The Next Omnichannel Shift: When Shopping Happens Inside Chatbots and Feeds

Omnichannel is one of those retail terms that gets repeated so often it can lose its meaning. The underlying idea that customers don’t shop in a single place, and brands win when experiences, messaging and measurement are connected across multiple touchpoints remains though. What has changed is what those channels are.

Until recently, an omnichannel plan could be drawn with two big boxes: physical stores and websites. Today, however, social platforms are becoming storefronts, apps are becoming ecosystems, and large language models (LLMs) are beginning to act as discovery engines, shopping assistants and, crucially, transaction layers.

Conversational commerce

Back in March, Carrefour became the first European supermarket to enable transactions through ChatGPT. An early signal that conversational commerce is moving from concept to capability. It demonstrates a meaningful shift where a customer’s shopping journey can now start and finish inside a conversation. Rather than jumping from search results to a retailer site, a shopper can ask for dinner ideas, refine choices based on dietary needs and budget, and then build a basket without leaving the chat interface.

Brands are realising that they need to show up in these conversations. Retailers and platforms are already positioning themselves for an advertising layer in conversational experiences. Amazon’s new shopping assistant, Rufus, is an example of how quickly “assistant” can become “inventory,” with plans reportedly moving toward paid placements over time. OpenAI also just quietly launched an ads manager for ChatGPT as it builds out its ad business. Meanwhile, consumers are increasingly asking LLMs for recommendations; often phrasing queries as “best for me” rather than “best overall.” That shift from keyword search to intent-rich conversation changes what it means to optimise for discovery.

In practice, people are using LLMs in three recurring ways. Exploration (broad ideas and options), narrowing (shortlists that match constraints) and reassurance (validating a choice before purchase). Brands that understand which stage they are influencing can tailor content accordingly.

The glue to a changing ecosystem

As the makeup of omnichannel becomes increasingly digital, superapps have increasingly been vaunted as the potential glue to hold the whole ecosystem together. But could the LLM become the glue? After all, it is an always-available layer that sits above existing digital channels. Only time will tell. But even if it does, it’s unlikely that brand and retailer apps will vanish any time soon. Apps still deliver unmatched value for loyalty, personalisation, push messaging, saved preferences and post-purchase service. But, social commerce is gathering pace. In fact, some forecasts suggest TikTok Shop could become a top-three global retailer by 2030.

Whilst a modern purchase journey might include a TikTok Shop, Reddit threads, ChatGPT or a brand app, physical retail is not going to disappear either. In fact, we continue to see growth in store footprints, even for digital-native brands. Abercrombie & Fitch is a good example. Its app detects when a customer walks into a store and switches to in-store mode. About an hour after they leave, it sends a push notification asking for feedback, timed so the visit is still fresh. Participation earns loyalty points. A simple loop that connects app, store, and CRM. Shein’s pop-ups in London and Paris, and TikTok Shop experimenting with pop-up formats, are reminders that whilst discovery may happen in-feed, trust and conversion can still be accelerated in-person.

Measurement is the new battleground

As channels proliferate, the hardest problem for brands is connecting the dots across fragmented journeys. When discovery happens in a chatbot, validation happens in a Reddit thread, and conversion happens in an app, traditional last-click reporting becomes less useful and can actively mislead budget decisions.

LLMs introduce an additional layer of complexity. Most brands can only observe LLM-driven traffic when it lands on owned properties. One solution is to treat AI search as a first-class input, just like SEO and onsite search. Teams can then compile the most common AI-driven phrases and prompts in their category and feed them into content and merchandising workflows so the brand’s answers are consistent wherever the customer encounters them.

From an attribution perspective, the goal is to make such journeys visible enough to act on. Start by ensuring analytics can identify traffic coming from LLM, then pair that with incremental measurement approaches so decisions don’t depend solely on click-level signals. Over time, as paid formats emerge in conversational interfaces, brands will need the same discipline they apply to search and social today. Consistent naming, clean landing experiences, and incrementality frameworks that actually hold up will be key.

What e-commerce leaders should do now

For marketeers, the immediate goal isn’t to overhaul every omnichannel plan, but to build readiness. New commerce surfaces such as TikTok Shop, conversational interfaces like ChatGPT, and community spaces like Reddit that shape preferences are adding steps to the journey while compressing the time between inspiration and purchase. The winners over the next few years will be the brands that treat these shifts as both a growth opportunity and a measurement challenge. Showing up with useful answers, creating connected experiences across digital and physical, and building analytics frameworks that can keep pace with how customers are making purchase decisions.