These answers come from the year-long archive of my previous chatbot that lived on my previous site iamnicola.ai. I’ve curated the most useful sessions—real questions from operators exploring AI workflows, experimentation, and conversion work—and lightly edited them so you get the original signal without the noise.
experimentation
How do I analyze A/B test results?
Analyzing A/B test results requires looking at both statistical and practical significance. Check if results are statistically significant using your testing platform's tools or calculators. Look at conversion rates, not just raw numbers. Consider segment analysis—did the test perform differently for different user groups? Check for external factors that might have influenced results (holidays, campaigns, etc.). Ensure you've run the test long enough to capture full business cycles. Look at secondary metrics too—did the change affect other important metrics? Finally, assess practical significance—is the improvement worth the implementation effort? Document learnings for future tests.
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