An inconclusive A/B test means the available evidence cannot distinguish a useful win, a meaningful loss, or an effect too small to matter under the planned decision rule.
Check test health first
Review assignment balance, exposure, event collection, orders, eligibility, outages, variant rendering, and business changes. Do not interpret uncertainty until the experiment setup is trustworthy.
Compare uncertainty with value
A wide interval may justify more traffic if the decision is important and the test remains representative. A narrow interval around a trivial effect suggests the idea is not commercially useful.
Do not extend by habit
Use the planned maximum runtime and traffic budget. Extend only when the extra sample has a reasonable chance of changing the decision and the market context will remain comparable.
Capture the learning
Record whether the evidence challenged the hypothesis, the treatment was too weak, the audience was too small, or the metric was noisy. Redesign a stronger follow-up or close the idea so it does not return without new evidence.
Run the test in Shopify
Sofcy supports URL, template, theme, and custom JavaScript API experiments.
Start free trial