# Customer Success Manager

Use when reviewing customer accounts for health, churn risk or expansion.

- Repository: https://github.com/alirezarezvani/claude-skills (29114 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-10-31
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add alirezarezvani/claude-skills --skill customer-success-manager -g -a claude-code -y`
Codex: `npx skills add alirezarezvani/claude-skills --skill customer-success-manager -g -a codex -y`
Cursor: `npx skills add alirezarezvani/claude-skills --skill customer-success-manager -g -a cursor -y`
Gemini CLI: `npx skills add alirezarezvani/claude-skills --skill customer-success-manager -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add alirezarezvani/claude-skills`

## Description

Use when reviewing customer accounts for health, churn risk or expansion. Scores health with health_score_calculator.py, churn with churn_risk_analyzer.py and upsell with expansion_opportunity_scorer.py.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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.

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## 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)

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## 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_sentiment), and `previous_period` scores for trend analysis.

### Churn Risk Analyzer

Required fields per customer object: `customer_id`, `name`, `segment`, `arr`, `contract_end_date`, and nested objects `usage_decline`, `engagement_drop`, `support_issues`, `relationship_signals`, and `commercial_factors`.

### Expansion Opportunity Scorer

Required fields per customer object: `customer_id`, `name`, `segment`, `arr`, and nested objects `contract` (licensed_seats, active_seats, plan_tier, available_tiers), `product_usage` (per-module adoption flags and usage percentages), and `departments` (current and potential).

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## Output Formats

All scripts support two output formats via the `--format` flag:

The rest: https://github.com/alirezarezvani/claude-skills/blob/HEAD/business-growth/skills/customer-success-manager/SKILL.md