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Test hypothesis
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A test hypothesis is a statement formulated to predict the result of a specific modification to a website or application as part of an optimization process. Resulting from a prior data analysis, it aims to answer a precise question concerning the expected impact on a predefined KPI.
The typical formulation of a hypothesis is: "If we change [element], then we'll see [desired result]". This hypothesis then guides the design and execution of the A/B or multivariate test, and will be validated or refuted by a statistical significance test, whether Bayesian or frequentist.
This approach structures the optimization process in a methodical way, ensuring that tests are based on sound observations and analysis.
By validating or refuting the hypothesis, companies can gain valuable insights into the effectiveness of the changes made, helping them to make informed decisions to improve the user experience and achieve their business objectives.
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