Is ChatGPT the New Google Shopping?

The update focuses on discovery, not transaction. ChatGPT now surfaces product grids with images, specs, prices, and reviews. Users can describe what they need, refine their criteria conversationally, and compare options without leaving the interface. Think of it less like a checkout and more like an extremely knowledgeable personal shopper who happens to have access to millions of products. On the infrastructure side, the ACP now powers the discovery phase, not just checkout.

Merchants who connect their catalogs can push structured product data, promotions, and real-time stock or pricing information directly into ChatGPT’s results. Major retailers including Target, Sephora, and Best Buy are already integrated. Shopify merchants get automatic inclusion through Shopify Catalog with no additional setup required. Crucially, OpenAI has stepped back from the idea of native in-chat purchasing. Transactions still happen on the merchant’s own site or app.

The numbers explain why: while 22% of users have purchased directly through an AI interface, 50% have purchased after using AI during their research phase (source: ecommerce nation).

Conversion rates for direct-in-chat purchases were reportedly three times lower in some tests. The opportunity is in influencing the decision, not hosting it.

These two surfaces serve the same consumer need but operate on fundamentally different logic. Understanding the difference is the first step to feeding each one correctly.

Here is the uncomfortable truth both channels share: garbage in, garbage out. Google Shopping has penalized poor feed quality for years. ChatGPT’s model takes that logic further because there is no bid to compensate for weak data. Your product either surfaces or it does not, based entirely on how well-structured and complete your catalog is.

For ChatGPT specifically, visibility depends on:

• Accurate, real-time pricing and availability (stale data means irrelevant recommendations)
• Rich product attributes that map to natural language queries (“waterproof hiking boots under €120”)
• Customer reviews and ratings, which ChatGPT factors into its comparisons
• Clear product categorization that an AI can interpret without ambiguity

Managing this across two channels with different format requirements, update frequencies, and ranking logic is where most e-commerce teams hit a wall. A feed built for Google Shopping’s structured taxonomy does not automatically translate into an ACP-ready catalog for conversational AI.

This is precisely the problem a feed management platform like Lengow is designed to solve. Rather than maintaining separate, manually updated feeds for each new surface, a centralized feed management layer lets you enrich your product data once and distribute it correctly to every channel: Google Shopping, Meta, Amazon, affiliate networks, and increasingly, AI-powered discovery surfaces like ChatGPT.

As the number of channels where consumers discover products keeps growing, the teams that win will not be those who react fastest to each new platform. They will be the ones who built a clean, complete, and adaptable product catalog from the start.

The front door to e-commerce is not changing. It is multiplying. And the key to every single one of them is the same: your data.