Did your A/B test really impact your goals? Use our calculator to find out!
Businesses evolve and so do their A/B testing strategies, including targeted goals. At some point, you’ll probably want to track goals for your organization that are non-binomial (or continuous), such as average pages per session, average session duration or revenue per user. Calculating statistical significance for A/B tests can be quite difficult, depending on the goal being tracked. To meet the various needs of optimization teams, we built a new statistical significance calculator that can handle all types of metrics. The calculator provides your team with options, including calculations for:
- Binomial metrics
- Continuous metrics with a t-test approach
- Continuous metrics with a nonparametric approach
Data Notes:
- The calculator works best when comparing one test variation against the original.
- See how to properly format your .csv for continuous (non-binomial) metrics.
- Learn more about the different statistical significance calculations.
Additional Statistical Calculators that Help You Prioritize A/B Tests & Maximize Impact
A/B Test Planning Calculator
Map the fastest route to statistically sound results
What it Does:
Calculates sample size, duration, and confidence level—and if you want stronger outcomes, we can help map the route to testing success.
Revenue Per Visitor (RPV) Calculator
Uncover the real financial impact of your experiments
What it Does:
Uses advanced, non-parametric analysis to measure RPV significance—and if you want greater impact, we can help navigate the path to revenue growth.
Do you know when a result is truly worth acting on?