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A/B Test Significance Calculator
See which variation is most likely to grow your Shopify revenue per visitor, powered by Bayesian analysis with 100,000 Monte Carlo simulations.
Built by Kozler for 7–8 figure Shopify brands to decide which tests to roll out across their stores.
Test Details & Notes
Hypothesis
A/B testing tool
Test Notes
Segmentation Notes
Recommended Next Steps
What Changed
What Changed
What Changed
What Changed
How many calendar days has this test been running?
How much do your order values vary?
The more your order sizes jump around, the more sales we need to see before we can confidently call a winner. As your test collects more orders, the calculator becomes more certain on its own.
Which one sounds most like your store?
This number says how much your orders bounce around the average. Around 0.2 means orders are nearly all the same; around 1.8 means orders swing a lot. The calculator uses this number for every version of your test, unless you type in a real figure for a specific version below.
Have a real number from Shopify? (optional)
Results are directional only - don't use them to make a final call. For reliable results, each variation needs at least 200 orders (5,000 visitors is shown as extra context).
At current pace, to reach 200 orders per variation
Results by variation
Choose which variation the detailed results below apply to. Thresholds, verdict, and revenue projections all follow your selection. The comparison table shows every variation at a glance.
Simulation lift distribution
Showing lift for the variation and metric selected below. The chart stays in sync with the metric tabs above when you change either.
Simulation lift distribution
Rotate your phone for a wider chart.
Showing lift for the variation and metric selected below. The chart stays in sync with the metric tabs above when you change either.
Projected Revenue Impact ?
| Time Period | Est. Visitors | Expected Gain |
|---|
Worst-Case Scenario ?
| Time Period | Est. Visitors | Potential Loss |
|---|