customer-success-managerlisted

# 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. --- ## Table of Contents - [Capabilities](#capabilities) - [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) --- ## Capabilities - **Customer Health Scoring**: Multi-dimensional weighted scoring across usage, engagement, support, and relationship dimensions with Red/Yellow/Green classification - **Churn Risk Analysis**: Behavioral signal detection with tier-based intervention playbooks and time-to-renewal urgency multipliers - **Expansion Opportunity Scoring**: Adoption depth analysis, whitespace mapping, and revenue opportunity estimation with effort-vs-impact prioritization - **Segment-Aware Benchmarking**: Configurable thresholds for Enterprise, Mid-Market, and SMB customer segments - **Trend Analysis**: Period-over-period comparison to detect improving or declining trajectories - **Executive Reporting**: QBR templates, success plans, and executive business review templates --- ## Input Requirements All scripts accept a JSON file as posi