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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 Overview
Test Details & Notes

Hypothesis

A/B testing tool

Test Notes

Segmentation Notes

Recommended Next Steps

Primary Goal Of This Test ?
What Are You Testing?
Baseline (Control)
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Variation 1
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What Changed
Test duration ?

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?

Have a real number from Shopify? (optional)
Your orders vary a lot. If you can grab the real number from Shopify (or your testing tool), the calculator's prediction will be much more accurate.
Your orders vary a lot. If you can grab the real number from Shopify (or your testing tool), the calculator's prediction will be much more accurate.
Snapshot
Input Summary
Results
Not enough data yet

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).

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    Probability to Win
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    Estimated Lift
    Baseline wins Challenger wins
    80%
    90%
    95%

    Projected Revenue Impact ?

    Projection style:
    Time Period Est. Visitors Expected Gain

    Worst-Case Scenario ?

    Time Period Est. Visitors Potential Loss