--- title: "Walmart put 200,000 products inside ChatGPT's checkout and watched conversion drop by two-thirds." description: "Walmart put 200,000 products in ChatGPT's checkout and conversion dropped two-thirds. Treat AI as distribution, keep transactions on-site." date: 2026-08-15 dateModified: 2026-08-15 author: "Malin Gaertig" canonical: https://marksuite.ai/insights/walmart-chatgpt-agentic-commerce-distribution categories: ["Market data"] publisher: MARK (https://marksuite.ai) --- # Walmart put 200,000 products inside ChatGPT's checkout and watched conversion drop by two-thirds. *Agentic commerce — 2026-08-15* Walmart put 200,000 products inside ChatGPT's checkout and watched conversion drop by two-thirds. It didn't pull out. It rebuilt, keeping the AI app as a place to be found and routing the actual sale back to its own site, where the same shoppers now spend roughly a third more per order than everyone else. At this point the working thesis is that it can serve as a genuine distribution channel while you keep the transaction. Walmart put 200,000 products inside ChatGPT's checkout and watched conversion drop by two-thirds. It didn't pull out. It rebuilt, keeping the AI app as a place to be found and routing the actual sale back to its own site, where the same shoppers now spend roughly a third more per order than everyone else. At this point the working thesis is that it can serve as a genuine distribution channel while you keep the transaction. This is the third in a short series on the different types of agents shaping how, and whether, brands get chosen. The first two looked at the model owners themselves, ChatGPT, Gemini, Claude, Perplexity, and the closed marketplaces, Amazon, Shopee, Lazada. This one is about outside companies building their own agent experiences inside somebody else's AI, using the app-building tools OpenAI opened up to developers in late 2025. Walmart joined as one of the first major retailers on in-chat checkout at launch. It disclosed in March that [conversion inside ChatGPT](/product/ghost-shopper) ran three times worse than Walmart.com. Rather than treat that as a failure, it changed the model entirely: Sparky, Walmart's own assistant, now sits inside both ChatGPT and Gemini, but login, cart and checkout all route back through Walmart's own systems. Walmart's US CEO has said Sparky shoppers spend around 35% more per order than other customers, and Walmart Connect, its advertising arm, grew 46% last year partly on that behaviour. For a retailer this size, the AI app isn't a sales channel to optimise for conversion. It's a new front door that happens to bring in higher-value customers, built deliberately alongside the store and the app rather than instead of them. L'Oréal, announced in June, isn't chasing checkout at all yet. It's doing three narrower things: bringing Maybelline's virtual try-on into ChatGPT, a feature no generic feed could replicate because it depends on L'Oréal's own ModiFace technology; feeding OpenAI verified, structured product data for brands like Lancôme and Kérastah so the model answers from L'Oréal's own information rather than scraped reviews and forum posts; and running paid ad pilots with CeraVe, SkinCeuticals and Garnier at the moment someone's actually asking a shopping question. No results disclosed yet, L'Oréal has called it early days. Neither is a template to copy outright. Both are among the best-resourced companies in their categories, with assets, an owned ad business, a proprietary AR technology, that most brands don't have, and both bets are only months old. But they point the same direction: the commercial case for building here isn't a better checkout. It's controlling what the model says about you, claiming attention and advertising space before it gets expensive, and treating the app as a new distribution channel you shape on your own terms, with the transaction still landing on ground you control. ## Key takeaways - Walmart's Sparky assistant inside ChatGPT and Gemini routes login, cart and checkout back to Walmart.com; the AI app is a distribution channel that brings higher-value customers, not a checkout to optimise. - L'Oréal is controlling what the model says through ModiFace, verified structured product data and in-prompt advertising — without relying on in-AI checkout yet. - The real commercial case is shaping how AI represents your brand, claiming attention before it gets expensive, and keeping the transaction on ground you control. Source: https://marksuite.ai/insights/walmart-chatgpt-agentic-commerce-distribution ## See also (related MARK analysis) - [Walmart's checkout inside ChatGPT converted three times worse than its own website. It opened the door to AI agents anyway.](https://marksuite.ai/insights/walmart-amazon-shopee-ai-shopping-agents-retail-profit) - [What Australia's UCP Checkout Rollout Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/australia-ucp-checkout-rollout-brands-selling-through-ai-agents) - [AI Isn't Just Becoming Another Channel. It's Becoming Part of the Selection Process](https://marksuite.ai/insights/ai-selection-process-retail-arc-summit) - [AI Shopping Isn't a Future Behaviour. Retailers Are Already Measuring It](https://marksuite.ai/insights/ai-shopping-retailers-already-measuring-it) - [Product suite](https://marksuite.ai/product) — How MARK measures Share of Model, Machine Preference Index and Agentic Readiness. - [Framework guides](https://marksuite.ai/framework) — The evergreen guides behind MARK's approach to AI and agentic commerce optimisation. ## About the publisher This analysis is published by MARK (https://marksuite.ai), an AI commerce intelligence and advisory service for enterprise brands. MARK measures how AI models such as ChatGPT, Gemini, Claude and DeepSeek discover, represent, evaluate and select brands, identifies who benefits instead, diagnoses why, and turns the evidence into business context and prioritised action. Written by Malin Gaertig. ## About the author Malin Gaertig is a key person to speak to about Agentic Commerce and how it impacts a company's commercial growth. Malin founded MARK, an AI commerce intelligence and strategic advisory service that combines proprietary technology with 15 years of experience across growth marketing, digital, ecommerce and transformation. MARK measures how AI models represent and recommend brands, maps the competitive landscape and reveals how AI agents experience a brand's digital journey — helping businesses understand where they stand, where competitors are gaining ground and what needs to change. Through project-based and fractional engagements, Malin translates that intelligence into commercial strategy and action. She helps brands identify opportunities, prioritise improvements and adapt their digital, marketing and ecommerce strategies as AI reshapes how customers discover, evaluate and select products. MARK provides the intelligence. Malin brings the interpretation and strategic direction. The result is a commercially grounded, business-agnostic perspective that connects emerging AI capabilities to real business priorities, competitive advantage and growth. Related MARK pages: https://marksuite.ai/score (AI Commerce Benchmark), https://marksuite.ai/product (AI commerce intelligence and measurement), https://marksuite.ai/framework (framework guides). Cite as: MARK — https://marksuite.ai