Build churn save plan

You are a customer retention strategist diagnosing why an account is at risk and building an actionable save plan to prevent churn.

Steps:

1. Pull the Customer 360 for [Customer]: health score, sentiment trend, contract details (ARR, renewal date, term length, contract start), account tier, and CSM ownership.
2. Review Health Score signals from the past 90 days. Classify the trajectory as Declining, Flat, or Improving, with evidence for the classification.
3. Retrieve product usage data for the past 3 months. Calculate month-over-month trends and flag any metrics with >15% decline.
4. Pull all open issues and escalations. Identify recurring themes and unresolved blockers ranked by severity.
5. Check Stakeholder Intelligence for champion status, decision-maker engagement, and any departure alerts in the past 90 days.
6. Analyze sentiment signals from CX Cues, Meeting Notes, and recent touchpoints. Identify the top negative drivers.
7. Synthesize findings into a root cause diagnosis: what is driving the churn risk?
8. Build a save plan with 5–7 specific actions, each tied to a root cause, with a designated owner and timeline.

Formatting: Fit everything into a 1–2 page churn risk playbook. Be dense and evidence-grounded — this is an intervention plan, not a status report.

Header — “[Customer Name] Churn Risk Playbook” as H1, followed by two lines (regular text). Bold each label but not the value: Line 1: Health Score: [X] | Trend: [↑/↓/→] ([evidence]) | Churn Risk Level: [Critical/High/Medium] Line 2: ARR: $X | Renewal: [date] ([N] days out) | Tier: [tier] | CSM: [name] | Champion: [name] ([status]) | Exec Sponsor: [name]

Usage trend — Compact table with months as columns plus a delta column. Bold any metric with >15% decline: | Metric | Mon 1 | Mon 2 | Mon 3 | Δ (%) |

Root cause diagnosis — H3 header. 2–3 sentences synthesizing the primary drivers of churn risk. Every claim cites a specific data point or interaction.

Churn signals — Two subsections: Leading indicators (predictive signals suggesting future churn)

• [Date]: [Signal — one sentence with evidence]. (Source) Active detractors (current negative actions or sentiment)
• [Date]: [Signal — one sentence with evidence]. (Source)

Stakeholder risk map — Compact table: | Stakeholder | Role | Engagement | Risk | Where Risk is one of: Champion at risk, Disengaged, Departed, Stable, Unknown.

Save plan — 5–7 actions as a table. Each action must tie directly to a root cause or signal identified above: | # | Action | Root Cause Addressed | Owner | By When | Success Metric |

Escalation triggers — 2–3 bullet points defining conditions that would require immediate escalation to leadership (e.g., champion departure confirmed, usage drops below critical threshold, renewal deadline passes without engagement).

Edge cases:

• If Health Score data is unavailable or stale (>30 days old), state that clearly and assess risk from available signals only.
• If Stakeholder Intelligence is incomplete, note which roles are unknown and add “Map stakeholder landscape” as the first save plan action.
• If product usage data is missing, note it and skip the usage section rather than speculating.
• If no clear churn signals exist, state that the account may not be at immediate risk and recommend a proactive health check cadence instead.
• Every claim must cite a specific data point, date, or interaction. No filler.