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Prompt Details

Model
Chat - (gpt-5.6)
Token size
334
Example input
[COMPANY]: SentryGate - compliance automation [CUSTOMER]: Northbridge Capital, financial services [USAGE]: 3 teams, $50k annual contract [RISK]: Usage dropped 30% last quarter. Champion left. [GOAL]: Retain and expand
Example output
STEP 1 — HEALTH SCORE MODEL - Usage (30%): Frequency, depth, and breadth of usage. - Engagement (20%): Logins, feature adoption, training completion. - Support (15%): Ticket volume, severity, resolution time. - Sentiment (20%): NPS, email tone, meeting feedback. - Outcome (15%): ROI metrics, goals achieved. STEP 2 — 10 SIGNALS TO TRACK 1. Weekly active users — threshold: <50% of seats. 2. Feature adoption — threshold: <3 features used. 3. Login frequency — threshold: <3x per week. 4. Support tickets — threshold: >5 in 30 days. 5. Champion activity — threshold: no contact in 14 days. 6. Meeting attendance — threshold: miss 2 in a row. 7. NPS score — threshold: <7. 8. Invoice payment — threshold: >15 days late. 9. Contract renewal date — threshold: <90 days. 10. Executive sponsor — threshold: no contact in 30 days. STEP 3 — INTERVENTION PLAYBOOKS - Low health (0-40): Emergency retention — trigger: score <40. Action: exec sponsor call + ROI review. Outcome: retain or exit interview. - Medium health (41-70): Proactive engagement — trigger: score 41-70. Action: QBR + training. Outcome: increase usage. - High health (71-100): Expansion opportunity — trigger: score >71. Action: expansion proposal. Outcome: upsell. STEP 4 — 30-DAY MONITORING PLAN - Week 1: Health score baseline. Owner: CSM. Metric: score documented. - Week 2: Signal tracking. Owner: CSM. Metric: 10 signals logged. - Week 3: Intervention (if needed). Owner: CSM. Metric: action taken. - Week 4: Review + adjust. Owner: CS lead. Metric: score improved. STEP 5 — RETENTION SCORE Score: 5/10. Champion loss and usage drop are significant risks. Action: Schedule exec sponsor call within 7 days.
GPT

B2b Customer Health Score System

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GPT-5.6
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Stop losing customers you didn't see slipping. This prompt builds a complete customer health score system using behavioral signals and the MEDDIC framework. You get: a health score model, 10 signals to track, 3 intervention playbooks, and a 30-day monitoring plan. It also scores each account on retention and expansion likelihood. Built for CS leaders and Account Managers who want to predict churn before it happens. Works with ChatGPT, Claude, any GPT.
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Added 6 days ago
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