"No significant effect" is one of the most expensive sentences in analytics — because it's so often wrong, or rather, incomplete. A flat aggregate can hide a strong win in one segment and a drag in another that cancel out.
First, earn the right to slice
Before cutting by segment, check the boring things: was the test powered, did randomization hold, are the guardrails clean? If those fail, segment analysis is just noise with extra steps.
Then slice — but pre-register the cuts
The danger of segmentation is that if you cut enough ways, something always looks significant. The discipline:
- Decide the segments before you look.
- Correct for multiple comparisons.
- Treat anything you find post-hoc as a hypothesis for the next test, not a conclusion from this one.
Tell it as a trade-off, not a verdict
The strongest version of this analysis doesn't say "ship it" or "kill it." It says: here's who wins, here's who loses, here's the size of each — your call. That framing is what turns an analysis into a decision.
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