Customer success & support

Customer Health Score Analysis & Proactive Risk Identification

A comprehensive framework for Customer Success Managers to evaluate account health, identify latent churn risks, and develop strategic intervention plans. It transforms raw usage and sentiment data into actionable retention strategies.

5 blanks to fill in · Added May 2024 · churn-prevention · retention-strategy · customer-health · risk-mitigation · account-management

The prompt

5 blanks

You are a Senior Customer Success Strategic Analyst specializing in churn prevention and account optimization. Your objective is to perform a deep-dive health analysis for [CUSTOMER NAME OR SEGMENT] based on the provided data points. Please analyze the following inputs: 1. Product Usage Data: [INSERT KEY METRICS SUCH AS MAU/DAU, FEATURE ADOPTION, OR API CALLS]. 2. Support History: [INSERT RECENT TICKET VOLUME, TICKET SEVERITY, AND TIME TO RESOLUTION]. 3. Relationship & Sentiment: [INSERT NPS/CSAT SCORES, LAST QBR FEEDBACK, OR RECENT SENTIMENT ANALYSIS]. 4. Financial Context: [INSERT RENEWAL DATE, CONTRACT VALUE, AND EXPANSION HISTORY]. Your analysis must include: A) Holistic Health Score (Scale 1-100) with a detailed breakdown of the scoring logic. B) Risk Identification: Categorize risks into Product (lack of value), Operational (champion departure), or Financial (budget cuts). C) Trend Analysis: Determine if the account is improving, stabilizing, or deteriorating. D) Strategic Playbook: Provide 3-5 immediate, actionable steps to mitigate risks or capitalize on expansion opportunities. E) Executive Summary: A concise brief for leadership regarding the account's long-term viability.

Open in ChatGPT

Blanks: Customer name or segment · Insert key metrics such as mau/dau, feature adoption, or api calls · Insert recent ticket volume, ticket severity, and time to resolution · Insert nps/csat scores, last qbr feedback, or recent sentiment analysis · Insert renewal date, contract value, and expansion history

How to use it

Use this prompt when preparing for Quarterly Business Reviews (QBRs), renewal discussions, or when a sudden drop in product engagement is detected. It is most effective when populated with specific, quantitative data from your CRM and product analytics tools.

Tips

Include recent competitive mentions if the customer has expressed interest in other tools.
Segment data by user roles (e.g., admin usage vs. end-user usage) for a more granular health view.
Mention any recent technical outages or bugs that specifically affected this account.
Cross-reference the health score with the original 'Success Goals' defined during the sales handoff.
Use the output to create an automated internal alert for the Account Executive and CSM.

Information Gathering Requirements

To get the best results, provide specific metrics rather than generalizations. Instead of saying 'low usage,' provide the percentage drop over the last 30 days. Include qualitative context like 'Primary Champion left the company' as these are high-weight risk factors.

Output Framework and Structure

The output is structured to move from data synthesis to actionable intelligence. The Strategic Playbook section uses a 'Problem-Action-Impact' format to ensure that the recommendations are not just theoretical but ready for immediate implementation.

Context and Considerations

Consider the customer's lifecycle stage. A new customer with low usage has an 'onboarding risk,' while a 3-year customer with low usage has a 'value realization risk.' Ensure the prompt reflects these nuances in the input data.