customer-success-manager

原文涵盖的主题

• Customer Success Manager
• Table of Contents
• Input Requirements
• Health Score Calculator
• Churn Risk Analyzer
• Expansion Opportunity Scorer
• Output Formats
• How to Use

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. -- Input Requirements Output Formats How to Use Scripts Reference Guides Templates Best Practices Limitations -- All scripts accept a JSON file as positional input argument. See assets/samplecustomerdata.json for complete schema examples and sample data. Required fields per customer object: customerid, name, segment, arr, and nested objects usage (loginfrequency, featureadoption, daumauratio), engagement (supportticketvolume, meetingattendance, npsscore, csatscore), support (opentickets, escalationrate, avgresolutionhours), relationship (executivesponsorengagement, multithreadingdepth, renewalsentiment), and previousperiod scores for trend analysis. Required fields per customer object: customerid, name, segment, arr, contractenddate, and nested objects usagedecline, engagementdrop, supportissues, relationshipsignals, and commercialfactors. Required fields per customer object: customerid,

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