---

name: health-diagnostic
description: "Run a customer health diagnostic that surfaces churn risk 90 days before renewal — so you're saving accounts, not watching them leave."

/health-diagnostic

"How are things going?" produces "Things are great, thanks!" from a customer who has already started evaluating your competitor. By the time you see the cancellation request, the decision was made 90 days ago — during a leadership change you didn't know about, or a product gap that accumulated into resentment, or an adoption drop-off that nobody flagged. This skill forces a structured diagnostic using behavioral signals and business context, not survey responses, to produce an honest renewal probability 90 days before you need it.

The Adoption Metric That Actually Predicts Renewal

• What is the one product behavior that, if happening regularly, predicts renewal at 90%+ rates in your customer base? (Not login frequency — the specific workflow that delivers your core value)
• Example: "Accounts where 3+ users run a report weekly renew at 94%. Accounts where only the admin logs in renew at 41%."
• What is this customer's current adoption level against that threshold?
• Is adoption trending up, flat, or declining over the last 60 days?
• If you don't know this predictive metric, stop here — that's the first thing to build before the next QBR season

Stakeholder Engagement — The Hidden Churn Signal

• Who was the original business sponsor when this account was signed? Are they still in role?
• If the original sponsor has left or been promoted away, who owns the relationship now? Have you met them?
• When was the last time you had a conversation with someone at this account above the day-to-day user?
• Is your champion actively talking about the product internally, or have they gone quiet?
• A disengaged champion isn't a soft signal — it's a 60-day churn warning

Business Change Detection

• What has changed in this customer's business in the last 6 months? (Layoffs, acquisition, new leadership, funding, budget cuts, strategy shift)
• Did any of those changes reduce the urgency of the problem your product solves?
• Is there a new decision-maker at this account who didn't choose you and has no loyalty to the incumbent vendor?
• What are they publicly saying about priorities? (LinkedIn, press releases, job postings are faster signals than QBR calls)

Unmet Needs

• What did this customer ask for in the last 6 months that you haven't delivered?
• Are they using a workaround or a competing product to fill that gap right now?
• How many support tickets have they submitted, and what category? (High ticket volume for the same issue is a churn predictor, not a support metric)
• What did they say they'd need to expand — and have those conditions been met?

The Honest Renewal Probability

• Given the above, assign a renewal probability: High (85%+), Medium (50-85%), Low (<50%)
• Name the one factor most driving that rating
• If Medium or Low: what is the specific intervention that could move it up? Who owns it? What's the timeline?
• If you'd rate it High but haven't talked to anyone above the day-to-day user in 90 days, downgrade it to Medium — you don't have enough signal

Rules

1. This diagnostic must use behavioral data — adoption metrics, login data, ticket history — not just qualitative impressions
2. Stakeholder mapping is mandatory — a renewal probability without confirming the original sponsor is still engaged is unreliable
3. Business change detection must be completed before the renewal conversation — you cannot walk in without knowing what's changed in their world
4. Every Medium and Low account must have a named intervention with a specific owner and date
5. "They seem happy" is not a health signal — name a behavioral metric

This diagnostic produces an honest health score with specific evidence, a named renewal risk factor, and a concrete next action for every at-risk account — before the customer is already gone.