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AI-Driven Customer Retention Platform for E-Commerce
  1. case
  2. AI-Driven Customer Retention Platform for E-Commerce

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AI-Driven Customer Retention Platform for E-Commerce

n-ix.com
eCommerce
SaaS
Digital Goods

Business Challenges in Customer Retention

The client's e-commerce platform lacked advanced customer segmentation and churn prediction capabilities, resulting in inefficient manual email marketing campaigns, suboptimal customer retention rates, and excessive operational overhead for campaign management.

About the Client

A cloud-based e-commerce and subscription management platform provider enabling businesses to monetize digital services with global compliance and payment solutions.

Strategic Project Goals

  • Implement ML-powered churn prediction models to identify at-risk customers
  • Automate personalized email campaign workflows based on churn probabilities
  • Reduce manual effort in campaign creation through template-driven automation
  • Enhance customer retention rates through data-driven marketing interventions
  • Improve platform scalability and cost-efficiency via cloud-native architecture

Core System Capabilities

  • Real-time churn probability calculation using machine learning models
  • Dynamic customer segmentation engine
  • Automated personalized email campaign workflows
  • Interactive template manager for campaign creation
  • Multi-tenant analytics dashboards with revenue impact visualization

Technology Stack Requirements

AWS SageMaker
AWS Lambda
AWS Step Functions
React
pySpark
Snowflake
Power BI

System Integration Needs

  • Payment gateway APIs
  • CRM systems
  • Third-party analytics tools
  • Cloud storage services (AWS S3)
  • Identity management (AWS IAM)

Operational Requirements

  • High-availability serverless architecture
  • Real-time processing capabilities
  • Enterprise-grade data security (GDPR compliance)
  • Horizontal scalability for multi-tenant support
  • 99.9% system uptime SLA

Expected Business Outcomes

Implementation of AI-driven marketing automation is projected to increase customer retention rates by 25-30%, reduce campaign management overhead by 40%, and improve marketing ROI through personalized interventions. The cloud-native architecture will reduce infrastructure costs by 35% while enabling rapid scaling across global markets.

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