Skip to content
OpenSourceSoftware.ai
PostHog logo

PostHog

PostHog · Analytics

GitHub stars

40,472
—Awaiting first sync

Awaiting first sync

No measured star history yet

What is PostHog?

PostHog brings the tools a product team uses to understand and improve its product into one place. Analytics, recordings, feature releases and customer feedback share the same data, so each question can be answered without stitching together separate services.

PostHog is an open-source product platform that combines product and web analytics, session replay, feature flags, experiments, surveys and error tracking with a data warehouse. PostHog Cloud is free within monthly limits for each product, and a hobby deployment can be self-hosted.

Core capabilities

  • Analyse product and web traffic with autocapture, funnels and SQL.
  • Watch session replays and heatmaps to see how people really use your product.
  • Roll out changes safely with feature flags, experiments and in-app surveys.

See what users do and why

Product and web analytics capture events automatically or through manual instrumentation, and can be explored visually or with SQL. Session replays and heatmaps show the behaviour behind the numbers, and error tracking links problems to the sessions they affected.

  • Product analytics
  • Session replay
  • Heatmaps
  • Error tracking

Release, test and ask

Feature flags roll changes out to selected users or cohorts, and experiments measure their statistical impact on goal metrics. Surveys collect feedback inside the product, and workflows send messages triggered by product data.

  • Feature flags
  • Experiments
  • Surveys

Work with the data directly

A managed warehouse with more than 120 sources and a SQL editor sits behind the tools, data pipelines send events to other services, and an MCP server lets AI assistants query the data. AI observability captures traces and costs for LLM-powered apps.

  • Data warehouse
  • SQL
  • MCP
  • AI observability

Where it fits

Use cases

  1. 01

    Find where users drop off

    Capture events automatically, build funnels and query the data with SQL to see which steps of sign-up or checkout lose the most people.

  2. 02

    See what went wrong in a session

    Watch session replays and heatmaps alongside tracked errors to understand a confusing page or a bug that customers report.

  3. 03

    Launch a feature to a small group first

    Release a change to selected users with feature flags, measure its effect with an experiment, and ask for feedback with an in-app survey.