A/B testing

Test changes with statistical significance

A/B tests, multivariate tests, and robust targeting & exclusion rules. Analyze usage with product analytics and session replay.

Screenshot of managing an A/B test in PostHog
  • boosted engagement by 40%

    "Y Combinator uses PostHog's experimentation suite to try new ideas, some of which have led to significant improvements."

    Read the story
  • increased registrations by 30%

    "This experiment cuts that in half to a 30% drop-off – a 50% improvement without a single user complaining!"

    Read the story
  • unthrottled event ingestion from a previous analytics provider, leading to better insights

    "PostHog, which can do both experiments and analytics in one, was clearly the winner."

    Read the story


  • Customizable goals

    Conversion funnels or trends, secondary metrics, and range for statistical significance

  • Targeting & exclusion rules

    Set criteria for user location, user property, cohort, or group

  • Recommendations

    Automatic suggestions for duration, sample size, and confidence threshold in a winning variant

  • Built on Feature Flags

    All the benefits of feature flags with added functionality around stat-sig experiments

  • JSON payloads

    Modify website content per-variant without additional deployments

  • Split testing

    Automatically split traffic between variants

  • Multivariate testing

    Test up to 9 variants against a control

  • Dynamic cohort support

    Add new users to an experiment automatically by setting a user property

Answer all of these questions (and more) with PostHog A/B testing.

  • Does this new onboarding flow increase conversion?
  • How does this affect adoption in Europe?
  • Will enterprise customers like this new feature?

Usage-based pricing

Use A/B testing free. Or enter a credit card for advanced features. Either way, your first 1,000,000 requests are free – every month.

Note: A/B Testing and Feature Flags are currently packaged together and share volume limits.


No credit card required


All features, no limitations





Boolean feature flags
Multivariate feature flags & experiments
Not included
Persist flags across authentication
Test changes without code
Multiple release conditions
Release condition overrides
Flag targeting by groups
Local evaluation & bootstrapping
Flag usage stats
A/B testing
Not included
Group experiments
Not included
Funnel & trend experiments
Not included
Secondary experiment metrics
Not included
Statistical analysis
Not included
Data retention

1 year

7 years

Monthly pricing

First 1 million requests
1-2 million
2-10 million
10-50 million
50 million+


PostHog vs...

Unlimited experiments
Multivariate experiments
Secondary goals
Minimum goals
Duration prediction
Cross-domain experiments
Traffic allocation
Target by location
Target by cohort
Target by user property

So, what's best for you?

Reasons a competitor might be better for you (for now...)

  • No-code experiments or CMS capabilities
    • You'll still need a designer/engineer to create experiments
  • No integration with Google Ads
    • PostHog can't run ad experiments, or target users into an experiment based on an ad variant engagement.

Reasons to choose

  • Integration with other PostHog products
    • Attach surveys to experiments or view replays for a test group. Analyze results beyond your initial hypothesis or goal metric.
  • Automated recommendations for sample sizes and runtime
  • Automatic significance calculator – to help you figure out the winning variant as quickly as possible
  • Robust targeting and exclusion options, including cohorts and location
    • Anything you monitor in analytics, you can target in an experiment

Have questions about PostHog?
Ask the community or book a demo.

Featured tutorials

Visit the tutorials section for more.

  • Running experiments on new users

    Optimizing the initial experience of new users is critical for turning them into existing users. Products have a limited amount of time and attention from new users before they leave and churn.

    Read more
  • How to set up A/B/n testing

    A/B/n testing is like an A/B test where you compare multiple (n) variants instead of just two. It can be especially useful for small but impactful changes where many options are available like copy, styles, or pages.

    Read more
  • How to run holdout testing

    Holdout testing is a type of A/B testing that measures the long term effects of product changes. In holdout testing, a small group of users is not shown your changes for a long period of time, typically weeks or months after your experiment ends.

    Read more
  • How to do A/A testing

    An A/A test is the same as an A/B test except both groups receive the same code or components. Teams run A/A tests to ensure their A/B test service, functionality, and implementation work as expected and provides accurate results.

    Read more

Install & customize

Here are some ways you can fine tune how you implement A/B testing.

Explore the docs

Get a more technical overview of how everything works in our docs.

Meet the team

PostHog works in small teams. The Feature Success team is responsible for building A/B testing.

(Shockingly, this team prefers their pizza without pineapple.)

Roadmap & changelog

Here’s what the team is up to.

Latest update

Feb 2024

Graphs and significance calculation added for secondary metrics

You've been able to add secondary metrics to A/B experiments in PostHog for a while, but we've now added much better reporting around them.

The new graphs and significance calculations will help you determine if there are knock-on effects to your experiments away from the primary metric.

For example, you may test a change to your sign-up flow to improve conversion as a primary metric, but you may also need to know about impact to activation as a secondary metric. Now you can understand both easily!

Up next

  • Feature Success Analysis

    Bringing together different parts of PostHog (flags, replay, surveys) to allow users to better analyse the success of a new feature.

  • Users & recordings linked to feature flags

    We want to make it easier for those who use feature flags to get information on users attached to a particular feature flag, and gather more information on those users' experience through session recordings.


See more questions (or ask your own!) in our community forums.

  • Question / Topic

Pairs with...

PostHog products are natively designed to be interoperable using Product OS.

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If nothing else has sold you on PostHog, hopefully these classic marketing tactics will.


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