Renewal forecast accuracy compares the renewal dollars a team predicted for a period against the dollars that actually renewed. It is measured on the renewal book alone, separate from new business and expansion, because the three run on different mechanics and blending them hides which one is causing the miss.
Why the renewal book needs its own number
New business forecasting starts from pipeline that may not exist yet. Renewal forecasting starts from a known base of contracts with fixed expiration dates, which should make it the most predictable line in the plan. That difference shows up in the accuracy figures teams quote. ORM notes that the roughly 90% accuracy commonly cited for new and expansion forecasting excludes renewals, and that producing even that figure takes heavy manual effort and goes stale as conditions change. ORM targets 95% on new and expansion without manual adjustment, holding from day one through day 90 of the quarter.
A blended accuracy number lets a strong renewal quarter cover a weak new business call, or the reverse. Splitting them tells you which motion to fix. See forecast accuracy for how the underlying measurement works across categories.
Measure against a frozen base
Accuracy = actual renewed value / forecast renewed value, with the forecast locked at a stated point such as day one of the quarter.
The submission date has to be fixed. A forecast revised in week eleven converges on the answer by construction and reports accuracy that means nothing. Locking day one is what turns the metric into a test of whether the team understood the quarter before it happened.
The expiring base has to be frozen too. Mid-term upsells that reset terms, co-terming, and short extensions all move contract value between periods after the number was set. Hold the available-to-renew schedule as of period start, then reconcile at close by naming the contracts that moved and the value each carried.
Read the signals that move ahead of the decision
Renewal calls miss when they are built on the account owner's confidence rather than account behavior. Three inputs carry more weight than sentiment.
- Support activity. ORM finds that accounts with zero support cases are at churn risk, the same as accounts with seven or more in a year, while accounts filing 3-5 lower-severity tickets are less likely to leave. - Usage trend. Declining logins and seat activity move before anyone mentions a renewal concern. - Champion status. A departed executive sponsor resets the buying decision even when the product is working.
Score the expiring base on those inputs and the renewal forecast becomes a probability-weighted view of a known pool rather than a roll-up of opinions. That is the version worth putting next to the rest of the forecast in a quarterly review.
Frequently Asked Questions
How do you measure renewal forecast accuracy?
Divide actual renewed dollars by forecast renewed dollars for the same period, using the forecast as submitted at a fixed point such as day one of the quarter. Locking the submission date is what makes the number comparable across quarters, since a forecast revised in week eleven will always look better.
Why does renewal accuracy need to be separate from new business accuracy?
Because the mechanics differ. Renewals start from a known expiring base with fixed decision dates, while new business depends on deals that do not exist yet. ORM notes that the roughly 90% accuracy figure teams cite for new and expansion forecasting excludes renewals entirely, so blending the two hides which side is missing.
What breaks a renewal forecast most often?
A denominator that moves. Mid-term upsells that reset contract terms, co-terming, and short extensions all shift expiring value between periods after the forecast was set. Freeze the available-to-renew schedule at period start and reconcile the movements at close.
Which signals improve renewal accuracy?
Support activity is the one most teams read backwards. ORM finds that accounts filing no support cases carry churn risk, as do accounts filing seven or more in a year, while accounts filing 3-5 lower-severity tickets are less likely to leave. Usage decline and champion turnover are the other two signals worth weighting.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like renewal forecast accuracy into prescriptive action for your team.
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