Design the list-building experiment
Specifies one bounded conversion test — the variant, hypothesis, success metric, and stop rule — so the experiment is runnable and yields a clear decision.
In / outGrowth bottleneck + available variants → experiment spec (variant, hypothesis, metric, stop rule)
You might say…
“I want to test whether a different opt-in hook grows my list faster but I've never run an experiment that was actually well-defined enough to learn from.”
What it does
Specifies one bounded conversion test — the variant (subject line, opt-in form, lead magnet, CTA placement, referral incentive, or trial channel), the hypothesis, the success metric, and the stop rule — so the experiment is runnable and decidable. Used at the front of a single growth experiment to define what is being tested and how the result will be judged.
Trigger: Use at the front of a single growth experiment to define what is being tested and how the result will be judged before anything is built.
Recognise the problem?
The primitives are the commodity part. The fastest next step is a conversation about composing them into something that works for you.
Start a conversation