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client-retention

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Reduce churn with AI-driven retention insights.

Marketing & Sales#retention#churn-prediction#customer-success#cohort-analysis#churn#user-engagement#ai-prediction
AuthorCleanExpo
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Provides a data-driven system to monitor user engagement, identify churn risks, and optimise retention so teams can proactively re-engage at-risk accounts and improve long-term user value.

Core Features & Use Cases

  • Engagement Monitoring: Collects and computes DAU, WAU, MAU, session duration, and feature adoption to surface usage trends.
  • Cohort & Churn Analysis: Runs cohort retention curves, flags disengaged segments, and scores churn probability using an AI model with rule-based fallbacks.
  • Intervention & Reporting: Designs and triggers personalised re-engagement campaigns, measures impact, and generates weekly retention reports for stakeholders.
  • Use Case: A customer success manager runs cohort analysis for last quarter, identifies at-risk users with falling feature adoption, scores churn probability, and launches targeted email sequences to recover revenue.

Quick Start

Analyse the last 30 days of engagement for the new-user cohort, score churn probability, and produce a summary with top re-engagement recommendations.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: client-retention
Download link: https://github.com/CleanExpo/Synthex/archive/main.zip#client-retention

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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