Shopify A/B testing

Direct answer: Shopify A/B testing compares a control experience with one or more variants to learn which version improves a target metric such as purchase conversion or revenue per visitor. Demi helps Shopify teams run these tests inside guardrails, with clear hypotheses, traffic splits, stopping rules, and post-test learning.

When A/B testing makes sense

A/B testing is most useful when the store has enough traffic for a result to emerge in a reasonable window. Below roughly 50,000 monthly visitors, many stores should prioritize qualitative fixes and measurement hygiene before relying on experiment significance.

What a good Shopify test includes

Every test should have a single hypothesis, a primary metric, guardrail metrics, traffic exposure limits, a minimum run time, and a plan for what happens if the variant wins, loses, or is inconclusive.

How Demi reduces testing overhead

Demi drafts the experiment plan, applies merchant policy, launches controlled exposure, pauses downside risk, and turns results into reusable learning instead of leaving each test as a one-off task.