StreamCart wants to test a new signup page that may improve visitor-to-account conversion. Before launching the experiment, the product team wants to know how many users are needed to reliably detect a meaningful lift.
Plan the sample size for a two-arm A/B test on conversion rate. The current signup conversion rate is 18.0%, and the team only wants to run the test if it has enough power to detect an absolute lift of at least 1.5 percentage points.
| Metric | Value |
|---|---|
| Baseline conversion rate | 18.0% |
| Minimum detectable effect (absolute) | 1.5 percentage points |
| Expected treatment conversion rate | 19.5% |
| Significance level | 0.05 |
| Desired power | 80% |
| Test type | Two-sided |
| Traffic split | 50/50 |
| Weekly eligible visitors | 120,000 |
{"mde_absolute":0.015,"desired_power":0.8,"significance_level":0.05,"traffic_split_control":0.5,"traffic_split_treatment":0.5,"baseline_conversion_rate":0.18,"weekly_eligible_visitors":120000,"feasible_sample_per_group":8000,"treatment_conversion_rate":0.195}Output(none)