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Customer Success · Version 1.3.0 · Reviewed 2026-08-02

Customer Health Score Designer

Improve signal validation and weighting method with evidence, explicit trade-offs, and a verification plan.

4 method steps 4 documented failure modes 4 diagnostic checks 7 quality gates

Builds health scores validated against actual churn rather than assembled from plausible signals.

₹99 one-time

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What this skill helps you do

  • Signal validation
  • Weighting method
  • Actionability

How Customer Health Score Designer works

You provide

Account history, usage signals, and the escalation context

It inspects

Whether signals precede or follow the decision in signal validation

It decides

A weighting method plan with commitments the delivering team agreed

You verify

Outcome measured against a matched control, not expectation

What it checks first

Customer Health Score Designer builds health scores validated against actual churn rather than assembled from plausible signals. Use it when the work involves Signal validation, Weighting method, Actionability.

  1. Whether the account signal reflects a decision already made or precedes it.
  2. Who the actual decision maker is versus who raised the escalation.
  3. What the customer needs to be true, rather than the remedy they requested.
  4. Whether context survives the handoff, since repeated explanation is the top escalation amplifier.

Failure modes it recognizes

  • An escalation handed off without the timeline, so the customer re-explains and frustration compounds.
  • A health score driven by usage decline that lags the churn decision by months.
  • Committing to a remedy the delivering team has not agreed to.
  • Treating a single vocal contact as representative of the whole account.

Answers it will reject

  • Offering a discount to resolve a trust problem, which delays rather than repairs it.
  • Escalating without stating what specifically is being asked for and by when.
  • Closing on the customer going quiet, which is frequently the strongest churn signal.

Decision rules it applies

  • Carry the full timeline and prior commitments through every handoff.
  • Confirm the remedy with the delivering owner before communicating it.
  • Separate what the customer requested from the outcome they actually need.

Evidence it asks for

  • Test each health signal against accounts that already churned, using pre-decision data.
  • Track time-to-first-substantive-response separately from time-to-resolution.
  • Measure interventions against a matched control rather than against expectation.

The method inside

  1. Reconstruct the customer journey and promised outcomes
  2. Separate activity volume from outcome and risk signals
  3. Identify the blocked dependency and accountable owner
  4. Create a jointly verifiable recovery or expansion plan

Deliverables

  • Signal validation account brief
  • Weighting method risk and dependency map
  • Actionability action plan

Evidence requirements

  • Success plan, adoption data, support history, and meeting notes
  • Renewal date, stakeholders, expected outcomes, and risks
  • Verified customer commitments and unresolved dependencies

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Design a customer health score. We have usage, support tickets, NPS, and login frequency available.

Expected output

Assemble it backwards from churned accounts rather than forwards from available signals, or you will encode assumptions. Test each candidate against data from before the churn decision window, and keep only signals that separate churned from retained...

Boundaries and compatibility

Ideal for

  • Signal validation: produce a decision or artifact grounded in supplied evidence.
  • Weighting method: produce a decision or artifact grounded in supplied evidence.
  • Actionability: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Inferring customer sentiment without evidence
  • Hiding unresolved product or service failures

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.