Product analytics · PostHog

PostHog

Open-source product analytics suite combining event analytics, session replay, feature flags, experiments and error tracking.

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PostHog is a product analytics platform aimed at software teams, combining several tools in one suite: event-based product analytics, session replay, feature flags, A/B experiments, surveys, error tracking and a built-in data warehouse. It is open source, with most of the codebase available under the MIT license, and can be run as a self-hosted Docker Compose deployment or used as PostHog Cloud, a hosted version of the same product. Each product area (analytics, replay, flags, error tracking, and others) has its own monthly free usage allowance, after which usage is billed on a pay-as-you-go basis with no credit card required to start. PostHog also includes SQL-based querying, SDKs for common languages and frameworks, and AI-assisted features for investigating product issues. It is commonly used alongside tools such as payment and version-control platforms for correlating product usage with business events.

At a glance

Vendor PostHog
Pricing model Usage-based
Free tier Yes
Deployment Cloud, Self-hosted
Open source Yes (MIT)
Best for Product and engineering teams wanting analytics, experimentation and error tracking in one open-source tool.

Pricing

Every product has a generous monthly free allowance with no credit card required; usage beyond the free tier is billed pay-as-you-go, and the self-hosted version is free and open source.

Plan Price Notes
Free $0/month Per product monthly allowance: 1M analytics events, 5K session recordings, 1M feature flag requests, 100K error tracking exceptions, 1,500 survey responses, 1M data warehouse rows; unlimited team members
Pay-as-you-go Usage-based beyond free tier Per-unit rates differ by product and fall with volume; see the vendor's pricing calculator for current figures

Prices read from the vendor's own page on September 19, 2026. Vendors change prices; check the source before you budget.

Features

  • Event-based product analytics
  • Session replay / recordings
  • Feature flags and A/B experiments
  • Error tracking
  • In-product surveys
  • Built-in data warehouse and SQL querying
  • Self-hostable open-source deployment

Integrations

Profile last reviewed September 19, 2026

Head to head

Alternatives

Mixpanel Cloud-based product analytics platform for event tracking, funnels, retention, session replay, and experimentation. Amplitude Cloud-based digital analytics platform for event tracking, behavioral cohorts, session replay, and feature experimentation. Google Analytics 4 Google's free, event-based web and app analytics platform with machine-learning-driven insights and cross-platform reporting. Matomo Open-source web analytics platform offering full data ownership, available as a hosted cloud service or self-hosted on-premise.

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Terms to know

Event tracking Capturing specific user actions, such as clicks or purchases, as discrete, named pieces of data. Funnel analysis A method for tracking how users move through an ordered sequence of steps toward a goal, and where they drop off. Cohort analysis Grouping customers by a shared starting point, such as signup month, and tracking how their behavior diverges over time. A/B testing A controlled experiment that compares two variants to measure which one produces a better outcome. Retention analysis The study of how many users keep returning to and engaging with a product after their first use. Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions.

Related guides

Behavioral event data, explained How product and marketing teams turn raw clicks and actions into events, and what separates a usable event stream from a noisy one. How to analyze a conversion funnel Building a funnel in SQL, choosing ordered vs unordered steps, and the ways funnels quietly mislead once you trust them too far. How to choose a product analytics tool Product analytics tools split by how events get captured, who reads them, and whether in-app engagement is bundled in — decide those first. How to run a cohort retention analysis How to build a retention cohort table in SQL, read the curve it produces, and avoid the comparisons that quietly mislead.