Definition
An A/B test is an experiment that compares two variants (A and B) to measure which performs better.
Why it matters
Pricing, packaging, and onboarding changes can move revenue and churn quickly. A/B tests let you quantify impact before rolling out broadly.
Pricing implications
Use A/B tests to validate changes like price increases, tier thresholds, or free-tier limits. Focus on revenue, churn, and conversion, not just click-through.
Measurement tips
Choose a single primary metric, set a minimum sample size, and run the test through a full billing cycle if possible.
Checklist
- Define the primary metric (MRR, conversion, churn).
- Limit the test to one variable (price or packaging change).
- Use a representative cohort that matches your target segment.
- Run the test long enough to reach statistical confidence.
- Monitor churn and support volume during the test.
- Avoid mid-test changes that invalidate results.
- Document the hypothesis and outcome for future reference.
- Roll out gradually if the lift is small or risky.