What kind of data does this framework require?

It works best with a mix of quantitative data like product usage and support tickets, alongside qualitative data such as CSM notes and executive engagement.

Can I customize the weights for different signals?

Yes, the framework includes a weighting and decay step where you can assign custom importance to usage, sentiment, and commercial data based on your specific business model.

How does this skill help prevent customer churn?

It provides a structured methodology to identify negative signals early, allowing teams to intervene with specific playbooks before a customer reaches a critical risk level.

Is this skill only for Customer Success teams?

While designed for CS, it is highly valuable for RevOps and Product teams looking to align on customer health definitions and prioritize feature development based on risk data.

Customer Success Risk Scoring Framework

Name: Customer Success Risk Scoring Framework
Author: gtmagents

bygtmagents

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分析与监控

Establishes a data-driven system for calculating customer health and identifying churn risks through quantitative and qualitative signals.

关于

The Risk Scoring Framework skill empowers Claude to help Customer Success and RevOps teams build sophisticated health scoring models. It guides users through inventorying product usage and sentiment signals, applying weighted decay models, and mapping scores into actionable risk tiers (Green/Yellow/Red). By aligning stakeholders on what constitutes a 'healthy' customer, this skill facilitates proactive churn prevention and identifies expansion opportunities through rigorous back-testing against churn and NPS outcomes.

主要功能

29 GitHub stars
Governance framework for long-term accountability and change management
Actionable health tier mapping with integrated playbook hooks
Multi-dimensional signal inventory including usage, sentiment, and support data
Weighted scoring models with time-based decay for data freshness
Validation loops to back-test scores against historical churn and expansion

使用场景

Designing a new customer health score for a SaaS platform
Aligning RevOps and CS teams on customer prioritization and intervention
Auditing existing churn data to refine risk indicators and weights

关于

主要功能

29 GitHub stars
Governance framework for long-term accountability and change management
Actionable health tier mapping with integrated playbook hooks
Multi-dimensional signal inventory including usage, sentiment, and support data
Weighted scoring models with time-based decay for data freshness
Validation loops to back-test scores against historical churn and expansion

使用场景

Designing a new customer health score for a SaaS platform
Aligning RevOps and CS teams on customer prioritization and intervention
Auditing existing churn data to refine risk indicators and weights