You're implementing an experiment. Which of these approaches should you follow as a best practice?

Assign two campaigns to each experiment arm.

Test one variable for each experiment.

Start with multiple hypotheses.

Divide your audience into as many arms as possible.


Choose an option to see if it’s correct. Check the explanation below. Learn Smarter, not Harder.

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Explanation: You’re implementing an experiment. Which of these approaches should you follow as a best practice?


Explanation: The correct approach to implementing an experiment, following best practices, is to **'Test one variable for each experiment.'** Testing one variable at a time allows for clear and focused experimentation, enabling researchers to accurately measure the impact of that specific variable on the outcome of interest. By isolating one variable, such as ad copy, targeting criteria, or bidding strategy, researchers can attribute any observed changes in performance directly to that variable, without confounding factors from other variables. This approach enhances the reliability and validity of the experiment results, making it easier to draw meaningful conclusions and inform future decision-making. Additionally, testing one variable at a time simplifies the experimental design and analysis process, reducing complexity and ensuring that the experiment remains manageable and interpretable. Therefore, testing one variable for each experiment is the best practice approach for implementing experiments, as it maximizes the accuracy and usefulness of the findings, leading to more informed marketing strategies and improved campaign performance.

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