To help suppliers understand how they can capitalise of this fast growing channel, IGD sits down with eStore Brands.
IGD’s latest UK grocery channel forecasts for 2026-2031 reveal that online will be the fastest-growing channel in the market over the next five years. Continued investment in technology, automation and fulfilment infrastructure will help retailers and suppliers unlock greater operational efficiencies, creating a stronger pathway to profitable growth.
Within online grocery, quick commerce is set to outperform the wider channel, making it the fastest-growing sector in UK grocery retail.
By 2031, quick commerce is forecast to account for 15% of total online grocery sales, driven by significant investment from retailers to expand geographic coverage, extend operating hours and cater to a broader range of shopping missions.
As retailers continue to enhance convenience and speed for shoppers, quick commerce is expected to become an increasingly important part of the grocery landscape.
To help suppliers understand how they can capitalise of this fast growing channel, IGD’s Toby Pickard, Retail Futures Senior Partner sat down with Francis Nicholas, VP Strategy at eStore Brands to hear how brands that are selling through online retailers, can utilise technology to improve product visibility, increase conversion, and grow sales.
Q: The digital shelf has become every bit as important as the physical shelf. What are the biggest opportunities retailers and brands are still missing online?
Many brands and retailers balance the implementation of commercially-driven merchandising actions with those grounded in shopper insights. The biggest missed prize is eCategory management. On a typical online grocery retailer, 70% - 80% of the products on any search results page might be organic, yet much of the attention and budget flows to the paid slots above them. What should practitioners focus on?
Double-down on the importance of master product data integrity. Treat product data as commercial infrastructure — structured, complete and readable by both shoppers and the AI systems increasingly reading the page.
Use digital shelf signals to steer range, space, pricing and media decisions, not just to report compliance after the fact.
Maximise the impact of organic and "super generic" occasion terms. Words like breakfast, lunch, dinner and BBQ can often drive hundreds of thousands or even millions of search impressions per month with a large retailer, but they are usually dominated by literal keyword matches rather than curated, basket-building assortments. When eStore worked with a client to leverage ASDA Xpert data, the client was able to provide insights to ASDA including suggestions on how to optimise for a high-volume grocery search term. ASDA agreed to these suggestions which resulted in a strong increase in basket adds and accelerated category growth.
The opportunity is not necessarily another technology wave. It is applying the category management discipline that already exists in physical stores to the online space - at scale.
Q: What are the biggest mistakes suppliers still make when it comes to product content, search visibility, and conversion?
Suppliers still often lose growth opportunities to avoidable basics — and in an increasingly AI-mediated environment those gaps are becoming increasingly obvious:
Inconsistent, incomplete or unstructured product data that means that a Product Detail Page doesn’t have the minimum required titles, packshots, descriptions and other important information such as ingredients. This can also break search relevance and confuse any LLM or retailer assistant trying to "read" the page.
Chasing keywords and retail media bids while ignoring category context. Sponsored slots dominated by one brand can benefit that brand and retailer revenue but degrade the shopper experience and category growth.
Treating content as a one-off launch task instead of an always-on test-and-learn engine. Amazon's Alexa for Shopping favours clear writing that answers real shopper questions over pages stuffed with keywords.
With up to 80% of users already relying on AI-generated summaries for High Purchase Value, Low Purchase frequency categories, "almost right" content now risks becoming a literal defect in how your product gets understood and recommended. This will reapply to low purchase value, high purchase frequency categories in time.
Q: With search, content, availability and retail media all competing for attention, where should retailers and suppliers focus first to deliver the greatest commercial impact?
With search, content, availability and retail media all competing for budget, the highest-ROI sequence is anchors back to a focus on the classic Brilliant Basics:
Fix availability and data quality first. If you are not in stock and not correctly ranged in the right categories and locations, every other investment is compromised — and the retailer's assistant will pass you over regardless.
Invest in clean, structured, enriched content that can power organic search, retail media relevance and AI discovery simultaneously.
Then scale your retail media — with guardrails. Sponsored slots should complement the organic category story, prioritising new launches, promotions and trade-up, not just buying visibility.
This turns digital shelf optimisation from experimentation into a measurable sales and profit driver, with positive commercial benefit to both retailer and supplier.
Q: AI is rapidly changing how shoppers discover products online. How should retailers and brands adapt to remain visible and relevant in an AI-driven shopping journey?
For optimised LLM search visibility, ensure that your product content is created using natural, benefit-driven language. This example of a New Zealand wine description has been optimised for traditional organic search: “A cool-climate varietal featuring pronounced herbaceous aromatics, high structural acidity, and distinct tasting notes of gooseberry, capsicum, and passionfruit. Fermented in stainless steel to preserve the primary fruit profile. Recommended pairing: fresh oysters or chèvre."
This could be optimised to win the LLM's recommendation, by rewriting the copy to explicitly answer the conversational ways real people describe their hosting habits and taste preferences: "A crisp, incredibly refreshing dry white wine from New Zealand that is perfect for summer garden parties and barbecues. It delivers bright, zesty fruit flavors without any of the heavy, oaky taste you get in some white wines, making it a guaranteed crowd-pleaser that is remarkably easy to drink. It's an affordable, premium-tasting choice to chill in the fridge for a casual weekend get-together or to pair with light chicken dishes and salads."
Another real shift is not that shoppers use chatbots though - it is that retailers are building their own AI assistants inside their shops, controlling what those assistants can see and keeping rival AI out. The conversation moves inside each retailer, on that retailer's terms. How could you optimise in this world:
Optimise for machines as well as people: rich attributes, clear specifications, use cases and compliant imagery that assistants can reliably parse and cite. As an example, Amazon's assistant draws on listings, reviews, Q&A and structured attributes.
Brands should look to be optimised within each retailer's assistant individually — a brand can be visible in one and invisible in another because each reads products differently. Showing up in a general chatbot does not help when Amazon as an example has blocked outside agents.
Make AI search performance a core shelf metric. Alexa for Shopping already had more than 300 million users in 2025, and those shoppers are around 60% more likely to buy. Over 26 million French ChatGPT users can now tell the ChatGPT app, "Give me three dinner ideas for a family of four under €20." The AI seamlessly opens Carrefour’s live catalog, pulls available inventory from the user's nearest local store, builds the virtual basket, and passes the user straight to Carrefour.fr for a one-click checkout
The winners will be brands whose products are not only discoverable to people, but compatible with both the LLMs and the retailer-owned agents fast becoming their primary shoppers. Will the New Line Forms of the future require retailer-specific AI assistant friendly content to be included?
Q: Many retailers talk about creating a seamless omnichannel experience. Where do you see the biggest disconnect today between the physical shelf and the digital shelf?
The rhetoric is seamless; the execution is not. The largest disconnect is that physical and digital decisions are often still made on different data, by different teams, with different incentives.
Store space, pricing and promotions might be planned on historical store data, while real-time digital demand, cross-shop behaviour and local availability often sit in separate tools and teams.
The disciplines diverge: physical retail allocates space by category strategy and shopper demand, but online those guardrails largely do not exist, so an algorithm surfaces the cheapest keyword match rather than a curated fixture.
Shoppers see one brand but meet different packs, claims, reviews and imagery between the aisle and the PDP.
Closing the gap means treating digital shelf analytics and location-based insight as the common language for omnichannel category management — not just an eCommerce report.
Q: Looking ahead to 2030, how do you see online grocery evolving, and what opportunities will that create for retailers, suppliers, and shoppers?
By 2030 online grocery will be less about "ordering from a website" and more about ambient, agent-led replenishment across store, quick commerce and scheduled delivery. In leading European markets, online could reach 18–30% of the food-at-home market, with the UK forecast at around 26%. It’s predicted that agentic commerce could orchestrate $3–5 trillion of consumer spend globally.
For retailers, the prize is algorithmic loyalty: owning the assistant and data layer that decides which basket gets built. That is why retailers like Walmart keep the catalogue, basket and checkout on their own systems even when their customer-facing solution Sparky appears inside ChatGPT.
For suppliers, growth shifts from winning individual clicks to also winning "default" status in agents' recommendation sets and retailer category strategies — powered by superior data, availability and eCategory management.
For shoppers, grocery becomes more predictive, personalised and inspiration-led, provided consent and fairness are handled transparently. Today Europeans are largely using AI to browse but not yet to buy — the execution gap is exactly where the next few years will be won.
The real disruption is not that more grocery moves online, but that more of the online journey is delegated to agents — and the winners will be those already building for an agent-read shelf today.
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