OpenAI quietly expanded ChatGPT into shopping mode, letting users discover, compare and purchase products directly inside the chat, according to The Information. The change turns an answer engine into an AI shopping assistant with the potential to reroute where consumers start and finish purchases. For merchants this is immediate and practical: update feeds, prepare APIs and optimize for conversational queries so your products appear in ChatGPT shopping recommendations.

Why conversational commerce matters now

Most ecommerce today begins with a search query on a search engine or a marketplace. Conversational commerce embeds product discovery and purchase inside a dialog with an assistant. A user can ask natural language requests like "recommend me a running shoe in size 10" or "is this in stock near me" and get options plus a way to buy without leaving the chat. That shift favors structured data, real time inventory and short persuasive copy that matches purchase intent.

Key features and industry reaction

• Transactional in chat Users can discover, compare and buy directly in ChatGPT, so the assistant becomes a point of sale and a first touch for product discovery.
• Commercial models OpenAI could monetize via ads, referral commissions or merchant partnerships, creating new fee structures to weigh against access to high intent shoppers.
• Competitive impact This moves shopper attention away from traditional search and marketplaces toward AI driven recommendations and zero click style outcomes.
• Platform opportunity Merchants that offer catalog APIs and rich product data can automate conversational sales funnels and appear in AI shopping flows.

What merchants should optimize for

To be visible inside AI shopping and conversational interfaces, focus on three technical and content priorities.

• Product schema and structured data Mark up product title, price, availability, ratings and shipping using product schema so chat assistants parse and present your listings. Use phrases like "in stock [product]", "lowest price [product]" and "[product] customer ratings" in the right fields.
• Catalog APIs and feeds Provide API ready catalogs with up to date inventory and dynamic pricing. That makes your products actionable for an AI shopping assistant that needs real time accuracy.
• Conversational content and transactional keywords Write product descriptions and FAQs in question answer form and include long tail, purchase intent phrases users speak to chatbots. Examples to target: "buy [product] online", "order [product] now", "compare [product A] and [product B]", "chat with a shopping expert", "recommend me a [product] for [use case]" and "add to cart [product]".

Search and SEO implications

Search optimization now includes being discoverable in AI answers and chat summaries as well as traditional results. Prioritize natural language queries and intent buckets, not just raw search volume. Key tactics include:

• Use long tail conversational phrases that mirror how people speak to an assistant.
• Segment content by intent: product pages for purchase ready queries, comparison pages for mid funnel, and FAQs for objections and zero click answers.
• Optimize multimedia and short form video for product discovery since AI assistants reference multiple channels when summarizing options.

Privacy, fees and operations

In chat purchases bring payment and browsing behavior into the assistant environment. Businesses should confirm data use and personalization rules with any platform partner, and plan for potential referral fees or commission models. Operationally, teams will shift toward catalog engineering, prompt design and AI oversight. Smaller merchants must assess if they can afford the engineering work to integrate or if they pursue partnerships to reach the audience.

Practical checklist

• Publish product schema and ensure availability and price fields are current.
• Expose catalog APIs or feeds that support real time inventory and dynamic pricing.
• Create conversational copy and FAQs that answer natural language shopping requests.
• Target transactional intent phrases like "buy now", "order today", "add to cart" and comparison prompts such as "compare" and "which is best for".
• Monitor AI answer citations and zero click visibility to see where your brand appears in chat recommendations.
• Review privacy and fee terms with platform partners before sharing payment or customer data.

OpenAI turning ChatGPT into an ecommerce interface is a step toward agentic AI that completes tasks rather than just answering questions. The immediate move for retailers is simple and strategic: prepare machine readable catalogs, optimize for conversational commerce and prioritize transactional keywords so your products are discoverable and buyable when users ask the chat assistant to help them shop.

Source: Martin Peers, The Information, published 2025-09-30.