Value stream mapping

Stage conversion analysis

Stage conversion analysis is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).

1 · What it is

What it is

A deal that doesn't advance out of a funnel stage is a defect the same way a unit failing inspection is — stage conversion is first-pass yield applied to a sales pipeline. This tool asks for one thing per stage: how many deals entered, how many advanced. From that it computes each stage's conversion rate, the rolled yield from first stage to closed-won (which is always lower than any single stage's rate, since losses compound), and names the single weakest stage.

2 · When to use it

When to use it — and when not to

Use it when

You can pull real per-stage counts from the CRM — how many deals entered a stage and how many advanced to the next one — for a bounded segment, not the whole blended pipeline.
You want to know which specific stage is losing the most deals, not just an overall win rate.
You want a rolled conversion figure that reflects the real compounding loss across every stage, not an average of each stage's rate.

Not when

You only have an overall win rate with no stage-level breakdown — that's a start, but it can't tell you which stage to fix.
You want time-based findings — lead time, flow efficiency, which stage is capping throughput — that's the sales funnel value stream map, the funnel PCE calculator, or the bottleneck analysis.
The pipeline segment blends deal types with genuinely different natural conversion patterns — scope down to one comparable segment first, same discipline as every other VSM-family artifact.

3 · How to fill it in

How to fill it in

Scope: Which deal source or segment, which start and end stage — typically SQL to closed-won/lost. Keep it to one comparable segment; a blended pipeline produces a conversion number that describes neither.
Stages: List each stage transition in order with how many deals entered it and how many advanced. Pull real counts from CRM stage-history, not a gut-sense estimate of 'about half fall through.'
Rolled yield · Weakest stage: Computed for you: each stage's conversion rate, the rolled yield from first stage to closed-won, and which single stage is the weakest link — nothing to enter here.
Narrative: Drafted from the weakest-stage finding and your observation notes — what reps or RevOps have actually seen about why that specific stage is losing deals.
Countermeasures: What will you do about the weakest stage, ranked by impact and effort, owned and dated? A countermeasure aimed at a stage the data doesn't name as weakest is a coaching failure mode, not a real action.

4 · What good looks like

What good looks like

The example below is a five-stage outbound funnel's stage conversion: real per-stage deal counts, a rolled yield figure with the arithmetic shown, the weakest transition named with its deal loss, and a countermeasure that traces directly to that finding.

Same example, as a downloadable xlsx workbook.

Download .xlsx

First-pass yield tracker

Outbound mid-market funnel — stage conversion

Jordan Ellis, Sales Manager · 2026-03-16

Team: Priya Anand, RevOps · Sponsor: Renee Okafor, VP Sales

Scope

Scope runs from SQL to closed-won or closed-lost for outbound-sourced mid-market deals only, same segment as the sales funnel value stream map. Counts are per calendar quarter, pulled from CRM stage-history, not a point-in-time pipeline snapshot.

Stages

Stage	Entered	Advanced	Conversion
SQL to discovery	200	150	75.00%
Discovery to demo	150	110	73.33%
Demo to proposal	110	70	63.64%
Proposal to negotiation	70	55	78.57%
Negotiation to closed-won	55	40	72.73%

Rolled yield · Weakest stage

Rolled yield

20.00%

Weakest stage

Demo to proposal

150/200 × 110/150 × 70/110 × 55/70 × 40/55 × 100 = 20.00%

Weakest stage

Demo to proposal

63.64% conversion · 40 lost

Narrative

Demo to proposal is the weakest transition at 63.64% conversion, losing 40 of 110 deals — the largest single-stage loss in the funnel. Rep feedback that prospects are asking for pricing before the demo even happens is consistent with a demo that's landing too late for some deals, rather than a demo quality problem across the board. Rolled yield from SQL through closed-won is 20.00%: of every 200 deals reaching SQL, roughly 40 close.

Countermeasures

Pilot an early-pricing-signal step at discovery for deals where the prospect asks about cost before a demo is booked, so pricing sensitivity surfaces before the demo-to-proposal stage rather than stalling it.
Linked finding: Demo to proposal — weakest stage at 63.64% conversion, 40 deals lost
Impact: high · Effort: medium · Owner: Jordan Ellis · Due: 2026-04-13
Re-run this tracker next quarter on the same segment to confirm the 20.00% rolled yield moves after the pricing-signal pilot, not just the one stage it directly targets.
Linked finding: Rolled yield — 20.00% SQL to closed-won
Impact: medium · Effort: low · Owner: Priya Anand · Due: 2026-06-30

5 · Common mistakes

Common mistakes

Averaging each stage's conversion rate instead of computing the rolled (compounding) yield.
A funnel with five stages each converting at 75% doesn't roll to 75% overall — it rolls to about 24%. Averaging badly overstates how many deals actually make it from first stage to closed-won.
Estimating stage counts from memory instead of pulling real CRM stage-history.
Reps' recall skews toward memorable deals, not typical ones — the CRM's actual stage-transition counts are the ground truth here, same as every other data-driven artifact in this catalogue.
Treating every stage below 100% conversion as equally worth fixing.
Same vital-few discipline as the rest of this catalogue — one weakest stage named with conviction, not a list of every stage with some loss.

6 · What it connects to

What it connects to

upstream

Sales funnel value stream map
The same stage-level thinking, applied with time data instead of counts — useful together when a stage is both losing deals and taking too long.

downstream

Deal A3
Once the weakest stage is named, a deal A3 is where you'd run root cause analysis on why that specific stage is losing deals, if it isn't already obvious.

7 · Where AI helps

Where AI helps

Judgement — stays yours

Deciding whether a stage's loss is a pattern worth acting on now or a one-quarter anomaly
Committing to which countermeasure to act on first

Analysis — AI helps

Drafting the narrative from rep/RevOps observation notes and the weakest-stage finding
Pressure-testing whether a proposed countermeasure actually addresses the named weakest stage

Drudgery — automated

Computing every stage's conversion rate and the rolled yield, with the arithmetic shown
Identifying the weakest stage from stage data
Exporting to xlsx in the house format

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