Not reaching statistical significance?

Tests that do not reach statistical significance have not produced a valid conclusion:

What it means: The observed difference could easily result from random variation. You cannot confidently say one variant is better.

Common mistakes:

Declaring the variant with higher raw numbers the "winner" despite insignificance. Stopping the test and implementing based on directional results. Assuming small differences mean variants are "tied."

Proper responses:

Continue testing until significance is reached, if possible. Accept the test as inconclusive and move on. Redesign with larger expected effect size or bigger samples.

Learning from inconclusive tests: The absence of significant difference is information. It suggests the tested variable may not matter much for this audience.

Inconclusive is a valid result. Acting on insignificant results is not cautious, it is wrong.