A standard feed may be enough to display a product, but not enough to power reliable conversational discovery.
Titles, variants, use cases, brands, and useful attributes are often incomplete at the product level.
Without product scoring, it is hard to know which listings are too weak for AI assistants and what to fix first.
Multiplying dedicated exports quickly creates fragile feeds as AI channels evolve.
FeedPlug starts from your existing catalog, scores each listing, and publishes a structured export usable by ChatGPT, Perplexity, and other AI assistants.
Shopify and other sources feed a single layer with titles, descriptions, images, prices, links, availability, and variants.
Product scoring highlights listings that are too weak, too vague, or too poorly structured for conversational discovery.
Brand, type, use cases, variants, price, availability, images, and links are enriched so LLMs can interpret the catalog correctly.
You publish one structured feed without rebuilding a separate flow for every new AI channel.
Product scoring helps you prioritize weak listings instead of reviewing the catalog blindly.
Your catalog stays usable for ChatGPT while still supporting your other commerce channels.
Product data becomes clearer, more consistent, and easier to maintain over time.
You avoid hand-built AI exports every time the catalog changes.
For an AI assistant to understand your offer, a SKU and a price are not enough. The feed must stay interpretable, clean, and rich at the product level.
Use these pages to understand AI distribution, exports, and catalog integrations.
These questions come up often when a brand wants a catalog that is easier for ChatGPT, Perplexity, and other AI assistants to understand.
Not really. A standard feed may be enough to display a product, but not always enough for conversational discovery. You need more structure and clarity at the listing level.
It should include explicit titles, readable attributes, clear use cases, variants, prices, availability, and consistent product links so the model can interpret the offer correctly.
Product scoring helps identify listings that are too weak, too vague, or too poorly structured before distribution. You see which products need to be improved first.
Ideally no. The goal is to start from a clean catalog base and publish a structured export that remains reusable as new AI channels appear.
Request a FeedPlug demo or review the AI assistants page to see how to structure your catalog before distribution.