How keyword scoring works
Every discovered keyword carries a relevancy score from 0 to 100. The score tells you how closely the keyword matches what your app actually does, independent of the App Store category the app is listed in. You use the score to sort and filter the discovered list, and to set thresholds in your discovery automations.
What the score measures
Relevancy is a semantic score. It compares the meaning of a candidate keyword against what your app is for, rather than whether the two share words. A keyword and a description can share no words and still be a strong match, or share several words and still be a poor match.
The score blends three judgments per keyword:
- How well it fits the app's description. The closer the keyword sits to the ideas expressed in your App Store listing, the higher the score.
- How well it fits the app's specific purpose. A keyword that describes what the app actually does scores higher than one that describes the broader category the app is listed in.
- How far it sits from topics the app is not about. Keywords that drift toward adjacent but commercially wrong subjects are penalised, which keeps the list from filling up with category-adjacent noise.
A candidate needs to do well on the first two and stay clear of the third to end up high in the list.
How the score appears in the product
In the Keyword Discovery tab, each row shows a relevancy score from 0 to 100 alongside a popularity score and a short-tail or long-tail label. You can sort by any of these columns and filter on ranges in the table's filter bar. Inside a discovery automation, you can set minimum relevancy and popularity thresholds so that only keywords that clear the bar are eligible to be added to a campaign.
What the score does not tell you
The relevancy score is about fit, not about commercial outcome. A keyword with a high score matches your app's purpose, but whether it converts for your app, at your bid, in a given market, is a separate question that can only be answered by running spend against it. Treat the score as a filter for relevance, then rely on your campaign metrics to decide which of the relevant keywords are worth keeping.