What are some common A/B test mistakes to avoid?

What are some common A/B test mistakes to avoid?

Some common A/B test mistakes include not having a clear hypothesis, testing too many variables at once, and not running the test long enough.

Can you explain why having a clear hypothesis is important?

A clear hypothesis helps you define what you're testing and why, ensuring that your results are meaningful and actionable.

What happens if I test too many variables at once?

Testing too many variables can lead to confusion about which change caused the effect, making it hard to draw valid conclusions.

How long should I run an A/B test?

You should run an A/B test for at least one full business cycle to gather enough data for reliable results.