How Replay Vision helps users find (and solve) product problems

Replay Vision is an AI layer for PostHog Session Replay that scans recorded sessions and summarizes behavior according to user-defined prompts; since its August 3 launch, users across 9,488 organizations have created 20,097 scanners. Analysis of custom prompts found four overlapping main uses: bug detection (37%), including pairing replay evidence with Error Tracking; conversion and drop-off investigation (32%), particularly for onboarding, signup, and checkout flows; UX friction and rage-click detection (31%), often using frustration or “stuck” templates; and feature adoption tracking (14%), focused on whether and how newly released features are used. Prompts commonly seek explanations for failed payments, abandoned flows, technical errors, confusing interfaces, and low engagement, with onboarding emerging as a particularly frequent concern across organizations. Most scanners retain their original prompt, but users who revise prompts tend to make them slightly longer and are more likely to keep scanners active after a month, suggesting that short prompts can be useful starting points that benefit from later refinement through wording or filters.

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