In A/B testing, what best describes the role of isolating a single variable?

• A. The test isolates a single variable to measure its impact on outcomes
• B. The test manipulates multiple variables to see combined effects
• C. The test ignores external factors and relies on intuition
• D. The test runs only to collect qualitative feedback

Answer: (C)

Isolating a single variable in A/B testing means ensuring that the only difference between the two versions is that one element being tested. By keeping everything else constant and using random assignment to groups, you can attribute any observed change in the outcome directly to that specific change. This approach is what lets you make a causal claim about the impact of that element rather than just observing a correlation. If multiple elements were altered, you wouldn’t know which change caused the difference. Relying on intuition or ignoring external factors would undermine the experiment’s validity, because external factors could be driving the result. While qualitative feedback can be useful, A/B testing primarily seeks quantitative evidence of impact on the chosen metric.