Here is one I actually shipped. What happened, what I did, and the stack if you want to run it yourself.
The year started with a piece of math nobody wanted on the table: churn and downgrades were larger than everything the new-business engine brought in. We were filling a bucket with a hole in the bottom and congratulating ourselves on how fast we poured.
Renewals were handled reactively. A CSM found out an account was leaving roughly when the account told them. By then the conversation is not a save, it is an exit interview. And the audit made the scale of it undeniable: 66% of renewals were getting zero renewal activity. Not late activity. None.
You cannot save a renewal in the last thirty days. You can save it ninety days out, when the signals first turn. The whole job was to move retention from reactive to proactive, which means one thing in practice: see the risk early enough to act on it. So the work started with autopsies, not dashboards, because you cannot build an early-warning system until you know what the early warnings are.
- GChurn and downgrades outweighed everything new business brought in, and a CSM learned an account was leaving when the account said so.
- IGong autopsies found what predicted a loss, Amplitude flagged accounts turning cold, Salesforce held the book view, Deepline ran the renewal play.
- AAI runs the autopsies and the early-warning score. The CSM owns the save, months ahead of the date.
- NThe score drove a standing renewal review at 180 days, with a VALUE business case built from usage for every at-risk account.
- TChurn and downgrades fell 28%, and the same read fed a seven-figure churned-customer win-back.