Can I use the output for automated reporting?

Yes, all tools support a --format json flag, making it easy to pipe analysis results into other business intelligence tools or automated reporting pipelines.

How are churn risk tiers defined?

The analyzer categorizes accounts into Critical, High, Medium, and Low risk tiers based on signals like usage decline, engagement drops, and commercial factors.

Does this skill require an external database or CRM connection?

No, it operates locally on JSON data snapshots using Python scripts, requiring no external API calls or direct CRM integrations.

Is any machine learning used for these predictions?

No, the skill uses deterministic, weighted algorithmic scoring to ensure results are repeatable, explainable, and consistent across every run.

What metrics are used to calculate the customer health score?

The health score is calculated using four dimensions: product usage (30%), engagement (25%), support ticket performance (20%), and relationship sentiment (25%).

Customer Success Manager

Name: Customer Success Manager
Author: zhangzhang-111-i

byzhangzhang-111-i

0•

Analytics & Monitoring

Analyzes SaaS customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models.

The Customer Success Manager skill provides a robust framework for managing SaaS customer portfolios through data-driven analysis. By leveraging three specialized Python tools, it calculates deterministic health scores across dimensions like usage and engagement, identifies critical churn risks through behavioral signal detection, and prioritizes expansion opportunities for upselling. This skill is designed for Customer Success teams who need repeatable, transparent metrics to drive retention and growth strategies without the complexity of external API integrations or black-box ML models.

Key Features

01Multi-dimensional health scoring based on usage, engagement, and support metrics

020 GitHub stars

03Tier-based churn risk analysis with weighted behavioral signal detection

04Automated identification of upsell, cross-sell, and expansion opportunities

05Deterministic Python-based analysis with both text and JSON output formats

06Pre-built templates for QBRs, success plans, and onboarding checklists

Use Cases

01Generating data-driven insights and metrics for Quarterly Business Reviews (QBRs)

02Ranking customer segments by expansion potential to optimize sales and CSM outreach

03Conducting weekly portfolio health audits to identify and prioritize at-risk accounts

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zhangzhang-111-i/claude-skills111 customer-success-manager

For use in Claude.ai and ChatGPT

Key Features

01Multi-dimensional health scoring based on usage, engagement, and support metrics

020 GitHub stars

03Tier-based churn risk analysis with weighted behavioral signal detection

04Automated identification of upsell, cross-sell, and expansion opportunities

05Deterministic Python-based analysis with both text and JSON output formats

06Pre-built templates for QBRs, success plans, and onboarding checklists

Use Cases

01Generating data-driven insights and metrics for Quarterly Business Reviews (QBRs)

02Ranking customer segments by expansion potential to optimize sales and CSM outreach

03Conducting weekly portfolio health audits to identify and prioritize at-risk accounts

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zhangzhang-111-i/claude-skills111 customer-success-manager

For use in Claude.ai and ChatGPT