Are your results statistically significant?

A/B Testing Significance Calculator

This significance calculator will tell your A/B test results is reliable

What is statistical significance?

Statistical significance is a mathematical concept that measures how likely it is that a given result is due to chance, it helps you to understand whether or not your results are meaningful.

For example, let’s say you have a website that converts at a rate of 2%. You make a change to your website and see that your conversion rate increases to 4%.

When you enter in your data (2% conversion rate for the original version and 4% conversion rate for the new version), the calculator will tell you that the difference is significant.

This means that the increase in conversion rate is unlikely to have occurred by chance, and is most likely due to the change that you made to your website.

Why is statistical significance important?

Statistical significance is important because you want to make sure that the differences you’re seeing are actually due to the change you made, and not just chance.

For example, let’s say you make a change to your website and you see a small increase in conversions. Is this a significant difference?

If the answer is “no,” then it’s possible that the increase in conversions is just due to chance. In other words, if you had made no change at all, you might have still seen an increase in conversions.

On the other hand, if the answer is “yes,” then you can be confident that the increase in conversions is due to the change you made.

Just getting started with A/B testing?

If you're just getting started with A/B testing, there are a few things you should keep in mind.

1. A/B testing is all about making small changes to see what has the biggest impact on your goal.
2. You need to have a clear idea of what you're trying to test and what your goals are.
3. Make sure you're collecting enough data to make informed decisions.

If you're not sure where to start, try testing something small, like the subject line of an email or the call to action on a landing page. Once you've got a feel for how A/B testing works, you can start testing more significant changes.

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Whichever change you decide to test, make sure you're clear on your goals. What are you trying to improve? Whether it's conversion rates, click-through rates, or something else, make sure you have a plan for measuring success.

Finally, don't forget that A/B testing is an ongoing process. The more you test, the more you'll learn about what works for your business. So keep at it, and don't be afraid to try new things. With A/B testing, you can never fail, only learn.

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