Experimentation & feature flags · Kameleoon

Kameleoon

Web experimentation and feature-management platform supporting frequentist, sequential, and Bayesian analysis side by side.

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Kameleoon runs A/B and multi-page website experiments plus feature-flag rollouts, and is notable for letting teams choose among classical fixed-sample frequentist testing, sequential testing (continuous monitoring without inflating false positives), or Bayesian statistics on the same experiment, along with multiple-testing correction and CUPED variance reduction. Its non-informative-prior Bayesian mode computes each variant's probability of improving over the original, while sequential testing lets teams check results at any time without pre-committing to a sample size. A newer AI feature, "PBX" (Prompt-Based Experimentation), lets users build test variants and prioritize test ideas conversationally rather than by manually coding changes. It is delivered as a lightweight client-side snippet plus server-side options, with SPA support for React and Next.js, and is cloud-hosted.

At a glance

Vendor Kameleoon
Pricing model Quote only
Free tier —
Deployment Cloud
Open source No
Best for Teams that want to pick their statistical method per experiment rather than being locked into one engine.

Pricing

Custom quote; a pricing page exists but no figures were shown on the pages read.

Pricing has not been verified yet — see the vendor's site.

Features

  • A/B and multi-page website testing
  • Choice of frequentist, sequential, or Bayesian analysis on the same experiment
  • CUPED variance reduction and multiple-testing correction
  • Feature flagging with progressive rollouts
  • AI-assisted test-variant generation (PBX)
  • Lightweight snippet with SPA framework support

Integrations

Profile last reviewed September 21, 2026

Alternatives

Optimizely One of the original A/B testing platforms, now the experimentation module of a broader digital-experience suite (CMS, commerce, personalization). VWO Long-running web experimentation and personalization platform, using a Bayesian stats engine, now merging with AB Tasty under the Wingify brand. AB Tasty French web experimentation and personalization platform defaulting to Bayesian reporting, now merged with VWO under the Wingify brand.

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Terms to know

A/B testing A controlled experiment that compares two variants to measure which one produces a better outcome. Statistical significance A threshold judgment that an observed effect is unlikely to be due to chance alone, given the data and test used. Confidence interval A range calculated from sample data that, under repeated sampling, would contain the true value a stated percentage of the time. P-value The probability of observing data at least as extreme as the result, if the null hypothesis were actually true. CUPED (controlled-experiment using pre-experiment data) A variance-reduction technique that uses each user's pre-experiment behavior to sharpen an experiment's estimate without adding more traffic. Sample size The number of observations in a study or test, which determines how precisely and reliably an effect can be measured.

Related guides

How to choose an experimentation and feature-flag platform Pick by where your experiment data comes from — flag telemetry or your own warehouse — and which statistical engine your team trusts, not feature count.