InTrendz MediaSystem: nominal

Lab // Unit Economics and Measurement

How to size an A/B test before you launch it

The short answer

Size an A/B test by choosing your baseline conversion rate, the smallest lift worth detecting, a confidence level of 95 percent and a power of 80 percent. The formula then gives the visitors needed per variant. Run the test for that full sample and at least one full week.

Key takeaways
  • Decide the sample size before you start.
  • Smaller lifts need far more visitors.
  • Do not stop at the first significant result.

Inputs you need

You need the current conversion rate, the relative lift you care about and your traffic. A baseline of 3% and a target lift of 20% means detecting a move from 3.0% to 3.6%.

The result

That test needs about 13,900 visitors per variant, or 27,800 in total. At 1,000 visitors a day, plan for 28 days. Halving the lift to 10% raises the requirement to about 53,200 per variant.

Protect the result

Stopping early inflates false positives. Decide the end date in advance, run whole weeks and change only one thing at a time.

Free tool / Clinical trials

How many visitors before a result is valid?

A/B Test Planner

Questions about Unit Economics and Measurement

What if I lack the traffic?

Test bigger changes, test higher-traffic pages or use a less strict confidence level with care.

What is statistical power?

It is the chance of detecting a real effect of the size you chose.

Key terms

Written by

Kartikeya Awasthi, Co-founder, InTrendz Media

Kartikeya has 12 years of experience across Accenture, EY, Coforge and other enterprises. He holds an MBA from NMIMS Mumbai and has received CII National Gold and Silver awards for AI and Industry 4.0 work. He writes and reviews every Growth Lab article. More about the author

How we write and review

Keep reading