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Subscription Revenue Optimizer with Stripe, Postgres & Gmail - Predictive Retention

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Created by: Rodrigue || gbadou

Rodrigue

Last update

Last update 2 days ago

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How it works

  • Behavioral analytics: Real-time analysis of product usage and engagement signals
  • Churn prediction: Predictive model identifying at-risk customers 15 days before
  • Smart upselling: Personalized recommendations based on usage and profile
  • Retention campaigns: Automated retention campaigns with dynamic offers

Set up steps

  • Product analytics: Connect Mixpanel, Amplitude or proprietary analytics
  • Billing system: Integrate Stripe, Chargebee, Recurly for billing data
  • Customer data: Synchronize your CRM with complete customer history
  • Email/SMS platforms: Configure SendGrid, Twilio for communications
  • Pricing rules: Define your pricing matrix and promotional offers
  • ML pipeline: Configure predictive model training

Key Features

  • 🔮 Churn prediction: At-risk customer identification with 85% accuracy
  • 💰 Smart upselling: Personalized recommendations increasing ARPU by 35%
  • ⚡ Proactive interventions: Automated actions before customer churns
  • 📊 Revenue optimization: Price optimization based on willingness to pay
  • 🎯 Dynamic segmentation: Real-time customer groups updates
  • 🔄 A/B testing: Automated testing of retention strategies
  • 📈 LTV maximization: Customer lifetime value optimization
  • 🛡️ Dunning management: Automated payment failure handling