[PLACEHOLDER: Main headline]
[PLACEHOLDER: One-line description]
Latest Articles
All articles →- Decision Intelligence: What Marketing Teams Actually Mean When They Say 'Data-Driven' Most 'data-driven' decisions aren't. Here's the framework for building systems that actually improve decisions over time.
- Why Most A/B Tests Fail Before They Start The statistical and process errors that invalidate most experiments before a single visitor lands — and what to do instead.
Free Tools
All tools →- A/B Test Statistical Significance Calculator Calculate whether your A/B test results are statistically significant using a chi-square test. Supports one-tailed and two-tailed testing.
- Chi-Square Test Calculator for CRO Run a chi-square test to determine if differences in conversion rates between your control and variant are statistically significant.
- Minimum Detectable Effect (MDE) Calculator Find the smallest effect size your A/B test can reliably detect given your sample size, baseline rate, and desired statistical power.
- Sample Size Calculator for A/B Testing Calculate the minimum sample size needed per variation before launching your A/B test, based on your baseline conversion rate and MDE.
- Welch's T-Test Calculator Compare the means of two independent groups with unequal variances. Used for revenue-per-visitor and other continuous metrics in A/B testing.