In-depth: PostHog vs Statsig

Dec 14, 2023

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, advanced product analytics, session replays, surveys, 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 homepage features

PostHog combines usage, performance, and behavioral data with flags and experiments. Having all these product and data 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, we also enable others to build integrations or other services on top of PostHog, open their own PRs, or give feedback on our roadmap. 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 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

PostHogStatsig

A/B testing

Test changes and analyze impact

Feature flags

Roll out features safely; toggle features for cohorts or individuals

Product analytics

Track events and conversion; analyze user behavior

Dynamic config

Replace hard-coded values in your app with config values

Web session replays

Watch real users use your web app; debug behavior

Mobile session replays

Watch real users use your native mobile app

User surveys

Ask users for qualitative feedback and gather responses

Notebooks

Collaborate on analysis in shareable notebooks

Open source

Code publicly accessible

Data warehouse experiments

Run A/B tests natively on data in your existing warehouse

Experimentation

Both tools enable you to run A/B/n and multivariate 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.

PostHogStatsig

Custom goals

Customize metrics that a test tracks

Secondary metrics

Monitor impact on unrelated metrics

Statistical significance calculation

Calculate if changes make a statistically significant impact

Split testing

Split participants into groups

Multivariate (A/B/n) testing

Test multiple variants of a change

Recommended run time

Calculate the recommended run time for your experiments

Statistics engine

How the results of an experiment are calculated

BayesianBayesian, Frequentist

Holdout testing

Withhold multiple features to measure cumulative impact

Partial

Multi-armed bandit

Optimize tests automatically by allocating traffic to the best performing variant.

Mutually exclusive experiments

Isolate user groups for simultaneous, independent experiments

Bonferroni correction

Includes α correction when tests are being performed simultaneously

  • Holdout testing: It's possible to run a holdout test 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 and boolean flags. This provides greater flexibility in testing and deploying different variations of a feature, making them more suitable for complex rollouts.

PostHogStatsig

Boolean flags

Simple flags returning true or flag

Multivariate flags

Flags with multiple customizable values

Payloads

Flags with string, number, or JSON payloads

Percentage rollouts

Target percentages of a group

Custom targeting

Target users based on user properties, custom contexts

Scheduling

Schedule flags to turn on or off

Environments

Manage flags for dev, staging, prod

Partial

Bootstrapping

Flags available on frontend application load

Early access management

Manage betas, test features

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.

PostHogStatsig

Autocapture

Capture events without manual logging

Dashboards

Combine insights into shareable dashboards

Graphs and trends

Build custom insights and visualizations

Cohorts

Combine users based on properties and events for group analysis

Group analytics

Track metrics at a company level

Funnels

Track users through a sequence of events

Retention analysis

Visualize which users stay, for how long

User paths

Track user flows and where they drop-off

In beta

Correlation analysis

Suggested events and properties that lead to success or failure

Lifecycle analysis

Understand who is dormant, churning, and thriving

Stickiness insights

See how many times users perform an event in a period of time.

Formulas

Use custom formulas to calculate unique insights

Query editor

Write your own queries in SQL

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.

Below is a sample comparison of PostHog and Statsig's integrations. Be sure to checkout PostHog's full list of integrations.

PostHogStatsig

Imports

Import data from source

Exports

Export data to other sources

Zapier

Trigger Zapier automations

Sentry

Connect to Sentry data

Datadog

Capture flag data in Datadog

Slack

Alerts for Slack

Microsoft Teams

Alerts for Microsoft Teams

Security and compliance

Both PostHog and LaunchDarkly 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.

PostHogStatsig

User privacy options

Anonymize users, drop personal data

History, audit logs

Manage and view flag edits and related users

GDPR-ready

Can be compliant with GDPR

HIPAA-ready

Can be compliant with HIPAA

Enterprise

SOC 2

SOC 2 security certification

2FA

Enforce login with two-factor authentication

SAML/SSO

Use SAML or single sign-on authentication

EnterpriseEnterprise

Approvals

Require approvals to change flags

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, and growth engineers.

Companies that use PostHog feature flags and experiments include Y Combinator, Vendasta, and AssemblyAI.

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 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.

Other products, like product analytics and session replay, have separate but similarly structured pricing.

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 50% discount, while startups can sign up for $50,000 of free credit (and a host of other perks) in the PostHog for Startups program.

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