Close-Date Realism Check

Test every close date against buyer behavior — a deal closing this month should have a buyer who's researching this month. The ones that don't get flagged.

RevOps - Forecasting

A deal closing this month should have a buyer researching this month

5
Close dates flagged
2
Pull-forward candidates
DealCloseIntent verdict
Acme - $80kJun 15Cold - likely slip
Beta - $120kSep 30Hot - pull forward
Gamma - $60kJun 20Active - holds
Why it lands
The deal set to close in two weeks shows a buyer who stopped researching the category a month ago. The deal set to close next quarter has a buyer researching hard right now. The close dates are backwards.

Overview

Cross-reference each deal's close date against the account's current HG intent activity — the principle that an imminent close should coincide with active buyer research — and flag deals whose close date and buyer behavior disagree, the leading indicator of slip.

Use cases

  • Predict slips before the forecast call

    A near-term close with a cold buyer is the textbook slip. Intent recency catches it weeks before the deal misses, while there's still time to re-engage or re-date.

  • Find the deals you can pull forward

    Some of next quarter's pipeline has buyers acting hot right now. Surfacing those pull-forward candidates lets reps accelerate the deals the buyer is already ready for.

View workflow prompt
# Close-Date Realism Check

## Parameters

- `{{deals}}` *(required)* — Pasted deals (deal, domain, stage, amount, close date, last activity date). Example: `Acme - acme.com - Commit - $80k - 2026-06-15 - last activity 2026-05-25`
- `{{category}}` *(required)* — The category whose intent should be active near a close. Example: `marketing automation`

## Purpose
For each deal in {{deals}}, test whether the close date is realistic by comparing it to the account's current {{category}} intent — a deal closing in two weeks should show a buyer actively researching now. Flag the mismatches before they slip.

## Process
1. **Parse** — read {{deals}} with close dates and last-activity dates.
2. **Intent recency** — `company_intent` + `intent_category` for the {{category}} per domain; note whether intent is active in the last 30 days.
3. **Mismatch test** — flag deals where close is imminent (<30 days) but intent is cold, and deals where close is far but intent is hot (potential pull-forward).
4. **Activity corroboration** — compare last-activity date to the close date; a near-term close with stale activity compounds the risk.
5. **Recommend** — for each flagged deal, recommend re-date, accelerate, or inspect, with the signal behind it.

## Output Format
Markdown with:
- `# Close-Date Realism Check — {{category}}`
- `## Realism Flags` (table: deal | close date | intent recency | verdict)
- `## Likely Slips` (imminent close, cold buyer)
- `## Pull-Forward Candidates` (far close, hot buyer)
- `## Citations`

## Quality Checklist
- Every flag compares close date to dated intent recency
- Intent recency cites `company_intent`/`intent_category` with a date
- Pull-forward candidates are surfaced, not just slips
- Verdicts are actionable (re-date / accelerate / inspect)