Kaizen Loop Lab

Can I Run an A/B Test
with My Traffic?

Instead of asking you to guess a minimum detectable effect, this calculator works backwards: tell it your baseline conversion rate, daily traffic and available test window, and it estimates the smallest relative lift you can realistically detect.

Your traffic constraints

%

Assumes a 50/50 A/B split, two-sided 95% confidence and 80% statistical power.

What your traffic can detect

Visitors / variant-
Smallest detectable lift-
Approx. target CVR-
Feasibility-
-

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If you can wait longer...

Test lengthVisitors / variantDetectable relative liftApprox. target CVR

If you want to detect a specific lift...

Relative liftSample / variantTotal visitorsEstimated days

How to use this decision

If the smallest detectable lift is very large, traditional fixed-horizon A/B testing may be impractical for your traffic. That does not mean “do nothing.” It means you should choose higher-impact changes, aggregate more traffic, extend the test window, use a higher-volume KPI, or rely on repeated pre/post experiments with careful context tracking.

This is a planning estimate, not a guarantee. Seasonality, traffic quality, repeated peeking, uneven allocation, novelty effects and measurement errors can all affect a real experiment.

Track the experiments you can actually run

Experiment Impact Lab lets you store up to 100 experiments locally, compare pre/post conversion rates, calculate p-values, export CSV, and generate an AI-ready review prompt.

$12 one-time download. No login, subscription, API key or cloud upload.

Get Experiment Impact Lab — $12