Choose the comparison
Open Optimize and select your published offer. The control is your current setup; the alternative is the change you want to test. For example, compare a $75 threshold with $90. Change one thing so you can interpret the difference.
A store-rates comparison is available for an offer with one enabled tier. That side uses the store's shipping rates without the tested free-shipping offer. Other store discounts and shipping rules still matter.
Create the $75 versus $90 experiment
Actual app creation screen with example inputs. Select the live offer, enter the alternative threshold, and review the cost assumptions.Review costs and readiness
Enter the margin and average shipping cost requested by the app. Profit reporting depends on these assumptions. Resolve the readiness messages before starting; do not try to bypass a targeting or campaign conflict.
Keep your theme, other promotions, and targeting stable during the comparison. One active experiment runs at a time.
Start and verify the comparison
Review the control, alternative, target market, and cost assumptions, then use the start action in Optimize. Check that the experiment appears as running and that exposures begin to collect. Shoppers are assigned to a side; repeatedly refreshing your own browser is not a reliable way to preview both variants.
Let the evidence collect
At least seven full days, 1,000 exposures per side, and 200 confidently matched orders in total. Confidence and traffic-quality checks must also pass. These are minimum gates, not a promise that a winner will appear when you cross them.
Check measurement health and both sides of the comparison. A temporary lead can reverse. Avoid stopping just because a favorable number appears.
See how traffic and effect size change the planning estimate. Setup time, the subscription trial, and experiment duration are different.
Your next decision
The intended comparison is running, both sides collect exposures, and the app shows no unresolved readiness or measurement problem.