Analyze · Conversion / Funnel Analysis

Analyze Time-in-Stage by Deal Type

Measure how long deals sit in each stage broken down by deal type to find what's slowing your cycle.

managerfounderAdvanced⏱ 4-5 hours of pivot table work
When to use
Run when sales cycle is creeping up and you can't tell whether it's specific deal sizes, services, or segments causing it. Best run quarterly with at least 12 deals per deal-type segment. Output should inform stage SLAs and forecast assumptions.
The prompt
You are a sales operations analyst at a digital marketing agency. You measure velocity, not just conversion, and explain where the days are going.
Agency: [AGENCY_NAME] — [SERVICES] | Period: [PERIOD] | Deal Type Segmentation: [SEGMENTATION] | Data:
[FUNNEL_DATA]
For each deal type segment, calculate average days in every stage and identify which segment x stage combinations are dragging the overall cycle longer than the company median.

- Use only [FUNNEL_DATA]; report median AND average so outliers are visible.
- Compute and show the company-wide median per stage as the comparison baseline.
- Flag any segment with fewer than 12 deals at that stage as low-sample.
- For each above-median offender, name one cycle-shortening action (e.g., introduce SLA, reduce signers, pre-sell scope).

A matrix with rows = deal type segments, columns = stages, cells = avg days (median in parens). Below the matrix, a ranked list of the top 5 segment x stage offenders with one action each.
Variables
  • [AGENCY_NAME] — Your agency name
  • [SERVICES] — Service lines
  • [PERIOD] — Date range
  • [SEGMENTATION] — How to slice deals: size, service, segment, region
  • [FUNNEL_DATA] — Per-segment per-stage days-in-stage data
Example input
Agency: SignalPath — PPC + SEO | Period: 2026 YTD | Segmentation: SMB ($15k/mo) | Data:
SMB: Disc 4d, Prop 9d, Neg 5d (n=28)
Mid-Mkt: Disc 7d, Prop 16d, Neg 9d (n=22)
Ent: Disc 12d, Prop 31d, Neg 24d (n=8)
Example output
Company medians: Disc 6d, Prop 14d, Neg 8d.

| Segment | Discovery | Proposal | Negotiation |
|---|---|---|---|
| SMB | 4d | 9d | 5d |
| Mid-Mkt | 7d | 16d | 9d |
| Enterprise* | 12d | 31d | 24d |
*Low sample (n=8) — directional only.

Top offenders:
1. Enterprise x Proposal (31d vs 14d) — introduce mutual action plan with signing timeline at proposal send.
2. Enterprise x Negotiation (24d vs 8d) — confirm signer + procurement path before proposal.
3. Mid-Mkt x Proposal (16d vs 14d) — small gap; add 10-day proposal SLA.
4. Enterprise x Discovery (12d vs 6d) — book second-meeting before ending discovery.
5. (none) — SMB is below median across the board.
Pro tips
  • Median matters more than average for time-in-stage — one stalled deal can blow the average.
  • If Enterprise consistently runs 2x the cycle, build a separate forecast assumption rather than averaging into one number.
  • Time-in-stage spikes often correlate with missing signer info — capture it earlier.
Works with
ClaudeChatGPTGemini
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