Can your traffic actually prove the conversion lift you're chasing?
See what a conversion-rate improvement would be worth, then see how much traffic and time you actually need to distinguish a real lift from ordinary noise. The value is conditional. The sample requirement is not.
Your test economics
The four core numbers are all available in Shopify Analytics. Monthly revenue is entered directly rather than reconstructed from traffic × CVR × AOV.
Shopify Analytics → Overview → Sessions.
Shopify Analytics → Online store conversion rate.
Use Shopify Total sales for the same monthly basis.
10 means 1.80% → 1.98%, not 1.80% → 11.80%.
Optional. If you leave this blank, the revenue scenario and detectability result still work. No margin assumption will be substituted.
Derived AOV = monthly revenue / monthly orders. Enter COGS on the same basis.
Required for a contribution estimate whenever return rate is above 0%.
2 = control + one challenger.
Example: if a 10% relative conversion lift is real and holds after rollout, this is what it would be worth at your current revenue.
| Today | If the lift is real | Difference | |
|---|---|---|---|
| Annual revenue | ₹240.0L | ₹264.0L | +₹24.0L |
| Annual contribution | — | — | — |
Small wins are disproportionately expensive to confirm.
Same baseline CVR, traffic, allocation and test setup. Only the relative lift changes.
| Relative CVR lift | Time to detect |
|---|
Show how this is calculated
Per-variant sample size uses the standard two-proportion approximation with a two-sided alpha of 0.05 and 80% power. When more than two variants are tested, alpha is divided by the number of control-vs-challenger comparisons.
Mawara can help decide what is worth testing.
We design CRO programmes around the traffic, economics and effect sizes a store can actually measure, rather than filling a roadmap with tests too small to resolve.