customer-success-manager

Scores customer health, churn risk, and expansion opportunities from JSON account data.

1|Updated May 6, 2026
One-click install
npx skills add https://github.com/surfingalien/FinSurfing --skill customer-success-manager-surfingalien
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: customer-success-manager
Source: https://github.com/surfingalien/FinSurfing/tree/main/business-growth/skills/customer-success-manager
Command: npx skills add https://github.com/surfingalien/FinSurfing --skill customer-success-manager-surfingalien

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve? Customer success teams lack a consistent, repeatable way to quantify account health, detect churn risk early, and prioritize expansion revenue across a SaaS portfolio. This Skill replaces gut-feel account reviews with deterministic weighted scoring models that run locally on exported customer data. ## Core Features & Use Cases - Multi-Dimensional Health Scoring: Weights usage (30%), engagement (25%), support (20%), and relationship (25%) signals into a 0-100 score with Green/Yellow/Red classification, segment-aware benchmarks, and trend analysis against previous periods. - Churn Risk Analysis: Scores five risk signal categories, applies a renewal-urgency multiplier based on days to contract end, and outputs tiered intervention playbooks (Critical/High/Medium/Low). - Expansion Opportunity Scoring: Identifies seat expansion, tier upsell, module cross-sell, and department expansion plays with revenue estimates and priority rankings. - Use Case: Export your customer portfolio from a CRM into JSON, run all three scripts before a QBR cycle, and walk in with health scores, at-risk ARR totals, and a ranked expansion pipeline. ## Quick Start Run the health score calculator on the sample customer data file to see a scored portfolio report, then run the churn risk analyzer and expansion scorer on the same input.

Frequently Asked Questions about customer-success-manager

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

FAQPage Schema
How do I calculate customer health scores for SaaS accounts?

Run health_score_calculator.py with a JSON file containing customer records with usage, engagement, support, and relationship metrics. It outputs weighted 0-100 scores with Green/Yellow/Red classification, dimension breakdowns, and trend analysis against previous periods.

How to predict churn risk from customer behavior data?

Run churn_risk_analyzer.py on customer JSON data containing usage decline, engagement drop, support issues, relationship signals, and commercial factors. It produces a 0-100 risk score, applies a renewal-urgency multiplier, and assigns intervention playbooks per risk tier.

What Python dependencies does the customer health scoring require?

None beyond the Python 3.7+ standard library. All three scripts use only argparse, json, sys, datetime, and typing, so no pip installs, API keys, or external services are needed.

Can I get machine-readable output for CRM integrations?

Yes, every script supports a --format json flag that emits structured JSON instead of the default human-readable text report. You can pipe results into files or downstream pipelines for dashboards and automation.

What are the limitations of deterministic churn scoring?

The scripts analyze point-in-time JSON snapshots with no real-time data, CRM integration, or predictive ML. Scores are algorithmic from weighted signals, and default thresholds may need calibration for your industry using the health-scoring framework reference.