What does a hypothesis in A/B testing include?

• A. It describes the problem being addressed, the planned change, and the expected impact of that change
• B. It lists the budget and resources
• C. It ignores the planned change
• D. It only states the desired outcome

Answer: (A)

In A/B testing, a hypothesis is a concise, testable statement that ties a problem to a planned change and the expected impact on a specific metric. It defines what you’re trying to improve, describes the modification you’ll test, and predicts the outcome you expect to see as a result. This makes the experiment measurable: you know which metric to track, what change to apply, and what level of improvement would count as success, all within a defined timeframe. For example, you might hypothesize that changing the product-page hero image to a more product-focused image will increase the conversion rate by a certain percentage because it better communicates value to visitors. The idea is to establish a clear cause-and-effect expectation so you can determine whether the change works. Budgets or resources aren’t part of the hypothesis, and simply stating the desired outcome isn’t enough without specifying the change and how you’ll measure its impact.