AStreamCart, a subscription video platform, tested a new pricing banner on its sign-up page. Product leadership wants to know whether the observed lift is both statistically significant and large enough to matter financially.
Analyze the A/B test on sign-up conversion and decide whether the treatment should be rolled out. You should evaluate both statistical significance and practical significance.
| Group | Users Exposed | Sign-ups | Conversion Rate |
|---|---|---|---|
| Control (current banner) | 24,800 | 2,728 | 11.00% |
| Treatment (new banner) | 25,100 | 2,912 | 11.60% |
Additional business inputs:
| Metric | Value |
|---|---|
| Significance level | 0.05 |
| Minimum practically meaningful lift | 0.40 percentage points |
| Expected net value per additional signup | $18 |
{"alpha":0.05,"control_n":24800,"treatment_n":25100,"control_conversions":2728,"treatment_conversions":2912,"minimum_practical_lift":0.004,"net_value_per_additional_signup":18}Output(none)