail is not new. In fact, we have seen a flurry of activity starting in 2020 across major Asian markets (China: JD acquiring Dada Nexus, Alibaba acquiring Sun Art Retail, SEA: GoJek & Tokopedia merging to form GoTo, India: Flipkart acquiring ClearTrip, Tata with BigBasket, and Reliance acquiring Dunzo and Fynd, etc.).

Not just M&A, partnerships and alliances among significant players are back on the table. A good example is the recent reconciliation between South Korean e-commerce giant Coupang and food conglomerate CJ Group—an unexpected reunion that ended a 20-month hiatus sparked by a pricing dispute. Meanwhile, we see multiple markets ripe for consolidation, with speculation about potential mergers or acquisitions involving major players.

These developments underscore a broader trend across Asia: mergers and acquisitions are becoming pivotal in shaping the future of commerce. From e-commerce behemoths expanding their reach to traditional retailers embracing digital transformation, companies are leveraging M&A to accelerate growth, fuel innovation, and rapidly build crucial capabilities. Even technology vendors are actively participating in this frenzy, acquiring specialized agencies and consultancies to bolster their offerings and stay ahead of the curve.

In this blog post, I explore the multifaceted role of M&A in the Asian retail ecosystem, examining how it catalyses growth, fuels innovation, and enables companies to acquire essential capabilities rapidly. We'll also delve into the increasing prominence of technology vendors in this landscape and the implications of their acquisitions for the future of retail.

M&A as a Growth Catalyst

In the fiercely competitive Asian retail market, achieving scale and expanding market share is paramount. M&A provides a strategic pathway for companies to rapidly achieve these objectives by acquiring existing players or merging with complementary businesses. A prime example is Grab's acquisition of Uber's Southeast Asia operations in 2018. This landmark deal consolidated the region's ride-hailing and food delivery markets, propelling Grab to a dominant position and intensifying competition with other players like GoTo and Foodpanda.

Similarly, the formation of GoTo in 2021 through the merger of Gojek and Tokopedia created Indonesia's largest tech company, combining ride-hailing, food delivery, e-commerce, and financial services under one roof. This strategic move not only accelerated the growth of the digital economy in Indonesia but also intensified competition with regional giants like Sea Limited and Grab.

In India, Reliance Retail's ongoing pursuit of Future Group's retail assets and the Tata Group's acquisition of BigBasket exemplifies the ambition of conglomerates and traditional retailers to expand their footprint and solidify their market position. Once completed, the Reliance-Future Group deal could give Reliance Retail a dominant position in India's organized retail market. Meanwhile, the Tata Group's acquisition positions them to capitalize on the growing demand for online grocery shopping and compete with established players like Amazon and Flipkart.

These are great case studies on how M&A has served as a catalyst for growth in the Asian retail market. It enables companies to quickly access new markets, customer bases, and capabilities, thus accelerating their growth trajectory.

Fueling Innovation and Fast-tracking Capabilities

In the last few years, retailers have been racing to innovate and rapidly acquire new capabilities to stay ahead of the curve. M&A actually fast-tracks this process and serves as a powerful tool for companies to achieve both these objectives—driving innovation by infusing new technologies and ideas while also enabling the swift acquisition of crucial skills and market access!

In China, JD.com's acquisition of Dada Nexus strengthened its last-mile delivery capabilities, particularly for groceries and other on-demand items. In addition to fueling innovation, M&A has allowed companies to fast-track the acquisition of essential capabilities. In India, Zomato's acquisition of Blinkit and Reliance investments in Fynd and Dunzo shows how companies are strategically acquiring/investing in startups to strengthen their capabilities in logistics, quick commerce, and various other sectors. In Indonesia, Bukalapak's series of acquisitions, including a logistics company, a payment gateway, and a digital marketing agency, further demonstrates this point.

These examples highlight how M&A has served as a catalyst for both innovation and the rapid acquisition of capabilities in the Asian retail market. By acquiring or merging with companies possessing complementary technologies, skills, or market access, Asian businesses have been able to quickly adapt to the changing landscape, enhance their offerings, and gain a competitive advantage.

The Role of Technology Vendors

While this saga plays out among retailers, the technology vendors are not far behind. Through strategic acquisitions, these vendors are expanding their capabilities and consolidating their position in the market. For instance, Salesforce's acquisition of Demandware allowed it to create Salesforce Commerce Cloud, a leading e-commerce platform.

Not to be left behind, Adobe, by acquiring Magento Commerce, further strengthened its digital experience offerings, providing retailers with a comprehensive suite of solutions for building and managing online stores, personalizing customer experiences, and analyzing customer data.

Furthermore, mid-size commerce agencies and retail tech consultancies have become hot targets for acquisitions. Valtech's acquisition of Kin + Carta is a prime example, bringing together expertise in experience innovation, digital engineering, cloud, data, and AI to deliver end-to-end digital transformation solutions for retailers. Similarly, Accenture's acquisitions of commerce agencies like The Stable and Tambourine underscore the growing demand for specialized expertise in commerce transformation.

As retailers increasingly look to develop new innovations, their technology partners are looking to not only build their own capabilities but also acquire the talent and expertise of specialised agencies to offer a wider range of services to their clients. This trend will likely continue as the retail landscape becomes increasingly complex and competitive, requiring retailers to partner with technology vendors that can provide them with the comprehensive solutions they need to succeed.

Emerging Trends and Future Outlook

The Asian retail landscape continues to evolve rapidly, with new trends and technologies constantly emerging. The rise of Gen AI, quick commerce, hyper-personalisation, social commerce, and the increasing importance of fintech and logistics are just a few examples of the forces shaping the industry's future.

All this leads to a relentless pursuit to innovate & grow amongst retailers, which in turn is fuelling the M&A activity in the region. Companies will seek to acquire startups and established players with expertise in these emerging fields to stay ahead of the curve and quickly integrate these capabilities into their existing operations.

However, deciding between organic and inorganic growth through acquisitions is not always straightforward. Acquisitions come with their own challenges of integration and cultural alignment. Companies must carefully weigh the pros and cons of each approach, considering factors such as time-to-market, cost, risk, and the potential for synergy. No one wants a situation where there is a 'square peg in a round hole'.

The future of Asian retail is undoubtedly bright. Still, it will be shaped by companies that can successfully navigate the complexities of M&A and leverage it as a strategic tool for growth and innovation.

The Asian culinary landscape is undergoing a dynamic transformation driven by a confluence of factors reshaping how people experience food. With a projected value of USD 270 billion by 2032, the food industry in Asia is poised for significant growth, fueled by rising disposable incomes, rapid urbanisation, and evolving consumer preferences. This economic prosperity and urban development surge has led to a growing demand for diverse and convenient dining options. At the same time, technological advancements have revolutionised how food is ordered, prepared, and delivered.

As FoodTech got supercharged during COVID-19, the food and dining markets in Asian countries have been constantly evolving to accommodate consumer eating habits. This innovation in the food industry has taken multiple shapes and formats and has welcomed trends like cloud kitchens, quick-service restaurants, meal kit subscriptions, air menus, and online table booking services, among others. Moreover, the rich cultural heritage, diverse traditions, and flavours offer a wealth of inspiration for culinary innovation, leading to a fusion of traditional and modern dining experiences.

In this article, we take a deep dive into five trends that are reshaping the future of dining in Asia. From the evolution of food ordering and the rise of smart restaurants to the focus on health and wellness and data-driven personalisation, these trends offer a glimpse into the exciting possibilities for the Asian food industry. Towards the end, we also offer recommendations to aspiring entrepreneurs and established food retailers looking to transform and ride this culinary wave digitally. But first, let's look at what makes this industry unique and an exciting place to be!

What Makes The Future of Dining Exciting in Asia

Asia’s growing middle class and rapid urbanisation is driving the growth of casual dining and food delivery services, catering to the fast-paced lifestyle of city dwellers. In addition, rising disposable incomes is fuelling demand for premium & diverse dining experiences as consumers spend more on culinary adventures. The changing consumer preferences, especially among the tech-savvy Asian GenZ and millennial consumers, are also putting the spotlight on healthier, sustainable food options and dining experiences that incorporate technology.

Tech adoption, especially AI & Data, as a result, is now playing a huge role in driving innovation in this domain.

With so much happening in the Asian food industry, Venture capital investments have been on the rise since 2019, with a particular focus on startups that are driving innovation beyond food delivery. Investors are now looking for companies developing new technologies and business models to enhance the entire food ecosystem, from farm to table. At the same time, Asia's rich cultural heritage and diverse traditions and flavours are a treasure trove of culinary inspiration. The growing interest in exploring different cultures drives the demand for authentic and fusion cuisines, creating exciting opportunities for culinary experimentation and cross-pollination.

With these dynamic forces at play, the future of dining in Asia promises to be a vibrant and exciting journey for both consumers and businesses alike.

Top Five Food Dining Trends in Asia

Let's look at the top five trends revolutionising how people interact with food in Asia. These trends reflect changing consumer preferences,the impact of technological investments, and the growing emphasis on health, nutrition, and sustainability.

1. The Evolution of Food Ordering: Convenience & Personalisation at your fingertips

The advent of smartphones and high-speed internet has dramatically altered the way Asians order food, making it more convenient and personalised than ever before. Apps like Foodpanda, GrabFood, and Zomato have become indispensable tools, offering a vast array of cuisines at the touch of a button. Consumers can now explore diverse menus, compare prices, read reviews, and place orders with unparalleled ease. The result is a booming food delivery market in Asia which is projected at USD 61.38 billion by 2024.

The COVID-19 pandemic accelerated the adoption of contactless services, including food ordering and payments. Restaurants and food delivery platforms swiftly adapted to this new normal, implementing QR code menus, online payment options, and delivery without physical contact. This shift not only enhanced safety but also streamlined operations, improving efficiency for both customers and businesses.

Beyond convenience and safety, the food ordering landscape in Asia is witnessing the rise of meal kit subscription services. The Asia Pacific meal kit delivery services market size was estimated at US$ 5.2 billion in 2023 and is expected to grow at a CAGR of 13.2% from 2024 to 2030. Companies like Blue Apron and HelloFresh have gained popularity by delivering pre-portioned ingredients and recipes directly to consumers' doorsteps. This trend caters to health-conscious individuals and those seeking to explore new cuisines without the hassle of grocery shopping.

As technology advances, the future of food ordering in Asia looks even more promising. Innovations like AI-powered recommendations, drone delivery, and augmented reality dining experiences are on the horizon, promising to redefine the way we interact with food.

2. The Rise of Smart Restaurants: Where Technology Meets Gastronomy

Known for its culinary diversity and rapid technological adoption, Asia is at the forefront of the smart restaurant revolution. This transformation, where technology seamlessly integrates into the dining experience, is driven by a confluence of factors, including the increasing demand for efficiency, convenience, and personalisation for both consumers and restaurant operators.

Tabletop Ordering Tablets, now a common sight in many Asian kitchens, empower customers to browse menus, place orders, and even pay bills without the need for human interaction. Simultaneously, kitchen display systems (KDS) have become indispensable tools for streamlining kitchen operations. By providing real-time order information to the kitchen staff, KDS significantly reduces order errors, speeds up service, and improves overall efficiency.

The integration of robotics and automation is another hallmark of smart restaurants in Asia. Robotic arms are increasingly taking over tasks such as food preparation, cooking, and even serving while robotic waiters navigate dining rooms to deliver orders. While this adoption of robotics is still in its early stages, it holds immense potential (in fact, market size is expected to be around USD 4 billion by 2026) to improve productivity, reduce labour costs, and enhance food safety.

By combining the convenience of digital ordering with the efficiency of automation, restaurants can deliver faster service, personalised menus, and a more engaging atmosphere.

3. The Omnichannel Dining Experience: Seamlessly Blending Online and Offline

Hybrid models that blend online and offline channels have changed how consumers interact with food by delivering seamless and personalised customer journeys. At the core of this revolution are ghost kitchens and virtual brands. These kitchen-only operations, often housed in shared spaces, focus exclusively on delivery and takeout, allowing restaurants to expand reach, experiment with new concepts quickly, optimise operational efficiency and reduce overhead costs.

These hybrid business models offer dine-in, takeout, and delivery services, leveraging technology to manage orders, optimise operations and social media platforms to drive customer engagement.This approach ensures a consistent customer experience across all channels while maximising revenue streams.

Food aggregators, such as GrabFood, Foodpanda, and Deliveroo, have played a pivotal role in shaping the omnichannel dining landscape. By partnering with multiple restaurants and offering centralised kitchen facilities, these platforms provide customers with a vast array of choices and efficient delivery services.

The rise of omnichannel dining in Asia has significantly impacted the food service industry. Restaurants are becoming more data-driven, using customer insights to tailor their offerings, and technology to optimise operations.

4. Health and Wellness: A Growing Focus on Nutrition and Sustainability

In response to growing health consciousness and evolving dietary preferences of Asian consumers, the Asian food industry is witnessing a notable shift towards health & wellness. Consumers are now beginning to actively seek out dining experience & food options that prioritise nutrition and ethical sourcing.

As a result, we are now seeing a growing popularity of plant-based, low-calorie, and organic ingredients, with restaurants prioritising fresh and wholesome food with transparent cooking methods. The demand for alternative protein sources is another significant aspect of this trend, with consumers seeking out plant-based meat alternatives. Good Meat, a subsidiary of Eat Just, Singapore-based Growthwell Foods, Beyond Meat, and Hong Kong-based OmniPork that sells plant-based pork alternatives, are a few examples of food brands catering to consumers' demand for alternative meat options.

The food delivery industry is also adapting to this trend by providing filters based on dietary restrictions, calorie counts, and nutritional information, empowering consumers to make informed choices. The focus on wellness extends beyond just food choices. We now see consumers figuring out the origins of their food, seeking out restaurants that prioritise ethical sourcing and supporting local produce. As awareness about the connection between diet and overall well-being grows, the food industry in Asia is likely to witness further innovations in healthy and sustainable dining experiences.

5. Data-based Personalisation: Tailoring the Dining Experience to individual Tastes

While food is at the core of the dining and food delivery industry, the role of data can’t be negated. Restaurants and food delivery companies are leveraging customer data to gain valuable insights into their behaviour, preferences, ordering patterns, thereby creating personalised experiences and fostering loyalty. In fact, over the years, loyalty programs have become a key strategy for the restaurant and food delivery brands to retain their customers and improve engagement. Customer feedback and sentiment analysis provide invaluable insights and are critical to improving conversions and enhancing customer satisfaction. This is now an integral component of any digital marketing strategy as this data can be used to refine menus, improve service, and develop new products or marketing campaigns.

Essentially, data is becoming the secret ingredient for success in the food industry. By harnessing its power, businesses can create a more engaging, satisfying, and profitable customer experience.

The Future is Now – Embracing the Digital Transformation in Food Retail in Asia

The future of food retail in Asia is unfolding at an exhilarating pace, driven by a mix of technological advancements, cultural shifts, and consumer demand. The landscape is evolving far beyond simple delivery services, and those who embrace this transformation will thrive.

For aspiring entrepreneurs, the Asian food retail scene offers a fertile ground for innovation. By leveraging technology, you can differentiate your brand, create unique customer experiences, and streamline operations. Consider identifying gaps in the market where new technologies haven't yet been fully adopted, such as niche cuisines, personalised dining experiences, or innovative food ordering solutions. Partnering with tech companies and utilising data analytics can also give you a significant edge over the competition.

For established food retailers, staying relevant and competitive requires embracing digital transformation. Evaluate your current operations and pinpoint areas where technology can improve efficiency, enhance customer engagement, and drive growth. Investing in staff training to ensure your team can effectively utilise new technologies is crucial for success. Don't hesitate to experiment with different formats and technologies to find what works best for your brand and customers.

Whether you are a budding entrepreneur or a seasoned restaurateur, the future belongs to those who can quickly adapt to changing customer trends/ food habits while embracing technology to drive innovation. The future of dining is not just about what's on the plate; it is about how digital is reshaping the entire culinary experience. It is exciting to be a witness to this digital revolution that is transforming the way Asia dines.

The COVID-19 pandemic was a catalyst for unprecedented change in the Asian retail landscape. As physical stores shuttered and supply chains fractured, a new model emerged, reshaping how consumers interact with brands: direct-to-consumer (D2C) retail.

Riding this digital wave, Asian businesses began selling products directly to customers, bypassing traditional intermediaries like wholesalers and distributors. While the pandemic accelerated this shift, the D2C model's success was actually rooted in Asia's existing infrastructure and market readiness.

A burgeoning digital-first generation, rising disposable incomes, and widespread smartphone and internet penetration created fertile ground for D2C growth. The convenience and personalised experiences offered by D2C brands resonated with consumers, driving a significant shift in shopping habits.

An Ogilvy report highlighted that a staggering 94% of Southeast Asian consumers who adopted digital services during the pandemic intended to continue these habits afterwards. As a result, companies across Asia doubled down on the D2C model, reaping the benefits of potentially lower costs, higher profits, and, most importantly, deeper customer insights due to direct engagement.

This article delves into the factors propelling the rise of D2C in Asia, exploring the challenges and opportunities these brands face, and highlighting a few success stories that have captured the hearts of Asian consumers. But first, let's take a deeper look at the reasons why the region has become a hotbed for these D2C brands.

Why D2C is Thriving in Asia

Across Asia, from major cities like Shanghai and Mumbai to tech-savvy hubs like Singapore and Seoul, D2C brands have become a powerful force, redefining how consumers discover, interact with, and purchase products. This transformation isn't limited to new players; established giants like Nike and Gap also embrace the D2C model alongside digital-first disruptors like boAt and Hey Tea. But what's fueling this remarkable growth? Here are 4 key factors that have made Asia a hotbed for D2C innovation.

• Pervasive smartphone and internet penetration

D2C thrives on digital infrastructure, and Asia boasts of a massive network of smartphone users and internet connectivity. In 2022, the smartphone adoption rate in the Asia-Pacific region reached 76%, a significant increase from 64% in 2019. Similarly, the Asia-Pacific region has the highest number of internet users in the world. This widespread access, even in lower-tier cities, has empowered D2C brands to reach consumers directly, regardless of location. With a profound grasp of this digital ecosystem, these brands specifically target tech-savvy consumers while focusing relentlessly on innovation to outpace competitors.

With a very strong smartphone ecosystem and wide internet connectivity, D2C was always poised to thrive in the region without much friction.

• Rapid adoption of online shopping

The growth of D2C is quite intricately linked to the growth of e-commerce. It would not be an exaggeration to say that e-commerce and other digital services, such as online payment, paved the path for the D2C industry to flourish in Asia.

The Asia-Pacific region leads the world in the number of internet users, and their comfort with online shopping has translated into a booming e-commerce sector. A 2023 joint report by Google, Temasek, and Bain & Co. revealed that the e-commerce sector experienced a 22% year-on-year revenue growth, underscoring its rapid expansion. Additionally, a KPMG report predicts that the retail e-commerce industry in the region is expected to reach US$7.4 trillion by 2025, growing at a CAGR of 12%.

This shift in consumer behaviour has naturally fueled the growth of D2C, which offers the convenience and personalisation that online shoppers crave. With the near vertical growth of the e-commerce industry, it was only natural for D2C to grow under its shade.

• Growing middle class with disposable income

Asia's burgeoning middle class, with its increasing disposable income, is a prime target for D2C brands. This demographic is willing to spend more on quality products and unique experiences, is open to brand experimentation, and prefers to buy local.

As consumers' purchasing power grows, so does their demand for brands that resonate with their cultural values and aspirations. D2C brands have capitalised on this trend by offering premium, personalised goods that cater to the preferences of this growing middle-class segment. They have also been able to cultivate brand loyalty by emphasising their commitment to local communities and by fostering a sense of shared identity with their consumers.

• Changing consumer expectations

The digital age has transformed consumer expectations. Today's shoppers demand convenience, personalised interactions, and unique brand experiences. The growing Gen Z population, in particular, seeks brands that align with their values, such as sustainability and ethical practices. This shift is evident in the growing preference for brands prioritising sustainability, ethical sourcing, and social responsibility.

D2C brands have risen to meet these expectations, leveraging data to understand preferences, offer customised solutions, and communicate their commitment to social responsibility.

However, considering that the D2C industry is new, it comes with its own challenges along with opportunities.

Navigating the D2C Landscape: Challenges on the Path to Success

While it’s true that the D2C industry enjoys the benefits that the Asian ecosystem provides, it is not bereft of the challenges of being a relatively new industry. Here are a few significant hurdles brands face on their path to success. brand.

• Intense Competition: The D2C market is increasingly saturated, with a growing number of brands vying for consumer attention. New digital-first companies compete not only with each other but also with established players who are expanding into the D2C space. Differentiation and innovation are crucial for survival.

• High Customer Acquisition Costs (CAC): Attracting new customers in this crowded landscape can be expensive. D2C brands often invest heavily in marketing, advertising, and promotional activities, leading to high CAC. Finding cost-effective customer acquisition strategies is a constant challenge.

• Logistics and Supply Chain Complexities: Managing the end-to-end supply chain can be daunting for D2C brands. Ensuring efficient inventory management, reliable shipping, and seamless returns processes in a region as vast and diverse as Asia requires careful planning and execution.

• Building Brand Awareness and Trust: Establishing a strong brand presence and gaining consumer trust takes time and effort. New D2C brands must overcome the challenge of competing with well-known, established brands. Building brand awareness through effective storytelling, transparent practices, and exceptional customer service is crucial.

• Navigating Regulatory and Cross-Border Complexities: D2C brands must grapple with a complex and evolving regulatory landscape that varies across countries in Asia. This includes ensuring compliance with data protection laws, consumer rights regulations, and product safety standards. Expanding across borders introduces additional challenges, as brands must adapt to different cultural nuances, consumer preferences, and legal frameworks in each market.

Despite these challenges, the D2C landscape in Asia remains ripe with opportunities. Brands that are able to adapt, innovate, and navigate these complexities thrive in this dynamic market. In the next section, let's look at a few successful Asian D2C brands that have overcome these challenges and emerged as industry leaders.

Asian D2C Brands That Customers Love

The D2C landscape in Asia is a mosaic of regional success stories, each shaped by unique market dynamics and consumer preferences. Let's discover a few of these D2C brands from China, India, and Southeast Asia, uncovering the common threads that weave through their triumphs:

China: Where Innovation Meets E-commerce Prowess

In China, beauty brand Perfect Diary and snack brand Three Squirrels have become household names, each carving their own path in the D2C landscape through a mastery of social media and a keen understanding of the digital landscape. Perfect Diary, targeting Gen Z and millennials, has leveraged platforms like WeChat and Weibo to build a cult-like following and achieve a valuation of US$4 billion. Their savvy collaborations with influencers and celebrities, along with a focus on data-driven product development, have set them apart in the crowded beauty market.

Three Squirrels, on the other hand, has revolutionised the snack industry by harnessing the power of creative branding, engaging social media campaigns, and a data-driven approach to product offerings. Their strong online presence on platforms like Tmall cemented their position as a leading online snack brand in China. Live-streaming platforms have further amplified their success, allowing them to showcase products and interact directly with consumers in real time.

India: A Growing Appetite for Digital-First Brands

India's D2C market is witnessing a surge in popularity, with brands like Mamaearth and boAt leading the charge by offering affordability, building strong communities, and establishing an omnichannel presence. Mamaearth, specialising in toxin-free baby and personal care products, has quickly become India's fastest-growing D2C brand. Their commitment to natural ingredients and transparency resonates with millennial parents, who are increasingly price-conscious and seek quality products at competitive prices, propelling their valuation to US$1.2 billion.

Meanwhile, boAt has made waves in the audio devices market with its trendy, affordable products and strong brand identity that fosters a sense of community and loyalty among its consumers. While starting online, both brands have expanded to offline channels to reach a wider audience, a strategy that has proven successful in the Indian market.

Southeast Asia: A Diverse Market with Unique Opportunities

Southeast Asia's diverse D2C landscape boasts brands like Singapore's Love, Bonito and Malaysia's Signature Market, each catering to distinct consumer needs through localization, a mobile-first approach, and strong community engagement. Love, Bonito has carved a niche in women's workwear, focusing on stylish and comfortable designs tailored to the Asian physique. Their strong online presence, enhanced by mobile-friendly websites and apps, and expansion into physical stores have fueled their growth across multiple markets.

Signature Market, on the other hand, has captured the growing demand for healthy snacking with its locally sourced, affordable products. They've expanded into new categories like wellness and baby food, establishing themselves as a trusted D2C brand in the region by building strong online communities and actively engaging with consumers through social media.

Common Threads of Success: Decoding the D2C DNA

While Asia's D2C landscape is rich in diversity, successful brands share a common DNA, a set of key traits that have propelled them to the forefront of the retail revolution:

• Digital Prowess: Asian D2C brands are digital natives who are fluent in the language of technology and data. They harness the power of e-commerce platforms, social media, and data analytics to reach consumers, build relationships, and drive sales.

• Customer Obsession: These brands don't just sell products; they create experiences. They listen intently to their customers, anticipate their needs, and deliver personalised solutions that go beyond transactions.

• Authentic Storytelling: In a crowded marketplace, authenticity is a powerful differentiator. Successful D2C brands weave compelling narratives that resonate with consumers on an emotional level, fostering a sense of connection and loyalty.

• Agility and Innovation: The D2C model empowers brands to be nimble and responsive. They can quickly experiment with new products, marketing strategies, and business models, adapting to their customers' ever-changing needs.

• Community Building: D2C brands understand the power of community. They create spaces where customers can connect, share experiences, and become brand advocates, amplifying their reach and influence.

These shared characteristics form the foundation of D2C success in Asia. By embracing these principles, brands can unlock their full potential and thrive in this dynamic and rapidly evolving market.

So, what's Next for D2C in Asia?

The D2C revolution in Asia shows no signs of slowing down. With a vast and diverse consumer base, rapid technological advancements, and a growing appetite for personalised experiences, the future of D2C in Asia is incredibly promising. Here's what we can expect to see in the coming years:

1. Deeper Integration of Technology: D2C brands will harness cutting-edge technologies like AI, machine learning, and data analytics to elevate customer experiences, streamline supply chains, and deliver hyper-personalised marketing.

2. Expansion and Innovation: D2C brands will aggressively explore new markets within Asia and beyond, venturing into untapped product categories. We can also anticipate a surge in innovation, with brands experimenting with emerging technologies like augmented reality and virtual reality to differentiate themselves in a competitive landscape.

3. Sustainability and Omnichannel Retailing: As consumers increasingly prioritise sustainability and ethical practices, D2C brands will respond by sourcing sustainable materials, reducing waste, and supporting social causes. Additionally, we'll witness the rise of omnichannel retailing, with brands seamlessly integrating online and offline experiences to cater to diverse consumer preferences.

4. Community-Driven Growth: D2C brands will continue to invest in fostering vibrant communities around their products and brands. Engaging content, active social media conversations, and immersive events will play a crucial role in deepening customer relationships and driving organic growth.

The future of D2C in Asia is a story of immense potential, driven by a dynamic interplay of technology, consumer behaviour, and entrepreneurial spirit. Brands that can adapt to the changing landscape, prioritise customer-centricity, and embrace innovation will undoubtedly thrive in this exciting new era of retail.

Sustainability has emerged as a CEO-level agenda for Asian retailers. With climate change a pressing reality and conscious consumerism on the rise, brands must urgently adapt if they want to resonate with younger generations' values.

The “Good for Me, Good for the Planet” trend that gained momentum during the pandemic is the new value system for consumer decision-making, particularly amongst millennials and Gen Z, who are at the forefront of conscious consumerism, seeking more transparency across the whole product lifecycle—from how and where the products are made to who the stakeholders are across the value chain.

Asian retailers are already taking steps, but it's crucial to move beyond superficial "greenwashing" and embrace genuine, actionable sustainability practices. This means more than just launching a few eco-friendly products or making vague promises. It requires a holistic approach considering the entire product lifecycle, from sourcing and manufacturing to packaging and disposal.

The challenges, however, are real: complex supply chains, fragmented data, and the need to balance sustainability with digital transformation and profitability. However, the rewards are significant: enhanced brand reputation, increased customer loyalty, regulatory compliance, and even cost savings through resource optimisation.

This article dives deep into the actionable sustainability trends emerging in the Asian retail landscape, showcasing how brands are turning challenges into opportunities and driving real change. From cutting carbon footprints and reducing waste to embracing circular business models and promoting supply chain transparency, Asian retailers are proving that sustainability isn't just good for the planet—it's good for business.

Trends Shaping a Greener Retail Landscape

The Asian retail market is witnessing a growing wave of sustainability initiatives driven by consumer demand and regulatory pressures. Here are the five big trends/initiatives being adopted by Asian retailers to help them go beyond greenwashing and achieve tangible results.

1. Cutting Carbon- From Renewable Energy to Green IT

Asian retailers are making significant strides in reducing their carbon footprint by investing in energy-efficient technologies and renewable energy sources like solar and wind power for their retail operations. Additionally, adopting green building principles for new stores and renovations, such as energy-efficient design, water conservation measures, and the use of sustainable materials, is becoming common.

For instance, Japan’s biggest retail group by sales, Aeon, which accounts for 1% of the country’s electricity consumption, is in the process of transitioning to 100% renewable energy for its 160-plus malls in the country. It wants to achieve net zero emissions from store operations by FY2040. Meanwhile, Samsung is developing innovative, cutting-edge carbon capture and clean air technologies to be installed in its manufacturing facilities. This proactive approach tackles emissions at the source, setting a new standard for environmental responsibility.

Green logistics is another area gaining traction. Asian retailers are adopting fuel-efficient or electric vehicles for transportation and deliveries, optimising routes to reduce mileage and investing in energy-efficient warehousing equipment.

For their IT Infrastructure, a key contributor to emissions, retailers are increasingly opting for cloud migration and partnering with technology companies that prioritise greener technologies to minimise the environmental impact of their digital operations.

While Asian retailers share many sustainability strategies with their global counterparts, it is the rapid adoption of innovative technologies that sets them apart in their efforts to reduce carbon footprints. The region's tech-savvy culture and willingness to experiment are accelerating progress toward a low-carbon future

2. Innovating for Zero Waste

Asia generates over 40% of the world's municipal solid waste, with a significant portion stemming from the retail sector. This includes packaging, unsold or expired products, damaged goods, customer returns, and operational waste. The consequences are dire: a significant increase in carbon footprints, loss of biodiversity, and pollution.

Having more supply than required is often the biggest cause of waste, which can make a huge impact. However, accurate demand forecasting, inventory optimisation, and more efficient in-store execution remain the key challenges for retailers in streamlining the supply and demand equation which is often the biggest cause of waste. It requires relevant data and insights to manufacture products as per customers’ preferences, in the right quantities and just in time.

A multifaceted approach is the need of the hour, and we are now seeing Asian retailers adopt a combination of technology, data-driven strategies for inventory optimization, and innovation solutions around eco-friendly packaging and recycling. For example, Alibaba’s grocery chain Freshippo's demand forecasting and inventory optimization are driven by customer demand. It utilises sales data to predict regional consumption habits and determine the next day's inventory for each store. This demand-oriented approach allows them to avoid overstocking and shortages, ensuring they can meet customer needs effectively.

Similarly, Thailand’s largest supermarket chain, Central Food Group, has implemented an AI-based system to identify products nearing their expiration date to minimise food waste. It strategically prices these products with discounts of 20% to 40% while determining the best recycling channel for unused products.

While progress is being made, the journey to zero waste is ongoing. By taking a multi-prong approach to combating waste, leveraging technology, data, and local solutions, and collaborating with stakeholders, Asian retailers are transforming waste reduction from a challenge into a competitive advantage.

3. Transparency and Traceability: Building Trust and Accountability

Asian retailers are increasingly recognising the value of transparency and traceability in their supply chains for several reasons.

While there is a growing segment of consumers demanding ethically sourced and sustainable products, stricter regulations requiring companies to disclose information about their suppliers, working conditions and their environmental impact is forcing the retailers to take a closer look at their supply chains and ensure compliance. On top of that, transparency and traceability have become differentiators for retailers in managing their reputation, attracting new customers, and even commanding premium prices.

Indonesian viscose rayon producer APR is a glowing example of responsible sourcing and supply chain digitisation. The company produces viscose rayon, a natural alternative to petroleum-based synthetic fabrics, from 100% wood cellulose. To ensure it sources wood fibre only from sustainably managed plantations and forests, APR has made its viscose supply chain traceable. The company has implemented a blockchain-based platform, Follow Our Fibre, to track its products from seedling to shipment. Data is captured automatically at each stage of the value chain using integrated tracking programmes. Consumers can scan a QR code on the product to see where that bale was produced, where its source material came from and how it was shipped.

There are many more Asian companies like APR that are leveraging technology to better track the origin of materials and monitor supply chain activities. Blockchain, AI, and other digital tools are crucial in these efforts. They allow retailers to track products in real time, monitor supplier compliance, and identify potential risks in their supply chains. While meeting regulatory requirements is essential, leading retailers are going beyond compliance to gain a competitive edge. The trend is likely to continue as consumers and governments demand greater accountability and sustainability from businesses.

4. Sustainable Product Innovation- Rethinking Design & Materials.

Asian retailers are actively incorporating sustainability into their product development process. This shift goes beyond simply creating eco-friendly lines; it involves a fundamental rethinking of design, materials, and manufacturing processes.

Many are investing in research and development to create products with sustainable materials, such as organic cotton or recycled plastics and implement eco-friendly manufacturing processes. This not only reduces the environmental impact of production but also appeals to a growing consumer base that values eco-consciousness. For instance, Kuala Lumpur-based Terrae sells activewear made from fabric that it creates by recycling used plastic bottles, discarded fishing nets from the ocean, fabric scraps and leftover fabrics, showcasing the potential of innovative materials to transform the industry.

Durability & energy efficiency are getting a lot of attention, with some brands looking to make products which are built to last- reducing the need for fewer replacements. Additionally, they prioritise energy-efficient designs to minimise the environmental impact of product use. For example, Samsung is developing low-power technologies for its consumer electronics products which will lower power consumption by about 30% by 2030 compared to products with the same specifications in 2019.

Parallelly, a lot of Asian brands are rethinking packaging designs, opting for recyclable, reusable or biodegradable materials to minimise waste and pollution. For example, the Vietnamese healthy snack brand Lecka is the first Asian firm to use bio-based, home-compostable packaging.

Asian retailers’ strategic move towards sustainable product innovation not only addresses environmental concerns but also attracts a growing segment of consumers who value eco-consciousness. By investing in new materials, technologies, and design principles, Asian retailers are not only reducing their environmental impact but also creating a competitive advantage in a rapidly evolving market.

5. Embracing Circularity: A New Business Paradigm

To embrace sustainability, many Asian retailers are transitioning towards a circular economy framework. Contrary to the traditional "take-make-dispose" model, the focus is now shifted to production and consumption in a manner that prioritises waste reduction and keeps products and materials in use for as long as possible.

A growing number of Asian brands are finding innovative ways to give new life to waste materials. This includes upcycling clothing, creating accessories from discarded fabrics, and repurposing packaging materials for new uses. ew-age Asian brands like Vietnam’s The Vandal and Ugly Born, Hong Kong-based Redress, Japan’s Relier81, and India’s Doodlage are just a few of many who are creating sustainable products from waste materials, contributing to the growing trend of upcycling & repurposing in Asia.

At the same time, brands are exploring new business models that extend the lifespan of products. This includes rental services, repair programs, and take-back initiatives, offering consumers alternatives to ownership. For example, Singapore-based startup Style Theory offers luxury dresses and branded bags for rent. With customers paying for the use rather than ownership, these products can be used for longer, ultimately reducing waste.

Japanese retailer Uniqlo is a prime example of a brand that has successfully integrated circularity into its business model. Uniqlo’s “Life Wear” concept is based on designing and producing products that are durable and can be reused or recycled. It runs a host of sustainability initiatives, including donating second-hand clothes collected from its customers to refugees, using recycled materials for new products, and repairing and upcycling products for its customers at its Re. Uniqlo studios. These efforts have not only reduced Uniqlo's environmental impact but also resonated with consumers, reinforcing the brand's commitment to sustainability.

The circular economy represents a win-win for both businesses and the environment. By incorporating circularity in business with initiatives like sustainable product lines and repair and recycling services, many Asian brands have been able to appeal to environmentally conscious consumers creating new revenue streams while contributing to a more sustainable business.

Sustainability As The CEO Level Agenda

Sustainability has moved to the forefront of the CEO agenda, becoming a core business imperative rather than a niche concern. With the growing influence of conscious consumerism, customers are increasingly choosing brands that align with their values, and investors are prioritising Environmental, Social, and Governance (ESG) factors in their investment decisions. CEOs who embrace sustainability not only contribute to the planet and society but also position their companies for sustained growth and future success.

However, implementing a comprehensive sustainability strategy is more than just aligning initiatives under Corporate Social Responsibility (CSR) activities. It demands a significant investment of effort, time, and money. Retailers need to set clear, measurable sustainability goals, track progress, and communicate transparently with stakeholders. Achieving this requires a data-driven approach, involving the collection and analysis of ESG data across all levels of the supply chain. Building a comprehensive data strategy becomes crucial for retailers to effectively incorporate sustainability and achieve tangible, quantifiable impact.

However, adopting a data-backed sustainability strategy is a significant challenge. Asian retailers often have complex and fragmented supply chains, making it difficult to trace products' environmental and social impacts throughout their lifecycle.

While retailers generate vast amounts of data across their operations, the lack of standardised metrics and suitable digital tools hinders the accessibility and integration of this data. Additionally, the quality and accuracy of sustainability data can vary significantly, and integrating it with existing enterprise systems can be technically demanding and costly.

By leveraging data analytics and associated technologies, retailers can gain valuable insights into their sustainability impact, identify areas for improvement, and drive meaningful change toward a more sustainable future.

How To Embrace It?

Retailers can look at sustainability from two lenses—operational and digital. Operational sustainability is about using technology to improve operational efficiencies, thereby reducing your carbon footprint. Meanwhile, digital sustainability aims to reduce the impact of IT operations and lower your associated emissions.

Be it operational or digital sustainability, retailers require data-driven approaches to make informed decisions, improve their environmental and social performance, meet consumer expectations, and comply with evolving regulations. Here are five strategies for retailers to begin their sustainability journey.

1. Build A Strong Data Foundation

Build a strong data platform based on which you can quantify and measure your sustainability goals. This system of insight can also help reduce waste by driving operational efficiencies. Leveraging the collated data, begin with a sustainability audit. Assess your current energy consumption, waste generation, water usage, supply chain practices, etc., to identify areas where you can improve your environmental and social impact.

This audit can serve as a baseline to set tangible sustainability goals. Define specific, time-bound targets for reducing emissions, waste, and water consumption, in alignment with international frameworks like the Sustainable Development Goals (SDGs) or Science Based Targets Initiative (SBTi).

Establishing clear metrics to assess your environmental footprints and social contributions is equally important. This will help track the progress of your sustainability initiatives regularly.

2. Energy-smart, Supply Chain-Savvy, and Zero-Waste

To cut down your emissions, invest in energy-efficient retail and tech infrastructure. Transition to renewable energy sources and energy-efficient buildings to curtail carbon footprints from operations. Similarly, partner with tech companies that can help you set up greener IT infrastructure to reduce your digital carbon footprint.

Optimise delivery routes using smart analytics while adopting greener transportation methods. Utilising digital tools to track and trace products throughout the supply chain can improve transparency and accountability.

You can reduce waste with sustainable packaging materials and recycling programs while partnering with waste management companies for proper disposal and recycling. In addition, efficient waste management practices can lead to substantial cost savings for brands with reduced disposal fees, lower energy consumption, and optimised inventory management.

3. Make Sustainability A Board-Level Agenda

Sustainability requires a cultural shift within organisations. Integrating sustainability into operations, culture, and incentives should now become an imperative for retailers.

Communication across your stakeholders to promote participation is the key. Educate and create awareness, both internally for your employees and externally for customers, helping them to make the right product choices in addition to encouraging (rewarding) them to participate in recycling programs.

4. Partner With Right Stakeholders

Prioritise partnering with suppliers that adhere to eco-friendly sourcing, manufacturing, and transporting while adopting fair labour practices. Work closely with them to iron out any environmental and social issues and ensure ethical and sustainable practices throughout your supply chain.

You can also collaborate with other retailers, suppliers, not-for-profit organisations and government agencies to share knowledge and best practices on sustainability.

5. Community Development

Connect with local communities to address environmental concerns and support sustainable development projects. Invest in philanthropic initiatives and social programs to build strong relationships with stakeholders and create a positive impact on society.

For instance, Fast Retailing, the parent company of Uniqlo, offers humanitarian aid for refugees and children, provides second-hand clothing to the needy, runs educational programs and supports employment in developing countries like Bangladesh.

Promoting social causes and community development can significantly bolster your sustainability agenda, help you create localised solutions, and drive consumer engagement.

By considering sustainability as a growth driver rather than a CSR obligation, retailers can take these actionable steps to contribute to a more sustainable future. Embracing sustainability will enhance brand reputation, increase customer loyalty, and reduce costs through resource optimisation. By tapping the demand for eco-friendly products and evolving with changing consumer value, retailers can drive future sales and secure a leading position in the sustainable retail landscape.