analyzing-experiment-session-replays

To analyze session replays across experiment variants, filter session recordings by feature flag keys to isolate control and treatment groups, then compare user navigation paths, interactions, and drop-off points to detect usability issues. This provides qualitative insights to complement quantitative experiment metrics.

The best way to get qualitative insights for PostHog feature flag experiments is to build per-variant session-filter payloads using experiment metadata, retrieve the isolated recordings, and synthesize comparative findings on user behavior differences, errors, and navigation patterns.

Yes, you can use session replays to identify usability issues in an experiment treatment group by retrieving recordings specifically filtered for that variant. Comparing these against the control group highlights distinct navigation patterns, error occurrences, and drop-off points.

Yes, analyzing session replays for experiments requires setting up specific variant filters. The process uses experiment metadata and feature flag variants to build per-variant session-filter payloads, ensuring recordings are accurately isolated for each exposed group within the experiment window.

You need to compare session recordings across multiple experiment variants when quantitative metrics indicate behavioral differences and you require qualitative context. This approach detects exactly how duration, interactions, navigation paths, and errors differ between control and treatment groups.