What Fabric does
How Fabric measures your brand in AI answers and improves your product content.
Fabric measures how often AI assistants recommend your brand, and improves the product content they read. When someone asks ChatGPT, Perplexity or Gemini for a recommendation, the assistant answers from the product content it can find and understand.
Measurement and enrichment
Measure
An AI Visibility Assessment asks the AI channels real shopper questions in your categories. It counts how often your domain appears in the answers, and how the answers describe it.
Improve
Enrichment fills in the attributes an AI assistant uses to match a product to a shopper's question: material, fit, use case, and answers to the questions buyers ask.
Content depth
An assistant can only recommend a product it can describe. Two catalogs selling the same jacket perform differently if one records the fill weight, temperature range and cut, and the other records only a title and a price.
That difference is content depth, and Fabric is built to increase it. Visibility is what Fabric measures; content depth is what enrichment changes.
How Fabric scores your catalog
Importing a catalog into Fabric produces a Catalog Quality Scorecard. It is computed once per import, grades the content you have today, and rolls up into two scores:
| Score | What it covers |
|---|---|
| Structural Catalog Score | Whether the basic fields are present and well formed: titles, descriptions, categories, identifiers, pricing, imagery, variants. |
| AI Answerability Score | Whether a product has the detail an assistant needs: attributes, FAQ and knowledge content, and how easily a model can read the data. |
Fabric reports the two scores separately. A catalog with complete basic fields can still give an assistant nothing to answer with. This is common, and you only see it when you measure both.
Terms used in these docs
These terms have a fixed meaning throughout the docs.