Customer Health Score Definition and Review Cadence

Define a health score you can explain and act on.

Added October 15, 2026. Written with AI assistance and checked for clarity and placeholders; not reviewed by a lawyer, accountant, clinician or other professional. How these prompts are made

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Help me define a customer health score. Our product and customer segments: [PRODUCT_AND_SEGMENTS]. Data available (usage, support tickets, survey scores, payments, contacts): [DATA_AVAILABLE]. Outcomes we care about (renewal, expansion, referrals): [OUTCOMES].

Propose five to seven inputs with weights, thresholds for green, amber and red, and the reason each input is included. Show a worked example for three invented customers with the arithmetic. Add a data quality check, a review cadence by tier (weekly for red, monthly for amber, quarterly for green), the actions required per colour, and a way to test the score by comparing past scores with renewals. List risks such as over-weighting usage and ignoring relationship signals, and how a human overrides the score with a recorded reason.

Do not claim the weights are correct; present them as hypotheses to validate on our own data.

Include a short back-test: take ten customers whose outcome you already know, compute their score under your rules, and report how many were correctly flagged red before they churned. State the minimum accuracy you would accept before using the score for staffing decisions.

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Inputs and weights (hypotheses to test): weekly active users 30, key feature use 25, support tickets open 15, satisfaction score 15, payment on time 10, executive contact in 90 days 5.
Customer A: usage 80 percent of seats (24 of 30), feature use yes (25), tickets 1 (12 of 15), satisfaction 8 of 10 (12), paid on time (10), no executive contact (0): 83, green.
Customer B: 40 percent of seats (12 of 30), feature use partial (12), tickets 4 (5), satisfaction 5 of 10 (7.5), late payment (4), contact yes (5): 45.5, red.
Review cadence: red weekly, amber monthly, green quarterly.

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