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 A/B testing to try new ideas, which has led to significant improvements."

    Read the story
  • increased registrations by 30%

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

    Read the story
  • switched from Mixpanel for a leaner stack

    "I feel like, every single week, we discover something new that makes a difference."

    Read the story

Features

  • 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.

Free

No credit card required

All other plans

All features, no limitations

Requests

1,000,000/mo

Unlimited

Features

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

1 year

7 years

Monthly pricing

First 1 million requests
Free
Free
1-2 million
-
$0.000100
2-10 million
-
$0.000045
10-50 million
-
$0.000025
50 million+
-
$0.000010

FAQs

PostHog vs...

VWO
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.

Roadmap & changelog

Here’s what the team is up to.

Latest update

Apr 2024

Cohort creation improved

Feature success has made two small, but mightily important quality-of-life improvements for when you create new cohorts.

The first is simply that we now tell you very clearly at the top of the page when your cohort was last calculated, so you can judge how accurate it is. Cohorts are still normally recalculated every 24 hours, so we added that information too.

The second update is that now, when you specify an event, you can also add filters and custom dates directly within the cohort creation. It's another small tweak which should hopefully greatly improve the speed at which you build cohorts.

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.

    Milestones
    Project updates

    No updates yet. Engineers are currently hard at work, so check back soon!

  • 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.

    Milestones
    Project updates

    No updates yet. Engineers are currently hard at work, so check back soon!

Questions?

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

  • Question / Topic

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