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AI-Powered Personalization Engine for E-commerce Platform

unosquare.com

Retail

eCommerce

Information technology

Challenges in Customer Engagement and Conversion Rates

The client faces declining online conversion rates (1.2% vs industry 3.5%) due to generic product recommendations, high cart abandonment (68%), and inability to deliver personalized shopping experiences across devices. Legacy systems lack real-time data processing capabilities.

About the Client

Multinational retail chain operating 500+ stores and online platforms across 15 countries

Goals for New Development Project

Implement AI-driven recommendation system with 95%+ accuracy
Reduce cart abandonment by 40% within 12 months
Achieve 200% ROI on personalization features within 18 months
Create unified customer profile across web, mobile, and in-store channels

Core System Functionalities

Dynamic product recommendations based on browsing history
AI-powered price optimization engine
Cross-device user behavior tracking
Personalized email campaign automation
Customer segmentation dashboard

Technology Stack Requirements

Python

TensorFlow

Apache Kafka

React.js

AWS SageMaker

System Integration Needs

Existing ERP system
CRM platform
Payment gateways
Mobile app SDKs

Performance and Security Standards

99.9% system uptime
Sub-200ms response time
GDPR compliance
Horizontal scalability to 10M users

Expected Business Impact Metrics

Projected 35% increase in average order value, 25% higher customer retention, and $4.2M annual revenue growth from personalized recommendations. Implementation expected to reduce marketing costs by 18% through improved targeting efficiency.