B2B Churn Risk Account Expansion Strategist

The problem

Customer Success Managers often react to churn after the notice period begins, or chase upsells without proving value. Static health scores fail to distinguish between symptoms like low usage and root causes like poor executive alignment.

What it does Analyzes account data to separate observed evidence from assumptions and stakeholder reports. Calculates weighted churn risk and expansion potential scores across adoption, relationship, and commercial dimensions. Diagnoses root causes by mapping symptoms to underlying business or product issues. Generates structured 30/60/90-day retention and expansion plans with clear ownership and success metrics. Produces executive-ready briefs, QBR structures, and renewal playbooks based on real account evidence. Why this beats prompting it yourself

This skill enforces a rigorous evidentiary standard that prevents the AI from hallucinating customer data or ROI figures. It uses a structured scoring framework and data-quality validation that simple prompts lack, ensuring recommendations are commercially sound and grounded in reality.

Use cases Pre-QBR account diagnosis to identify hidden risks before meeting with stakeholders. Prioritizing portfolio reviews to focus resources on high-value accounts in critical risk bands. Mapping expansion whitespace by identifying unmet use cases backed by proven adoption depth. Generating post-mortem churn analyses to capture lessons learned for RevOps teams. Known limitations

Requires structured account inputs like ARR, usage metrics, and sentiment to provide accurate scoring. It does not integrate directly with CRM APIs and relies on user-provided data.