How do you calculate stage-to-stage conversion?

Of opportunities that entered a stage, the share that reached the next one, computed on a creation cohort rather than within a period. Period-based rates compare two different populations.

What does a near-100% conversion rate between two stages mean?

The stages are not distinguishing anything. Either the exit criterion is not applied, or the two stages describe the same state and one should be removed.

Why do our stage probabilities not match observed conversion?

Because assigned probabilities are usually set once and never re-fitted, while the process and the mix change. Re-fitting them against observed conversion is arithmetic on data you already hold and is often the highest-yield forecasting fix available.

Should conversion be measured per rep?

Only with care. Individual conversion differences frequently reflect when each person creates opportunities rather than how well they sell, so hold the creation criterion constant before comparing.

Stage-to-Stage Conversion

The proportion of opportunities moving from each stage to the next. The most localised view of where pipeline dies.

The calculation

Of the opportunities that entered a stage, the proportion that went on to reach the next one. Computed on a creation cohort followed forward, not on counts within a reporting period — the period version divides one population by a different one.

What the pattern tells you

Reading the conversion profile

Observation	Likely meaning	Action
One stage far lower than the rest	A real qualification or capability gap	Investigate that transition specifically
Near-100% between two stages	Stages not distinguishing anything	Merge or remove one
Rates drifting up over time	Criteria loosening, not skill improving	Re-check exit criteria
High conversion, low win rate	Advancement is not qualification	Exit criteria are not being applied

Source: Diagnostic framing stated here

The forecasting use

Assigned stage probabilities in most CRMs are defaults nobody re-fitted. Comparing them against observed conversion and correcting the difference is usually the largest single improvement available to forecast accuracy, and it costs an afternoon.

Computing it defensibly

Group by creation date and follow forward until most of the cohort has resolved. A cohort still half open produces a provisional rate.
Hold the opportunity creation criterion constant. Any change to it breaks the series.
Segment before comparing. Different motions have genuinely different profiles and a blended rate describes neither.
Report the count alongside the rate. A 40% conversion on ten opportunities is not a finding.

Where it misleads

Rates improve when opportunities are created later in the process, which is a definitional change rather than a performance one.
Deals that skip stages distort every rate they touch; count them before trusting the series.
It measures advancement, not quality — and advancement is exactly what someone under pressure can produce directly.

RELATED TERMS

Time in Stage

How long opportunities remain in each pipeline stage. The diagnostic that localises where deals actually stall.

Revenue Funnel

The staged model describing how prospects progress from first awareness to closed revenue, used to locate where volume is lost between stages.

Win Rate

The proportion of opportunities that close won, measured against a defined denominator — which is where most of the disagreement lives.

Weighted Pipeline

Pipeline value multiplied by a probability assigned to each stage, producing an expected value rather than a gross total.

COMMON QUESTIONS

How do you calculate stage-to-stage conversion?: Of opportunities that entered a stage, the share that reached the next one, computed on a creation cohort rather than within a period. Period-based rates compare two different populations.
What does a near-100% conversion rate between two stages mean?: The stages are not distinguishing anything. Either the exit criterion is not applied, or the two stages describe the same state and one should be removed.
Why do our stage probabilities not match observed conversion?: Because assigned probabilities are usually set once and never re-fitted, while the process and the mix change. Re-fitting them against observed conversion is arithmetic on data you already hold and is often the highest-yield forecasting fix available.
Should conversion be measured per rep?: Only with care. Individual conversion differences frequently reflect when each person creates opportunities rather than how well they sell, so hold the creation criterion constant before comparing.