Customer Service & Retention AI
Customer Success Manager
Customer Success Manager is an ecommerce AI skill for Alireza Rezvani, built for teams working with Codex, Claude Code, OpenClaw. Use it to you are handling recurring…
View original link · GitHubWhat this skill helps you do
Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Runs three Python CLI tools—health_score_calculator.py, churn_risk_analyzer.py, and expansion_opportunity_scorer.py—that produce deterministic, repeatable analysis from JSON customer data. Supports text and JSON output formats for integration into dashboards and pipelines. Includes segment-aware benchmarking across Enterprise, Mid-Market, and SMB accounts.
Install and get started
Copy the full instructions into your AI tool. Test one low-risk example before connecting real store data.
Original Skill instructions
You are a Customer Success Manager analyzing SaaS portfolios. Run three Python CLI tools in sequence on JSON customer data: (1) health_score_calculator.py scores each customer across Usage (30%), Engagement (25%), Support (20%), Relationship (25%)—classifying Green/Yellow/Red. (2) churn_risk_analyzer.py detects at-risk accounts via usage decline, engagement drop, support issues, relationship signals, and commercial factors—producing Critical/High/Medium/Low tiers with intervention steps. (3) expansion_opportunity_scorer.py identifies upsell, cross-sell, and seat-expansion with revenue estimates. Use --format json for pipelines, --format text for reviews. Act on trends—a declining Green is more urgent than a stable Yellow. Calibrate thresholds per your product.
Useful tasks
- Quarterly Business Reviews with health scores and risk analysis
- Identifying at-risk accounts for proactive CSM intervention
- Scoring expansion and upsell opportunities by revenue potential
- SaaS portfolio health monitoring across Enterprise, Mid-Market, and SMB segments
- Preparing executive summaries with churn risk tiers and retention recommendations
How to use it
- Run all three scripts together—health, risk, and expansion give a complete picture
- Act on trends not snapshots: a declining Green score is more urgent than a stable Yellow
- Calibrate default thresholds based on your specific product and industry benchmarks
- Use --format json for pipeline integration; --format text for terminal reviews
- Cross-check output totals against your CRM before sharing with stakeholders
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