# PostHog vs Statsig in-depth tool comparison - [ ![](https://res.cloudinary.com/dmukukwp6/image/upload/c_scale,w_50/Lior_51d29d101a) Lior Neu-ner](/community/profiles/28754.md) Dec 14, 2023 - [Comparisons](/blog/comparisons.md) PostHog and Statsig both offer A/B testing and feature flags, but they're different in two important ways: - **Statsig** is a dedicated testing platform that offers advanced statistical methods for running tests. It's ideal for data scientists and growth teams in large enterprises who need to conduct complex A/B testing. - **PostHog** is an all-in-one platform for engineers and product teams who want a more straightforward approach to experimentation. In addition to A/B testing, it offers [feature flags](/feature-flags.md), advanced [product analytics](/product-analytics.md), [session replays](/docs/session-replay.md), [surveys](/surveys.md), and more. This post compares their platforms, experimentation features, pricing, and more. ## How is PostHog different? ### 1\. We're an all-in-one platform PostHog brings together all the tools engineers need for testing, releasing, and measuring the success of new features. Feature flags and A/B testing are only part of a suite of tools PostHog offers. PostHog combines usage, performance, and [behavioral data](/product-engineers/behavioral-analytics.md) with flags and experiments. Having all these dev tools together enables you to do better analysis of shipped features and make better decisions about what you are building next. ### 2\. We're open source and transparent PostHog is built with transparency at its core. Not only do we work in the open and give full access to [our source code](https://github.com/PostHog/posthog), we also enable others to [build integrations](/docs/apps/build.md) or [other services on top of PostHog](/blog/how-we-built-an-app-server.md), open their own PRs, or give feedback on [our roadmap](/roadmap.md). PostHog's open app framework makes it easy to integrate internal tools, an advantage closed-source products like Statsig can't offer. ### 3\. We ship weirdly fast We update [our changelog](/changelog.md) with a recap of new features every week, and often there’s even more in beta testing. We work hard to keep PostHog on the cutting edge and respond quickly to feedback from our users. ## Comparing PostHog and Statsig ### Platform Statsig [**Experiments**](/experiments.md) Run statistically rigorous A/B/n tests and validate ideas with confidence ✓ ✓ [**Feature Flags**](/feature-flags.md) Control feature access with precision and safely roll out changes ✓ ✓ [**Product Analytics**](/product-analytics.md) Track usage, retention, and feature adoption with comprehensive analytics ✓ ✓ [**Web Analytics**](/web-analytics.md) Privacy-focused web analytics with real-time data and no sampling ✓ ✓ **Remote config** Replace hard-coded values in your app with remotely configurable parameters ✓ ✓ **Web app recordings** Capture recordings from single-page apps and websites ✓ ✓ **Mobile app recordings** Capture recordings in iOS and Android apps ✓ ✗ [**Surveys**](/surveys.md) Collect product feedback with no-code surveys and customizable targeting ✓ ✗ **Notebooks** Collaborate on analysis in shareable notebooks ✓ ✗ **Open source** Audit code, contribute to roadmap, and build integrations ✓ ✗ **Data warehouse experiments** Run A/B tests natively on data in your existing warehouse Beta ✓ ### Experimentation Both tools enable you to run [A/B/n](/tutorials/abn-testing.md) and [multivariate](/product-engineers/what-is-multivariate-testing-examples.md) tests, set custom goals, and calculate statistical significance, but: - **Statsig** offers some more advanced testing techniques, such as multi-armed bandit, mutually exclusive, and holdout tests. It also lets you choose between Bayesian and Frequentist engines, and supports Bonferroni correction. - **PostHog** provides a more intuitive user interface and simpler setup process, making it ideal for teams who prefer a more straightforward approach to experimentation, and tight integration with its other powerful tools. Statsig **Custom goals** Define your own goals and metrics to track ✓ ✓ **Secondary metrics** Monitor impact on unrelated metrics ✓ ✓ **Statistical significance** Automatic calculation of statistical significance with configurable confidence levels ✓ ✓ **Split testing** Split participants into groups ✓ ✓ **Multivariate (A/B/n) testing** Test multiple variables simultaneously to find optimal combinations ✓ ✓ **Recommended run time** Automatically calculate the recommended run time and sample size ✓ ✓ **Statistics engine** How the results of an experiment are calculated Bayesian or Frequentist Bayesian, Frequentist, or Sequential with Bonferroni correction **Holdout testing** Reserve a group of users who do not see any changes, so you can measure long-term impact against a true baseline ✓ ✓ **Multi-armed bandit** Optimize tests automatically by allocating traffic to the best performing variant ✗ Pro **Mutually exclusive experiments** Isolate user groups for simultaneous, independent experiments ✗ ✓ - **Holdout testing:** It's possible to run a [holdout test](/tutorials/holdout-testing.md) across multiple A/B tests in PostHog. However, the process is more manual than Statsig's, which has built-in functionality to do this. ### Feature management While both offer the core features you need, Statsig's feature flags are boolean-based, while PostHog supports [multivariate flags with JSON payloads](/docs/feature-flags/creating-feature-flags.md#served-value) *and* boolean flags. This provides greater flexibility in testing and deploying different variations of a feature, making them more suitable for complex rollouts. Statsig **Boolean flags** Simple on/off flags to enable or disable features ✓ ✓ **Multivariate flags** Test multiple variants of a feature in a single flag ✓ ✓ **Payloads** Pass structured data (strings, numbers, or JSON objects) to variants for dynamic configuration without code changes ✓ ✓ **Percentage-based rollouts** Roll out features gradually to a percentage of users ✓ ✓ **Custom targeting** Target features based on user properties and attributes ✓ ✓ **Flag scheduling** Schedule flags to turn on or off automatically at specified times ✓ ✓ **Multi-environment support** Use the same flag key across PostHog projects for local development or staging Partial ✓ **Bootstrapping** Make flags available immediately on page load without waiting for API response ✓ ✓ **Early access feature opt-in widget** Allow users to opt in or out of specified features with a built-in widget or custom UI ✓ ✗ **Remote config** Replace hard-coded values in your app with remotely configurable parameters ✓ ✓ ### Product analytics Both PostHog and Statsig offer the functionality you expect from product analytics tools, such as dashboards, graphs, and funnels. However: - **PostHog** provides deep insights into how users are interacting with your product. It includes features such as lifecycle, stickiness, correlation, and retention analysis. - **Statsig** does provide some additional insights, such as retention analysis, but its main focus is to use product analytics to set up metrics to run A/B tests on. Statsig **Autocapture** Capture events without manual tracking ✓ ✓ [**Dashboards**](/dashboards.md) Combine insights into shareable dashboards ✓ ✓ [**Graphs & trends**](/trends.md) Build custom insights and visualizations ✓ ✓ **Cohorts** Combine users based on properties and events for group analysis ✓ ✓ [**Group analytics**](/profiles.md) Track metrics at a company and account level ✓ ✗ [**Funnels**](/funnels.md) Track users through a sequence of events to find drop-off and improve conversion ✓ ✓ [**Retention**](/retention.md) Track user retention over time to understand how long users stay with your product ✓ ✓ [**User paths**](/user-paths.md) Understand how users navigate through your product and where they get stuck ✓ Beta **Correlation analysis** Automatically identify significant factors that impact conversion ✓ ✗ [**Lifecycle**](/lifecycle.md) Track user lifecycle to understand how users interact with your product ✓ ✗ [**Stickiness**](/stickiness.md) Track user stickiness over time to understand how long users stay with your product ✓ ✓ **Custom formulas** Perform calculations and math operations on multiple event series ✓ ✓ **SQL query editor** Write SQL queries directly against your data without a separate data warehouse ✓ ✓ ### Integrations Both PostHog and Statsig have a range of integrations that enable them to import, export, enhance, and make use of data, but PostHog being open source means you can [create your own integration](/docs/apps/build.md). Below is a sample comparison of PostHog and Statsig's integrations. Be sure to checkout [PostHog's full list of integrations](/cdp.md). Statsig **Import from data warehouses** Import data from third-party sources like Postgres, S3, GCS, Stripe, HubSpot, and more ✓ ✓ **Batch exports** Schedule data exports to S3, Snowflake, BigQuery, and more ✓ ✓ **Realtime event streaming** Send events to Slack, webhooks, and other tools as they happen ✓ ✓ **Zapier** Trigger Zapier automations ✓ ✗ **Sentry** Send and receive data from Sentry ✓ ✗ **Datadog** Send feature flag and event data to Datadog ✗ ✓ **Slack** Alerts and notifications for Slack ✓ ✓ **Microsoft Teams** Alerts and notifications for Microsoft Teams ✓ ✓ ### Security and compliance Both PostHog and Statsig enable companies to remain secure and compliant with privacy regulations. Companies can customize the levels of user privacy related to these platforms to their needs. Statsig **User privacy options** Anonymize users, drop personal data ✓ ✓ **History and audit logs** Manage and view edits and related users Scale ✓ **GDPR-ready** Can be compliant with GDPR ✓ ✓ **HIPAA-ready** Can be compliant with HIPAA ✓ Enterprise **SOC 2 Type II** SOC 2 security certification ✓ ✓ **2FA** Enforce login with two-factor authentication ✓ ✓ **SAML/SSO** Use SAML or single sign-on authentication Scale Enterprise **Flag approvals** Require approvals to change flags Scale ✓ **Flag permissioning** Control who can edit and modify flags ✓ ✓ ## Frequently asked questions ### Who is PostHog useful for? PostHog is built for startups and their engineers. It provides all the tools startups need to build successful products. The people who find PostHog most useful are founders, [product engineers](/product-engineer/what-is-a-product-engineer.md), and growth engineers. Companies that use PostHog feature flags and experiments include [Y Combinator](/customers/ycombinator.md), [ElevenLabs](/customers/elevenlabs.md), and [ResearchGate](/customers/researchgate.md). ### Who is Statsig useful for? Statsig is for teams that require advanced experimentation capabilities and more sophisticated statistical methods. It's ideal for data scientists and growth teams who need to conduct complex A/B testing. Teams that frequently run multiple experiments on the same surface concurrently will appreciate Statsig's ability to handle mutually exclusive experiments and implement Bonferroni correction. ### Can I migrate from Statsig to PostHog? Yes. See our [Statsig to PostHog migration guide](/docs/migrate/statsig.md) for more. ### How much does PostHog cost? Feature flags and experiments are free for up to 1M requests per month. Beyond that, it costs $0.0001/request (or $1 per 10,000 requests). There are discounts for high-volume users, non-profits, and [startups](/startups.md). Other products, like product analytics and session replay, have separate but similarly structured [pricing](/pricing.md). ### How much does Statsig cost? Statsig is free up to 1M requests per month. Thereafter, it's $150 per month for up to 5 million metered events, and then $50 per every 1 million events thereafter. ### Does PostHog offer discounts for nonprofits and startups? Yes, PostHog offers both. Nonprofit organizations can contact our team and are usually eligible for a discount, while startups can sign up for $50,000 of free credit (and a host of other perks) in the [PostHog for Startups program](/startups.md). > PostHog is the leading platform for building self-driving products. With a full suite of developer tools – [AI observability](/ai-observability.md), [product analytics](/product-analytics.md), [session replay](/session-replay.md), [feature flags](/feature-flags.md), [experiments](/experiments.md), [error tracking](/error-tracking.md), [logs](/logs.md), and more – PostHog captures all the context agents need to diagnose problems, uncover opportunities, and ship fixes. A [data warehouse](/data-stack.md) and [CDP](/cdp.md) tie it all together, unifying that context into one source agents can read across. You can steer it all from [Slack](/slack.md), [the web app](/ai.md), the desktop ([PostHog Desktop](/desktop.md)), or your own editor via [the MCP](/mcp.md). ### Community questions Ask a question