Minimum Detectable Effect (MDE) Calculator
Before running an A/B test, you need to know: can you actually detect the change you're hoping for? MDE tells you the smallest improvement your test can reliably measure given your traffic and baseline conversion rate.
How to Use This Calculator
What is MDE?
Minimum Detectable Effect is the smallest improvement your test can reliably detect given your sample size and statistical settings.
Reading the Table
Each row shows what you can detect if you run your test for that many weeks. Green means easy to detect, red means hard to detect.
Confidence Level
Controls your false positive rate. At 95% confidence, there's a 5% chance of declaring a winner when there's no real difference.
Statistical Power
Your ability to detect a real effect when one exists. At 80% power, you have a 20% chance of missing a real effect.
What Is Minimum Detectable Effect?
MDE is the smallest change in your metric that a test can reliably detect at a given confidence level. If your MDE is 2% but you're expecting a 0.5% lift, your test doesn't have enough power to see the difference — you'll likely get an inconclusive result.
MDE depends on three things: your sample size (traffic), your baseline conversion rate, and your chosen statistical power and significance level. More traffic means you can detect smaller effects.
MDE for Subscription Businesses
This calculator includes metric presets built for subscription businesses. Different stages of the funnel have very different traffic volumes and baseline rates:
High-traffic metrics
Sign-up rate, landing page conversion — typically enough volume to detect 1–5% relative changes within 2–4 weeks.
Mid-traffic metrics
Free-to-paid, trial conversion, checkout completion — may need 4–8 weeks to detect meaningful changes.
Low-traffic metrics
Cancellation rate, payment recovery — often too low-volume for traditional A/B testing. Consider before/after analysis instead.
Common mistake
Running a test for a fixed time then calling it. If your MDE is larger than the expected effect, the test was doomed from the start.
Frequently Asked Questions
What is Minimum Detectable Effect (MDE)?
Minimum Detectable Effect is the smallest change in a metric that an A/B test can reliably detect at a given confidence level. If your MDE is 2% but you're expecting a 0.5% lift, your test doesn't have enough statistical power to see the difference.
How do I calculate MDE for my A/B test?
MDE depends on three factors: your sample size (traffic), your baseline conversion rate, and your chosen statistical power and significance level. Enter your weekly visitors and baseline conversion rate into the calculator above, and it will show you the smallest effect you can detect at each test duration.
What sample size do I need for an A/B test?
The sample size you need depends on your baseline conversion rate, the size of the effect you want to detect, and your chosen confidence level and statistical power. Generally, detecting smaller effects requires larger sample sizes. Use this calculator to see what's detectable at your current traffic levels.
What confidence level should I use for A/B testing?
The standard confidence level for A/B testing is 95%, which means a 5% false positive rate. For high-stakes tests (pricing changes, major redesigns), consider 99%. For early-stage exploration, 90% may be acceptable to detect effects faster.
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