Feature Stickiness

Feature stickiness shows, of the users who used a feature in a month, what share use it daily too: the feature's daily active users divided by its monthly active users.

Feature stickiness is the whole-product stickiness logic (the DAU-to-MAU ratio) narrowed onto one feature to say how much that feature has become a daily habit. Its value runs from zero to one and its reading depends on the feature's nature: for an inherently daily feature (a feed, notifications) high stickiness is expected, but for one naturally used monthly (billing, settings) low stickiness is not bad at all. So comparing stickiness across two features of different natural frequency misleads; this metric works better for a feature's trend over time than for ranking features side by side. The denominator trap is that both sides of the ratio must be users of that feature, not all product users; taking whole-product MAU as the denominator artificially shrinks feature stickiness.