Lifecycle Email Map
Maps email by user state rather than by calendar, so nobody receives an onboarding message in month nine.
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Running it, start to finish
- Define states by observable behaviour and count who is in each.
- Give every sequence an explicit exit condition.
- Concentrate effort on the transition with the biggest drop-off.
What you get back
The output this produces, every time.
- Defines states behaviourally, so nobody gets an activation nudge for something they already did.
- Names the exit condition for every sequence, which is what most programmes omit.
- Weights effort at the transition where the drop-off actually is, not where writing is most pleasant.
Getting better results
Where this usually goes wrong, and how to avoid it.
- Trigger on behaviour, not elapsed time. A day-five email to someone who succeeded on day one damages credibility more than the email could ever earn.
- Watch the at-risk signal, not the renewal date. By the time a renewal is due the decision is usually made. The usage decline was visible months earlier.
- Judge on the transition. Open rate measures the subject line. Whether people moved state measures the email.
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Written for The AI University. Every prompt in this library is original work — authored, tested and revised here, not collected from elsewhere. 365 of them, free with an account.