PostHog tells engineering teams what users did. Managani helps product teams decide what to change, tell users, guide adoption, and measure the follow-through.
PostHog is excellent for events, funnels, session replay, feature flags and experiments. Managani is for the product operations that analytics usually triggers: capture the request, plan the change, announce it, guide users to it, and track whether adoption moved.
If your core need is quantitative product analytics — deep event analysis, funnels, cohorts, session replay, feature flags and A/B testing for an engineering team — PostHog is genuinely excellent, and Managani is not trying to be a data warehouse. Plenty of teams will keep PostHog for analytics and use Managani for the customer-facing follow-through.
Sometimes. PostHog is analytics-led; Managani is for the customer-facing work around feedback, roadmap, changelog, onboarding and adoption.
Yes. Managani is open source at v1 (the SDKs are already MIT on npm), and every feature is included — no usage-metered or per-seat tax.
Managani includes product tracking — adoption, friction and drop-off — so you can act on usage. It is not a data warehouse or session-replay tool. If you need deep engineering analytics and experiments, keep PostHog for that; use Managani for the customer-facing loop around it.
PostHog is usage-based (events, recordings) and can climb as you scale. Managani is free during open beta, with every feature included and no per-seat tax.