Stop 10 · A/B Testing & ExperimentationTopics · 4/8
Common Experimentation Pitfalls
Part of the Data Analyst Roadmap
In short
Novelty effects (a change performs well just because it's new), seasonality, sample ratio mismatch, and running too many tests at once without correction — the recurring ways experiments mislead teams.
How to learn this
- 1Learn the term 'novelty effect' and how a longer test duration helps detect it.
- 2Read about sample ratio mismatch (SRM) and why it can silently invalidate a test.
- 3List the pitfalls most likely to show up in your own team's testing process.
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