How to Get Your Products on ChatGPT, Perplexity & Google AI: The Definitive Guide

Step 1: Submit Your Feed to the OpenAI Product Feed Program

OpenAI accepts product feeds from merchants through its Commerce program. Here's what you need:

Feed Format: CSV, TSV, XML, or JSON. OpenAI accepts updates as frequently as every 15 minutes, so you can keep pricing and inventory near real-time.

Required Fields: Product ID, title, description, price, currency, availability, image URL, product URL, brand, and condition. These are the minimum for your products to be indexed.

Recommended Fields (these dramatically improve recommendation rates): GTIN/UPC, product category (Google taxonomy), detailed product type, additional image URLs, sale price, shipping information, size, color, material, pattern, age group, and gender.

How to Submit: Apply through chatgpt.com/merchants. OpenAI reviews applications and begins indexing feeds within weeks. Shopify merchants are being onboarded automatically — over 1 million Shopify stores are expected to be live by mid-2026.

Pro Tip: Don't just submit your Google Shopping feed as-is. AI-ready titles should be descriptive and natural. Instead of "Running Shoes - Blue - 10" use "Women's Waterproof Trail Running Shoes — Lightweight, Breathable, Blue, Size 10." AI systems understand natural language better than abbreviated keyword formats.

Step 2: Optimize for Google AI Mode and Gemini Shopping

Google's AI Mode (powered by Gemini) is reshaping how Google surfaces products. Instead of traditional Shopping ads, AI Mode synthesizes product information from the Google Shopping Graph — which contains over 50 billion product listings updated 2 billion times per hour.

To appear in Google AI Mode:

Google Merchant Center: Ensure your products are listed in Google Merchant Center with complete, accurate data. Google AI Mode pulls directly from the Shopping Graph.

Universal Commerce Protocol (UCP): Launched by Google and Shopify in January 2026, UCP is an open standard that lets AI agents discover, evaluate, and transact with merchants. Early UCP adopters will have a significant visibility advantage in Google AI Mode and Gemini shopping experiences.

Structured Data on Your Site: Implement Product schema markup (JSON-LD) on all product pages. Google's AI systems use schema to validate and enrich data from your feed. Sites with structured data see up to 30% higher visibility in AI overviews.

Key Optimization: AI Mode queries are 23x longer than traditional search queries. Optimize your product descriptions for natural language queries like "comfortable work shoes for standing all day" rather than keyword strings.

Step 3: Get Featured in Perplexity Shopping Results

Perplexity processes over 400 million questions per month, with shopping as a significant and growing category. Perplexity's shopping experience differs from ChatGPT — it cites more sources per answer (increasing your chances of inclusion) and has the strongest freshness bias of any AI platform.

Perplexity pulls product data from multiple sources: merchant product pages, review sites, editorial comparisons, Reddit discussions, and structured data. To maximize Perplexity visibility:

Content Freshness: Perplexity strongly favors fresh content. Update product pages and related blog content at least quarterly. AI citation rates drop sharply after 3 months.

Review Coverage: Perplexity synthesizes reviews from multiple platforms. Ensure you have active review profiles on your site, Google, and third-party platforms like Trustpilot. Brands with profiles on Trustpilot, G2, or Capterra have a 3x higher chance of being cited.

Editorial Mentions: Perplexity heavily weights editorial product comparisons and "best of" lists. Pursue inclusion in relevant product roundups from industry publications.

Step 4: Enrich Your Product Attributes for AI Matching

This is where most brands fail. Basic product data — title, price, image, description — gets you indexed. Enriched attributes get you recommended. AI assistants need to match your products to specific, nuanced shopper needs, and they can only do that if your data provides the detail they need.

The attributes that matter most for AI recommendations:

Use-Case Descriptions: "Ideal for daily commuters who walk 10,000+ steps" rather than just "comfortable walking shoe."

User Segmentation: "Designed for beginners," "professional-grade," "sensitive skin-friendly" — these help AI match products to specific user profiles.

Benefit Statements: Transform features into benefits. "Merino wool blend" becomes "Naturally temperature-regulating merino wool that stays fresh for multiple wears."

Competitive Context: Help AI understand where your product wins. "30% lighter than category average" or "Only brand in this price range with OEKO-TEX certification."

Compatibility Information: What other products, systems, or standards work with yours? This enables AI to recommend your product within broader shopping contexts.