5 Things Retailers Need to Know About Query-Driven Shopping

For years, online shopping has followed a familiar path: search, browse, compare, and purchase. Today, however, retail journeys are undergoing a quiet but powerful shift. Consumers are increasingly relying on IA chatbots and assistants to guide their decisions.

Here are the five shifts reshaping retail as AI moves into the heart of the shopping journey.

1. Shopping now starts with a question

Today’s consumers don’t begin their journey with a search. They start with questions like: what should I buy for my teenage nephew who likes anime and cycling? What’s a thoughtful gift for grandparents who live far away? Can you recommend fun, office-appropriate presents under $10?

As AI chatbots train consumers to pick products via prompts, shoppers are increasingly relying on AI to interpret their needs and recommend products. While AI-assisted shopping still represents a relatively small share of traffic, habits are shifting quickly, with AI traffic to U.S. retailers more than quadrupling between January and July 2024.

2. AI is moving closer to the transaction

The transition to a conversational sales funnel is accelerating, and the first impression a chatbot provides for a product now matters as much as any listing or homepage. In the US, this transition is moving even faster thanks to emerging in-chat purchasing systems, such as Instant Checkout within ChatGPT, which enables single-item purchases from merchants on selected platforms. 

Even when a purchase happens on a retailer’s site, there’s a high chance the recommendation that drove it came from AI. This evolution means AI is no longer just a channel, but an active participant in commerce.

3. Retail visibility is being redefined

Retailers are no longer solely vying for visibility on Google or online marketplaces. They compete to be favorably interpreted by answer-generating machines. 

In response, they are exploring new ways to influence how their products are interpreted and surfaced by AI systems. SEO has long been a game of cat and mouse between retailers and ever-changing algorithms. Generative engine optimization (GEO) follows a similar pattern, aiming to guide AI systems much like SEO once influenced search rankings. But with LLMs essentially acting as black boxes, its fundamentals remain largely untested.

4. Product data is now the backbone of AI-driven commerce

Online retailers can’t simply drop a chatbot into their website or app and hope for the best. Structured data helps systems explain products and support comparisons, while up-to-date pricing, stock, and reviews enable recommendations. Messy product tagging and descriptions can create gaps that AI models fill with approximations drawn from external sources, beyond a brand’s control.  Retailers investing in strong catalog hygiene can enhance the shopping experience, whether or not AI is involved.

This shift is accelerating further as AI becomes more embedded in the transaction. Open standards like OpenAI and Stripe’s Agentic Commerce Protocol enable AI agents to interact directly with ecommerce systems — from checking stock to completing purchases and applying loyalty points. As a result, more retailers are revisiting product taxonomies to improve consistency and ensure attributes are intelligible to both humans and AI. 

5. Owning the customer relationship is more important than ever

The risk retailers face with end-to-end AI shopping mirrors what open web publishers are already experiencing: reduced referral traffic and disintermediation from audiences. This means losing not only eyeballs and traffic, but also the first-party data such visitors generate. 

This makes it pivotal for retailers to find ways to foster direct consumer interactions and source independent audience intelligence.

Query-based shopping ultimately puts customer motivations at the center of the journey. Retailers that truly understand their audiences can position products more effectively, aligning with intent and answering needs directly within their content. Change is accelerating, but the path is clear: test, learn, and build lasting connections — or risk falling behind.

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