Retailers chase AI shopping traffic while guarding customer data

Retailers are racing to appear in chatbot results as shoppers increasingly turn to ChatGPT and Google Gemini for product recommendations, but they're resisting efforts to cede the customer data that underpins online sales. For AI builders, this signals a shift in how product visibility is earned and a new battleground over data ownership in e-commerce.

What happened: Retailers optimize for chatbot queries

Growing online traffic from AI platforms has pushed retailers including Walmart, Ulta Beauty, and Wayfair to update their websites so their products rank highly in chatbot searches. According to Adobe, AI traffic to U.S. retail sites jumped 393% in Q1, with visitors converting at meaningful rates. The mechanics differ from traditional search: a chatbot answers a detailed question rather than ranking pages against keywords and links, which forces retailers to rewrite how products are described and how a brand gets found at all.

Why AI builders should care: A new optimization layer

This is not just a trend for e-commerce teams. For anyone building AI-powered shopping assistants, product recommendation engines, or agentic commerce tools, the retailer response matters. If brands optimize their content for ChatGPT and Gemini, your AI agent will surface more accurate, structured results. If they resist by building their own AI experiences, the data landscape fragments. The shift demands that AI teams think about how their models retrieve product information and whose data they rely on.

Practical implications: Data ownership becomes the core tension

Retailers want the AI traffic, but they worry about losing control over customer relationships. The coverage notes that agentic commerce is growing fast, but retailers are concerned about ceding customer data and are pushing to strengthen their own AI-powered site experiences. This creates a strategic fork: either retailers cooperate with AI platforms and share data, or they invest in proprietary AI shopping tools that keep customers on their own sites. For product teams building retail AI, the choice of data source and integration model will determine whether you get rich, real-time product data or walled-off content.

Caveats and unknowns

This reporting is based on a Reuters article and associated coverage, which describes a trend rather than confirmed outcomes for every retailer. The scale of AI shopping traffic growth (393% in Q1) comes from Adobe analytics, which may not capture all traffic sources. It is also unclear how different retailers will balance visibility and data sharing, and the landscape could shift quickly as AI platforms update their indexing and recommendation policies. Not all retailers will respond the same way, and the data privacy implications remain unresolved.