By the time they tell you, the decision is already made. Save attempts after cancellation rarely work. And you only see the churn problem in next quarter's numbers, when it's too late to do anything about it.
NPS is lagging. AM gut feel is biased toward the squeaky wheels. The "at-risk" spreadsheet gets touched once a quarter, the day before the QBR. By then, the customer has been deciding for months.
Pull every behavioral signal you already have. Weight recent shifts. Rank by expected churn × MRR. Attach the top 2-3 reasons so the CSM walks into the call already calibrated.
Explainable rules, not black-box ML. You can read why a forecast is high or low. That means operators trust it, edit it when their gut disagrees, and the model learns from the edits.
Output lands in the systems your team already opens. No new dashboard to log into.
Demand, churn, and inventory are three shapes. The underlying engine takes any historical series with a few signals attached and gives you a forecast with confidence and explanations.