What is your favorite research method? Under what circumstances do you feel it's best applied? What are the pros and cons of using this methodology?

"My favorite research method is A/B testing, especially when evaluating specific features or design elements in a product to understand their impact on user behavior. A/B testing is ideal when we want to determine the effectiveness of a change by directly comparing two or more versions of an experience. It’s best applied when we have a clear hypothesis, measurable outcomes, and a large enough sample to achieve statistical significance.

Pros: One major advantage of A/B testing is that it provides clear, actionable insights by isolating variables. This helps determine causation rather than just correlation, which is valuable for making confident, data-backed decisions. Additionally, A/B testing is highly iterative, allowing teams to continuously optimize features based on real user feedback in real-time environments.

Cons: However, A/B testing does have limitations. It requires a significant user base to achieve statistical significance, which may not be feasible for niche products or low-traffic features. Also, it can be narrow in scope—testing one variable at a time often doesn’t capture the complexity of user experiences where multiple factors interact. Finally, if not designed carefully, A/B tests can introduce biases or fail to account for confounding variables, leading to misleading results.