Automatic extraction
Shopping cards are automatically detected and extracted from ChatGPT responses at no additional cost. When ChatGPT includes product recommendations or commercial information in its response, the scraper parses this data into structured shopping card objects.Shopping cards are included by default in the response structure. You don’t need to set any special parameters to enable them.
Shopping card features
Each shopping card provides comprehensive product information:Comprehensive product data
Product titles, prices, ratings, reviews, images, and merchant information
Multiple offers
Compare prices across different merchants for the same product
Rating citations
Track the source of product ratings and supporting websites
Promotional tags
Identify special offers like “Best price” or promotional deals
Stock information
Check product availability and delivery details
Product images
Access product image URLs for visual display
Shopping card structure
Here’s a sample shopping card from the API response:Product data fields
Each product in a shopping card includes:| Field | Description | Type |
|---|---|---|
title | Product name | string |
url | Product page URL with ChatGPT attribution | string |
price | Current price | string |
featured_tag | Product category or style tag | string |
merchant | Merchant information | string |
imageUrls | Array of product image URLs | array |
rating | Product rating (0-5 scale) | float |
numReviews | Number of reviews | integer |
id | Unique product identifier | string |
offers | Array of shopping offers from different merchants | array |
rating_grouped_citation | Rating source information | object |
Offer details
Each offer within a product provides merchant-specific information:Offer structure fields
Offer structure fields
| Field | Description | Type |
|---|---|---|
merchant_name | Merchant name | string |
product_name | Product name as listed by merchant | string |
url | Offer URL with ChatGPT attribution | string |
price | Offer price | string |
details | Stock and delivery information | string |
available | Offer availability status | boolean |
checkoutable | Whether offer can be checked out directly | boolean |
price_details | Detailed price breakdown (base, total) | object |
tag | Promotional tag (e.g., “Best price”) | object |
Rating citations
Therating_grouped_citation object tracks where product ratings come from:
| Field | Description | Type |
|---|---|---|
title | Source title | string |
url | Source URL | string |
supporting_websites | Array of supporting website references | array |
Use cases for shopping cards
Shopping cards enable powerful e-commerce and market intelligence applications:E-commerce monitoring
Track how ChatGPT surfaces and recommends products to understand AI-driven product discovery. Monitor which products appear in responses to specific queries and how they’re positioned.Price comparison
Monitor pricing across different merchants and marketplaces. Each shopping card includes multiple offers, allowing you to track price variations and identify the best deals.Product research
Extract structured product data for competitive analysis. Analyze product ratings, review counts, and merchant information to understand market positioning.Marketing intelligence
Understand which products ChatGPT highlights in responses to marketing-related queries. Track how your products or competitors’ products appear in AI-generated recommendations.Shopping cards provide attribution URLs that include ChatGPT tracking, allowing you to understand the source and context of product recommendations.