A hypothesis is not a result. Plan a marketing test
One idea, one primary metric and a decision rule chosen in advance. No promises of growth before the test begins.
Define success before drawing conclusions.
“Move delivery information higher on the page and more people will buy.” It is a useful starting point, but not yet an experiment plan. What changes? What is the comparison? What would count as convincing evidence?
State the reasoning
Write a hypothesis that could be disproved: “Showing delivery cost and timing before checkout may help customers understand the full cost.” This describes a possible mechanism. It does not promise a revenue increase.
Define the change
Describe the control and the new version. For an initial test, change one clear element, such as the position of the delivery information. Changing the price, offer and page together makes the result harder to interpret.
Use the business’s actual delivery terms. Do not invent a promise for the sake of a test.
Choose the metric and guardrails
The primary metric should answer the question. For purchases, consider the share of sessions with a purchase, but define the metric and source before starting. Add guardrails, such as average order value or checkout errors.
The required duration and data volume depend on traffic and the size of the effect you want to distinguish. A handful of purchases is weak evidence for declaring a winner. If the evidence is insufficient, record the result as inconclusive.
Where AI can help
Prepare a test plan for clearer delivery information: hypothesis, two versions, primary metric, guardrails and stopping conditions. Ask for missing inputs first. Do not present an expected effect as a measured result.
AdHatch helps you save the hypothesis, plan and decision in your business context. You still need to run and measure the experiment using your chosen method. Saving a plan does not automatically launch an A/B test.
Return to the question
After the test, record the dates, changes and observed outcome. Document the limitations and decision: adopt the change, investigate again or reject the idea. Even an unconfirmed hypothesis is useful when the team understands what it tested.