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customer-success-manager

Analyze customer accounts to score health, churn risk, and expansion potential from JSON inputs.

Updated Apr 24, 2026
Search Tags:#saas#health-scoring#customer-success#retention-analysis#churn-risk#qbr#expansion-revenue
One-click install
npx skills add https://github.com/Veloxia-agency/VELOXIA-WEB --skill customer-success-manager-veloxia-agency
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customer-success-manager
Source: https://github.com/Veloxia-agency/VELOXIA-WEB/tree/main/.claude/skills/business-growth/skills/customer-success-manager
Command: npx skills add https://github.com/Veloxia-agency/VELOXIA-WEB --skill customer-success-manager-veloxia-agency

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 teams understand account health, anticipate churn risk, and prioritize expansion work without manual spreadsheet analysis.

Core Features & Use Cases

  • Health scoring: Calculates weighted customer health across usage, engagement, support, and relationship signals.
  • Churn risk analysis: Flags at-risk accounts, ranks warning signals, and recommends intervention playbooks by severity.
  • Expansion discovery: Identifies upsell, cross-sell, seat expansion, and department expansion opportunities with estimated revenue and priority.
  • Use case: Use it when preparing QBRs, reviewing renewal risk, triaging a portfolio of accounts, or finding where healthy customers are ready for growth conversations.

Quick Start

Ask the skill to analyze your customer JSON file and return health scores, churn tiers, and expansion recommendations for the portfolio.

Frequently Asked Questions about customer-success-manager

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

FAQPage Schema
How do I predict SaaS churn risk and score customer health without manual spreadsheet analysis?▼

You can predict SaaS churn risk by analyzing customer accounts with deterministic Python CLI scripts that calculate weighted health scores across usage, engagement, support, and relationship signals, flagging at-risk accounts and ranking warning signals by severity.

What is the best way to prepare for QBRs and renewal reviews across enterprise and SMB segments?▼

The best way to prepare for QBRs and renewal reviews is to analyze your structured customer JSON file to generate health scores, churn tiers, and expansion recommendations, triaging portfolios across enterprise, mid-market, and SMB segments.

How do I identify expansion revenue opportunities like upsell and cross-sell in my customer portfolio?▼

You identify expansion revenue opportunities by analyzing customer accounts to discover upsell, cross-sell, seat expansion, and department expansion opportunities, returning estimated revenue and priority rankings for healthy accounts ready for growth.

Can I use this customer success analysis tool with text inputs or does it require structured JSON?▼

You must provide structured JSON inputs for the deterministic Python CLI analysis to calculate health scores, but the tool supports both text and JSON output formats for returning churn tiers and expansion recommendations.

When do I need automated churn risk analysis instead of manual customer success monitoring?▼

You need automated churn risk analysis when triaging a large portfolio of accounts for retention monitoring or renewal preparation, replacing manual spreadsheet analysis with deterministic scoring scripts that recommend intervention playbooks by severity.

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