Renewal Pipeline Risk Scan

Scan the renewal book for accounts whose signals turned — declining intent, a competitor installed, a downsizing signal — so renewals get worked before they're at risk, not at the wire.

RevOps - Renewals

Renewals that turned in the data — flagged months before the renewal date

$1.4M
ARR at risk
9
Renewals flagged
AccountRenewalRisk driver
Acme - $120kSep 30Datadog installed
Beta - $90kAug 15Intent down 50%
Gamma - $200kOct 01Layoff signal
Why it lands
A renewal looks safe in the CRM until 30 days out. HG sees the account stop using the category and install a competitor months earlier — turning a fire drill into a planned save play.

Overview

Scan a pasted renewal book and flag accounts whose HG signals indicate elevated churn risk — declining category intent, a competitor's product newly installed, or negative operating signals — so RevOps and CS prioritize the renewals that need intervention now.

Use cases

  • Work renewals on signal, not on calendar

    Most renewal motions start 90 days out regardless of risk. This ranks the book by actual churn signal so the at-risk $200k renewal gets attention before the safe $20k one.

  • Hand CS a save list with evidence

    RevOps passes CS a ranked at-risk list where each flag cites the buyer's own behavior — declining intent, a competitor installed — so the save conversation starts from facts.

View workflow prompt
# Renewal Pipeline Risk Scan

## Parameters

- `{{renewal_book}}` *(required)* — Pasted renewals (account, domain, renewal date, ARR, product). Example: `Acme - acme.com - 2026-09-30 - $120k - Observability`
- `{{category}}` *(required)* — The category whose intent indicates engagement. Example: `observability`
- `{{competitors}}` *(optional)* — Competitor products whose appearance signals risk. Example: `Datadog, New Relic`

## Purpose
Scan {{renewal_book}} for churn risk by reading each account's {{category}} intent trajectory, watching for {{competitors}} newly installed, and checking operating signals — so the renewals that need a save play are worked months before the renewal date.

## Process
1. **Parse** — read {{renewal_book}} with renewal dates and ARR.
2. **Engagement trajectory** — `company_intent` for the {{category}}; falling intent on the category you sold them is an early disengagement signal.
3. **Competitor encroachment** — `company_technographic` + `company_install_time_series` to detect any {{competitors}} product newly installed or growing.
4. **Account health** — `company_operating_signals` for layoffs, budget freezes, or leadership churn that threaten the renewal.
5. **Score and time** — weight signals into a churn-risk score; rank by ARR × risk × proximity of renewal date so the biggest, soonest, riskiest renewals surface first.

## Output Format
Markdown with:
- `# Renewal Pipeline Risk Scan — {{category}}`
- `## At-Risk Renewals` (table: account | renewal date | ARR | risk driver | HG signal)
- `## Competitor Encroachment` (renewals where a competitor appeared)
- `## Save-Play Priority` (ranked by ARR x risk x timing)
- `## Citations`

## Quality Checklist
- Every risk flag cites a specific HG signal trajectory
- Competitor encroachment cites `company_technographic`/`company_install_time_series`
- Risk scoring weights ARR, severity, and renewal proximity
- Healthy renewals are not flagged just to pad the list