3 min read
Statistical significance explained without any maths
What the number actually claims, what it doesn't, and the four sentences you need to read a result honestly without ever computing anything.
Topic
Articles on Statistical significance
Everything we have published on Statistical significance: guides, experiments and what we learned along the way.
13 articles
3 min read
More than two variants: when an A/B/C actually makes sense
Adding a third variant costs you a third of your sample and buys you a comparison you may not need. Three cases where it's worth it, and one very common case where it isn't.
3 min read
Traffic allocation: when to use 50/50 and when to use 90/10
An even split gets you the fastest answer. An uneven one limits how many customers see a change you're not sure about. You can't have both.
3 min read
The five mistakes every brand makes in its first month of CRO
Stopping early, testing everything at once, no guardrail, changing the test mid-flight and treating a win as a fact. All five are avoidable.
4 min read
How much traffic do you need for A/B testing?
The honest answer has three inputs and no marketing spin. Here's how to calculate it for your own site, and what to do when the number comes back too big.
2 min read
How to Measure the Real Impact of Your CRO Improvements
Stop celebrating statistical noise. Learn which metrics actually matter, how to reach significance, attribute results cleanly and document every learning.
2 min read
What to Do When a Test Returns Inconclusive Results
Your A/B test came back flat? A tie isn't a failure. Learn how to read an inconclusive result, what to do next, and how to turn it into real learning.
2 min read
A/B testing vs A/B/n: when to use each
Testing more than two versions at once is tempting, but every extra variant splits your traffic. Learn when A/B/n pays off and when classic A/B wins.
2 min read
Mistakes that invalidate your A/B tests (and how to avoid them)
A poorly run A/B test is worse than no test at all: it gives you false confidence. Here are the most common mistakes that invalidate results and how to prevent them.
2 min read
Sample size: how to know if your test is reliable
Sample size quietly ruins more experiments than any other factor. Learn the three variables behind it and how to know if your A/B test can actually reach a conclusion.
2 min read
How Long Should You Run an A/B Test
Stop too early and you crown false winners; run too long and you waste traffic. Learn how to set the right A/B test duration before you launch.
2 min read
Statistical Significance Explained for Marketers
P-value, confidence level and false winners explained in plain English. Learn to read what your A/B testing tool tells you and stop shipping fake wins.
2 min read
A/B testing for beginners: concepts you need to master
Learn the core A/B testing vocabulary: control, variant, hypothesis, significance and metrics, so you can launch reliable experiments from day one.
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