Experiment Calculator: Estimate Sample Size for A/B Tests
Because 51% vs. 49% means nothing without 10,000 people
By Tristan Kromer · Quick Answer: Kromatic’s free Experiment Calculator helps us estimate the sample size needed before running A/B tests or surveys and interpret results afterward. The key insight: small differences like 51% vs. 49% aren’t statistically meaningful unless you have ~10,000 respondents. Margin of error matters more than most entrepreneurs realize, and this tool makes it easy to avoid false conclusions from quantitative data.
Hi there,
tl;dr: Understand A/B test results and plan the right sample size with our Experiment Calculator
Ok, it’s not as fancy as our Innovation Portfolio game, but it’s even more important for day-to-day work. You can use our Experiment Calculator to:
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Estimate the sample size you need, and
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Understand the results from quantitative experiments
Too many entrepreneurs run a survey and assume that 51% is better than 49%. Well, it’s not unless you’ve got ~10,000 people in your survey.
Margin of Error is a really important concept, and our calculator will help you make sense of your quantitative data at zero cost. Yep, it’s an open resource for the community.
So please check out:
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New UI
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Name your experiments
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Save, share, and export your data
And of course, please let us know what you think of the experiment calculator by responding to this email!
If you read this far, a quick question for you. Please hit reply and let me know: do you run quantitative experiments on your innovation projects?
Don’t forget to check out our other free Kromatic resources – we are always here to help you invest in today, tomorrow, and the future!
Frequently Asked Questions
What is an experiment calculator and why do I need one for A/B tests?
An experiment calculator helps you estimate the sample size you need before running a quantitative experiment and understand your results afterward. Without one, we risk drawing false conclusions — like assuming 51% is meaningfully better than 49% when it’s actually within the margin of error. Kromatic’s free Experiment Calculator handles both planning and analysis for A/B tests and surveys.
How many people do I need in a survey to get statistically significant results?
More than most people think. As the article points out, a difference like 51% vs. 49% isn’t statistically meaningful unless you have roughly 10,000 respondents. The exact sample size depends on your expected effect size and desired confidence level. Using a tool like the Experiment Calculator helps us estimate the right number before we start collecting data.
What does margin of error mean in quantitative experiments?
Margin of error represents the range within which your true result likely falls. If your survey shows 55% with a ±5% margin of error, the real number could be anywhere from 50% to 60%. As product managers, we need to understand margin of error to avoid overreacting to small differences in our data that may not be statistically meaningful.
Is the Kromatic Experiment Calculator free to use?
Yes, it’s completely free. Kromatic offers it as an open resource for the innovation community. You can name your experiments, save your work, share results with teammates, and export your data — all at zero cost.
When should I use an experiment calculator vs. just looking at raw survey numbers?
Always use a calculator when making decisions based on quantitative data. Raw numbers can be deeply misleading — small differences between options often reflect random noise rather than real preferences. We should use an experiment calculator both before running experiments (to plan proper sample sizes) and after (to confirm whether our results are statistically meaningful before acting on them).
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