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A/B Testing

A/B Testing is an experimentation method that involves showing two versions of the same page, email, or feature to different users, to measure which one performs best.
It allows you to make decisions based on real data rather than on intuition, to optimise conversion, engagement, or retention.

Related Services

UX Research Product strategy Our Method

Related Terms

ROI Userflow Product Discovery UX

A/B testing in practice

Typical Use Cases

  • Optimise a purchase or registration journey.
  • Test new pricing.
  • Compare two wordings of a message or a call-to-action.
  • Test a new feature with a subset of users.

Methodology

  • Only one variable tested at a time.
  • Hypothesis written and success criterion defined beforehand.
  • Sufficient statistical volume to conclude (calculate the required sample size).
  • Minimum duration (1 to 2 full cycles) to avoid weekly biases.

Tools

  • Dedicated platforms: Optimizely, AB Tasty, Kameleoon, VWO.
  • Accessible solutions: GrowthBook, Statsig, PostHog.
  • Custom Backend for SaaS - feature flags + analytics.

Caveats

  • Risk of p-hacking - do not look at the results too early.
  • Seasonality effects - take into account natural variations.
  • An A/B test win does not make a product strategy.

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