Analyze · Pipeline Review & Deal Risk

Identify At-Risk Deals in This Week's Pipeline

Scan your open pipeline for risk signals and return a ranked list with the why.

managerfounderBeginner⏱ 45 min/week
When to use
Use mid-week when you want a fast read on which deals are quietly dying. Best when your CRM has last_activity_date, stage_entered_date, and amount. Pairs with the weekly review prompt — this one drills deeper into the 'at-risk' bucket.
The prompt
You are a skeptical sales manager at a digital marketing agency. You have seen every flavor of happy ears and you assume a deal is at risk until the rep proves otherwise.
Agency: [AGENCY_NAME] — [SERVICES]
Average sales cycle: [SALES_CYCLE_DAYS] days
What 'at risk' means here: [RISK_DEFINITION]
Pipeline export:
[PIPELINE_EXPORT]
Scan every open deal in the export. Return a ranked at-risk list (highest risk first) with a short, evidence-based reason per deal.

- ONLY use deals present in [PIPELINE_EXPORT]. Never invent.
- Risk reasoning must cite a specific field value (e.g. 'no activity for 21 days', 'stage age 38 days vs cycle 42').
- If two deals tie, break tie by amount (bigger = higher rank).
- Mark uncertainty as 'unclear — missing [field]' instead of guessing.
- Do NOT recommend actions in this output — that's a different prompt.

| Rank | Deal | Owner | Amount | Stage | Risk Score (H/M/L) | Evidence |
|------|------|-------|--------|-------|--------------------|----------|

Below the table: 1-line note on any data quality gaps you noticed.
Variables
  • [AGENCY_NAME] — Your agency name
  • [SERVICES] — Services you sell
  • [SALES_CYCLE_DAYS] — Average sales cycle length in days
  • [RISK_DEFINITION] — Your house rules — e.g. 'no activity >14 days', 'stage age >1.5x avg', 'single-threaded'
  • [PIPELINE_EXPORT] — CSV pipeline export with at minimum: deal, owner, amount, stage, close_date, last_activity_date, stage_entered_date
Example input
Agency: Northwind Digital — SEO + paid social
Sales cycle: 42 days
Risk definition: no activity >14 days, OR stage age >60 days, OR close_date in past
Pipeline export:
deal,owner,amount,stage,close_date,last_activity_date,stage_entered_date
Acme Roofing,Jamie,6500,Proposal,2026-05-22,2026-05-18,2026-05-02
BlueTrail Law,Priya,4000,Discovery,2026-05-30,2026-05-09,2026-03-12
Cedarworks,Jamie,15000,Negotiation,2026-05-15,2026-05-20,2026-05-10
DeltaFit,Marcus,2500,Discovery,2026-06-10,2026-04-28,2026-04-02
Example output
| Rank | Deal | Owner | Amount | Stage | Risk | Evidence |
| 1 | BlueTrail Law | Priya | $4,000 | Discovery | H | Stage age 74 days vs 42-day cycle; last activity 16 days ago |
| 2 | DeltaFit | Marcus | $2,500 | Discovery | H | 27 days no activity; stage age 53 days |
| 3 | Cedarworks | Jamie | $15,000 | Negotiation | M | Close date 5/15 already past — but activity 5 days ago suggests live |
| 4 | Acme Roofing | Jamie | $6,500 | Proposal | L | Within cycle; recent activity |

Data quality note: no champion field in export — can't assess single-threaded risk. Recommend adding 'primary_contact' column.
Pro tips
  • Define your house risk rules ONCE and reuse them — consistency matters more than perfection.
  • If you don't have stage_entered_date in your CRM, this prompt's accuracy drops by half. Worth adding.
  • Run this Tuesday — gives reps 3 days to react before Friday forecast.
Works with
ClaudeChatGPTGemini
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