Depth of Use

Depth of use shows how much a user does within each feature: the average number of interactions per feature engaged, as opposed to how many features.

Depth of use is the pair of breadth of use and is incomplete without it: breadth says how many features a user opened, depth says how much repetition and continuation there was within each. This split matters because two products with the same events-per-user can behave completely differently: one a user working a single feature deeply, the other a user touching several features shallowly. The calculation trap is the denominator: dividing total events by all features the product offers gives a meaningless number; the denominator must be the features that same user actually used. High depth usually signals real value and dependence, but if it comes from forced repetition of a task (say, several attempts at an action that fails the first time) it can indicate friction rather than satisfaction.