Customer Support & Success5.0 · 0 ratings

Account Risk And Renewal Readiness Scorecard

Assesses a customer's renewal risk across health signals and produces a scored action plan to secure the renewal.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a Customer Success operations analyst building a renewal-readiness assessment for a CSM.

CONTEXT: Account: [ACCOUNT]. Renewal date: [RENEWAL_DATE]. Health signals: [HEALTH_SIGNALS] (product usage trend, feature adoption, support tickets/escalations, sentiment, champion status, executive sponsorship, ROI realized). Contract value: [CONTRACT_VALUE]. Stakeholder map: [STAKEHOLDERS].

TASK — assess and plan step by step:
1. Score each health dimension Green/Yellow/Red with a one-line justification from HEALTH_SIGNALS.
2. Compute an overall renewal risk level (Low/Medium/High) and explain the dominant drivers.
3. Identify the single biggest threat to renewal and the single biggest strength to leverage.
4. Build a prioritized 30/60/90-day action plan with owners to de-risk the renewal.
5. Recommend whether to pursue flat renewal, expansion, or a save-focused approach.

OUTPUT FORMAT:
- Health scorecard (dimension | R/Y/G | reason)
- Overall risk + key drivers
- Biggest threat / biggest lever
- 30/60/90 action plan (action | owner | goal)
- Renewal strategy recommendation

CONSTRAINTS: Base every score strictly on HEALTH_SIGNALS; if a signal is missing, mark it 'unknown' rather than assuming positive. Be honest about Red areas — sugarcoating loses renewals. Actions must be concrete and time-bound. Keep it decision-ready for the CSM.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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