customer-success-manager
Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.
Profile →npx skills add alirezarezvani/claude-skills --skill customer-success-manager --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Customer Success Manager Production-grade customer success analytics with multi-dimensional health scoring, churn risk prediction, and expansion opportunity identification. Three Python CLI tools provide deterministic, repeatable analysis using standard library only -- no external dependencies, no API calls, no ML models. --- ## Table of Contents - [Input Requirements](#input-requirements) - [Output Formats](#output-formats) - [How to Use](#how-to-use) - [Scripts](#scripts) - [Reference Guides](#reference-guides) - [Templates](#templates) - [Best Practices](#best-practices) - [Limitations](#limitations) --- ## Input Requirements All scripts accept a JSON file as positional input argument. See `assets/sample_customer_data.json` for complete schema examples and sample data. ### Health Score Calculator Required fields per customer object: `customer_id`, `name`, `segment`, `arr`, and nested objects `usage` (login_frequency, feature_adoption, dau_mau_ratio), `engagement` (support_ticket_volume, meeting_attendance, nps_score, csat_score), `support` (open_tickets, escalation_rate, avg_resolution_hours), `relationship` (executive_sponsor_engagement, multi_threading_depth, renewal_sentime
- Table of Contents
- Input Requirements
- Health Score Calculator
- Churn Risk Analyzer
- Expansion Opportunity Scorer
- Output Formats
- How to Use
- Quick Start
- Workflow Integration
- Scripts
- 1. healthscorecalculator.py
- 2. churnriskanalyzer.py
- 3. expansionopportunityscorer.py
- Reference Guides
Health scoring python scripts/health_score_calculator.py assets/sample_customer_data.json python scripts/health_score_calculator.py assets/sample_customer_data.json --format json Churn risk analysis python scripts/churn_risk_analyzer.py assets/sample_customer_data.json python scripts/churn_risk_analyzer.py assets/sample_customer_data.json --format json Expansion opportunity scoring python scripts/expansion_opportunity_scorer.py assets/sample_customer_data.json python scripts/expansion_opportunity_scorer.py assets/sample_customer_data.json --format json python scripts/health_score_calculator.py customer_portfolio.json --format json > health_results.json
What does the customer-success-manager skill do?
Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill customer-success-manager --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.