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 measure the impact of my experimentation program?

Measure experimentation program impact by tracking tests run, win rate, average lift per test, and cumulative conversion improvements. Track velocity—how many tests you run per month or quarter. Monitor win rate—what percentage of tests show positive results (30-40% is typical). Calculate average lift from winning tests. Most importantly, track overall conversion rate trends over time—successful programs show steady improvement. Also measure cultural metrics like number of people proposing tests and time to implement tests. Example: A program running 20 tests per quarter with 35% win rate and average 5% lift per winner resulted in 15% overall conversion improvement over a year.

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