When is an A/B test not applicable?

A/B testing is not applicable in the following cases:

• Low traffic or small sample size: when the number of users is too small, the results will be statistically insignificant.
• When changes affect all users at once: for example, changing the database architecture or critical updates that cannot be divided into groups.
• If the effect of changes manifests very slowly: when the test results require a long time to evaluate, making testing inefficient.
• Under ethical or legal restrictions: if testing can harm users or violate laws.
• When it is impossible to isolate a variable: if it is difficult to identify a single metric to test, the results will be ambiguous.

In such situations, it is better to use other analysis methods or conduct testing at the prototype and research level.