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customer-success-manager

Analyze customer data to score health, predict churn, and identify expansion opportunities.

Updated Mar 7, 2026
Search Tags:#SaaS metrics#customer success#health scoring#customer retention#churn prediction#expansion opportunities
One-click install
npx skills add https://github.com/tapanshah/Claude-Skills --skill customer-success-manager-tapanshah
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customer-success-manager
Source: https://github.com/tapanshah/Claude-Skills/tree/main/business-growth/customer-success-manager
Command: npx skills add https://github.com/tapanshah/Claude-Skills --skill customer-success-manager-tapanshah

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps Customer Success Managers proactively identify at-risk customers, pinpoint expansion opportunities, and improve overall customer health by analyzing key metrics.

Core Features & Use Cases

  • Health Scoring: Continuously monitors customer health across usage, engagement, support, and relationship dimensions.
  • Churn Prediction: Identifies customers at high risk of churn based on behavioral signals and commercial factors.
  • Expansion Identification: Pinpoints upsell, cross-sell, and new department adoption opportunities.
  • Use Case: A CSM can use this Skill to get a prioritized list of customers needing immediate attention, along with specific recommended actions, before their next check-in.

Quick Start

Analyze the customer data in 'customer_portfolio.json' to identify churn risks and expansion opportunities.

Frequently Asked Questions about customer-success-manager

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is multi-dimensional health scoring and how does it work for customer retention?▼

Multi-dimensional health scoring evaluates customer data across usage, engagement, support, and relationship dimensions. This framework continuously monitors SaaS metrics to provide a comprehensive view of account stability and highlight behavioral signals.

Does this customer success analytics approach require external Python dependencies?▼

Analyzing a customer portfolio involves processing JSON data through Python CLI tools to generate a prioritized list of accounts needing attention. This deterministic analysis outputs specific recommended actions based on health scores and churn risk.

How do I analyze a customer portfolio to prioritize accounts for immediate check-ins?▼

No external Python dependencies are required. The customer success analytics and health scoring frameworks run entirely using Python's standard library, utilizing deterministic CLI tools to process SaaS metrics without external packages.

What is multi-dimensional health scoring and how does it work for customer retention?▼

Yes, standard Python scripts analyze customer data to pinpoint upsell, cross-sell, and new department adoption opportunities. The CLI tools process commercial factors and engagement metrics to identify expansion potential across the portfolio.

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