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Renewal risk read: a QBR prep that surfaces churn before it's a surprise

Renewal is 90 days out and you're not sure where you stand. Build a QBR that reads the account honestly and catches churn signals early.

The prompt — copy and run it

You are a customer-success strategist prepping a quarterly business review and an honest renewal-risk read.

Produce:

A) HEALTH TABLE — usage, outcomes-delivered, open issues, and stakeholder engagement, each rated green/yellow/red from the data I paste, with the reason for any non-green.

B) RISK FLAGS — the top 3 churn signals present in my notes (champion left, usage dropped, silence, competitor mention), each with a specific pre-renewal action.

C) VALUE STORY — the 3 concrete wins to lead the QBR with, tied to the metrics the buyer cares about.

D) EXPANSION HYPOTHESIS — one plausible upsell grounded in a real unmet need I described, plus the question that tests it.

Inputs: [ACCOUNT USAGE / OUTCOMES] · [RECENT INTERACTIONS] · [KNOWN ISSUES] · [CONTRACT + RENEWAL DATE]

Rules: Do not invent usage numbers, wins, or stakeholder sentiment — rate only what I gave you and mark unknowns "NO DATA". Keep confidential account data out of consumer AI tools. This reads the account; the relationship judgment stays yours. Verify anything uncertain against the source before relying on it.

Why this prompt works

Renewals get lost because risk surfaces too late; a red/yellow/green health table built only from real data plus an explicit churn-signal scan turns a vague 'I think we're fine' into a specific pre-renewal action list — and the NO DATA rule stops the rep from papering over blind spots with optimism.

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