User Friction
- User Friction
- The cumulative effort, hesitation, and recovery a user expends to complete an intended task — usually proxied by behavioural signals like rage clicks, dead clicks, scroll U-turns, form abandonment, and dwell time on a stuck state.
Detailed Explanation
No single behavioural signal tells you a user is struggling. A rage click on its own might be enthusiasm; a long dwell might be reading; a U-turn might be a deliberate back-navigation. Friction is what you get when you aggregate these signals at the session and target level and weight them by recency and severity. A useful friction score is comparable across sessions, comparable across releases (so you can A/B it), and decomposable — when the score spikes, you should be able to point at which signal contributed and on which element. Most teams over-index on one signal (heatmaps of clicks, rage clusters) and miss the compounding pattern, which is where the real product damage lives.
How Relyv helps: Relyv computes a per-session friction score from rage clicks, dead clicks, scroll U-turns, form abandonment, console errors, and failed network requests in the same time window. Sessions are ranked by score in the triage inbox, so the highest-friction users surface first. Each contributing signal is shown next to the score with a deep link to the exact timestamp in the replay — so the score is auditable, not a black box.