Hotjar vs PostHog

Side-by-side comparison to help you pick the right tool.

HotjarPostHog
TaglineHeatmaps, session recordings, and surveys for understanding user behaviour.Open-source product analytics, session replay, and feature flags.
CategoryAnalyticsAnalytics
PricingFreemiumFreemium
Skill LevelBeginnerDeveloper
PlatformsWeb, BrowserWeb, Browser, Api Headless
Use CasesSmall Team, Solo Indie, Client WorkSolo Indie, Small Team, Side Project
TraitsHas Free Tier, Fast To Set UpHas Free Tier, Self Hostable, Good Api, Active Development, Open Source
Best ForBest for product teams and UX researchers who want to understand why users drop off, not just where.Best for product teams who want deep user insights with the option to self-host and keep all data in-house.

Hotjar

Hotjar is a product experience analytics tool available via web browser that captures where users click, scroll, tap, and move through heatmaps and individual session recordings. Feedback widgets embedded on pages collect open-ended user responses, while survey tools ask structured questions at key moments in the user journey. The Funnels feature visualises where users drop off in multi-step flows. The free tier includes 35 daily sessions recorded and basic heatmaps. Paid plans lift the session limits and add advanced filtering. Hotjar is used by product teams, UX researchers, and marketers who need qualitative user behaviour data to understand why metrics like bounce rate and conversion rate look the way they do, complementing quantitative tools like Google Analytics or Plausible.

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PostHog

PostHog is an open-source product analytics platform that combines event tracking, user session recordings, heatmaps, feature flags, A/B experimentation, and in-app surveys in one self-hostable package. The cloud-hosted version offers a generous free tier of 1 million events per month; self-hosting on your own infrastructure is free with no usage limits. PostHog's autocapture automatically records user interactions without manual event instrumentation. SDKs cover JavaScript, React, Python, iOS, Android, and more. Its all-in-one approach eliminates the need to stitch together Mixpanel, FullStory, LaunchDarkly, and Optimizely. It is the preferred product analytics stack for developer-led companies and privacy-conscious product teams who want full ownership of their user data.

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