Are you wondering if a design or copy change impacted your email or landing page's conversion rate? Use this A/B testing tool to calculate the statistical significance of your A/B test to make truly data-driven decisions.
|99-100%||Results are highly significant (this is a sure thing).|
|95-98%||Results are statistically significant (good enough for academic publishing).|
|90-94%||Results tend toward statistical significance (good for a rough sense).|
|51-89%||Results are not statistically significant (could just be a fluke).|
|<= 50%||Results are not statistically significant (likely a fluke).|
* Results assume experiment was set up the correctly.
** Results calculated using the chi-squared statistical hypothesis test.
Read this guide for an A/B testing framework that will set you up for digital marketing success and learn how to use a/b testing statistics to deliver more personalized customer experiences, and drive more revenue while growing your business.
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