Why not just use our trailing churn rate like we always have?
A trailing rate is accurate on average, but it can't tell you when a specific quarter's book is riskier than average. Thornbury's flat 9% rate missed $294,000 of exposure that was sitting in six accounts with a clear usage decline, invisible inside a company-wide blend.
What if we don't track detailed product usage per account?
Start with whatever exists: login frequency and active seat count are usually available even without a full analytics instrumentation, and both are meaningful risk signals on their own. Add feature-level adoption once it's available, and note in Risk Definitions which signals the current tiers are actually built from.
How many quarters of history do we need to calibrate tier churn rates?
Two quarters is a workable start; four is stronger. The methodology doc records how many accounts and quarters each tier's rate is calibrated from, so a rate built on nine accounts is visibly weaker evidence than one built on forty.
Won't netting expansion into the forecast make the number look better than it is?
Only if expansion isn't qualified first. The pack's rule requires a named stakeholder, a stated target, and a date before any opportunity nets against churn. Thornbury's worked example still lands lower than a naive forecast even with real expansion included.
Can an account be both a churn risk and an expansion opportunity?
In principle yes, but in practice a real expansion pitch rarely survives contact with an account already in the red tier. The pack treats an expansion conversation on a declining account as a risk signal worth logging in Risk Definitions, not as pipeline to count.
How is this different from a pipeline coverage or forecast accuracy review?
Those tools cover new-business pipeline and a quarter's commit-versus-actual gap. Pipeline coverage checks whether enough new pipeline exists to hit the number; this pack covers the separate, ongoing question of what the existing customer base itself is worth net of churn and expansion.
Does this pack set next year's quota, or just forecast the current book?
Just the forecast. Quota-setting for a renewal-heavy book is a separate, earlier decision. The territory and quota model template builds next year's territories and quotas from scored account potential, before this pack's ongoing renewal and churn tracking takes over.
Risk-adjusted Forecast