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 success of an experimentation program?

Measure experimentation program success by tracking tests run, win rate (typically 30-40%), average lift per winning test, overall conversion rate trends, and business impact (revenue, sign-ups, etc.). Track velocity—how many tests you run per month. Monitor whether you're testing strategically or randomly. Measure time to implement tests and results. Most importantly, track overall conversion rate over time—successful programs show steady improvement. Also measure cultural metrics like number of people proposing tests. A good consultant helps establish metrics and reporting. Success isn't just about individual test wins—it's about building a systematic program that delivers consistent improvements.

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