What is a recommended best practice when implementing an experiment?

Testing one variable for each experiment is a recommended best practice because it allows for clear and accurate measurement of the variable's impact on the desired outcome. By isolating a single variable, you can directly attribute any changes in performance metrics, such as click-through rates or conversion rates, to that specific change. This clarity is crucial for making informed decisions based on the results of the experiment.

When multiple variables are tested simultaneously, it becomes challenging to determine which change was responsible for any observed effects. This can lead to confusion and ambiguity in the insights gained from the experiment, undermining the validity of the conclusions drawn.

Using a control group is certainly valuable in experiments as it provides a baseline for comparison, but it complements the practice of testing one variable at a time rather than serving as a standalone best practice. Conducting surveys before experiments could provide useful qualitative insights, but it doesn’t directly influence the method of conducting the experiments themselves. Overall, focusing on a single variable enhances the scientific rigor of the testing process and allows marketers to make better strategic decisions based on clear evidence.