Behavioral Data Review — Page 2

Behavioral patterns predict outcomes better than job titles or company size.

Login frequency masks whether customers actually use your product or are quietly leaving.

Starting cohorts at signup masks activation failures that look like product problems.

Separate activation from retention to diagnose whether users can't find features or won't use them.

Standard stickiness metrics hide collaborative feature failures in multi-seat accounts.

Individual-level curves reveal why users leave, not just that they do.

Habituation requires repeated use over time, not just one-time activation.

Whole-product and feature activation measure different things and need different thresholds.

How to measure feature discovery in ways that actually reveal what's broken.

Measure adoption only among customers who could actually use the feature.