Shopping is moving into assistants, and assistants read product content differently than people do. The Feedmind Score measures one thing: how well a catalog can be read, understood and answered from by an AI agent. We publish the method in full, because a score nobody can audit is a score nobody should trust.
A category median is the anonymized aggregate of every store we have scanned in that category. No individual shop’s data is exposed by the median, and a category needs at least 20 scanned stores before we publish one. The named competitor is a public scan of a public storefront, run with exactly the same rules as yours — if someone scans you, you appear in their comparison the same way.
It is not a guarantee of placement. No one outside the model providers can promise that a change makes an assistant recommend you, and anyone who does is selling something.
It is not attribution. We do not measure traffic or revenue from assistants; we measure whether your content can be used at all. Readability is a precondition, not a conversion metric.
It is not a ranking. Two stores with the same score are equally readable; which one gets named depends on price, availability, reviews and the shopper’s question.