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Development of Personalized Recommendation Engine for Telecommunications Provider

instinctools.com

Telecommunications

Challenge

The streaming provider faces challenges in user engagement and retention due to the overwhelming number of content options. Users struggle to find content they enjoy, leading to dissatisfaction and potential churn. Generic recommendation systems are ineffective as they fail to cater to individual tastes and viewing habits.

About the Client

A leading European streaming provider offering a wide range of movies and TV shows to a large subscriber base.

Project Objectives

Develop a machine learning-powered recommendation engine to personalize content recommendations for users.
Increase user engagement and content consumption.
Improve subscriber retention rates.
Enhance user satisfaction with the streaming service.
Drive subscriber growth by attracting new users with personalized experiences.

Functional Requirements

User profile creation and management
Content tagging and metadata management
Recommendation algorithm implementation (collaborative filtering, content-based filtering)
Real-time recommendation generation
A/B testing of different recommendation algorithms
Reporting and analytics dashboards to track recommendation performance

Preferred Technologies

Python

Flask

MySQL

Machine Learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)

Integrations Required

Content Management System (CMS) for accessing movie and TV show metadata
User Authentication System
Analytics Platform

Key Non-Functional Requirements

Scalability to handle a growing user base and content library
High performance for real-time recommendation generation
Security to protect user data and prevent unauthorized access
Reliability and availability
Maintainability and ease of updates

Estimated Impact

Implementing this recommendation engine is expected to significantly increase subscriber engagement, reduce churn, and drive subscriber growth. The case study indicates a potential for a 30% increase in premium subscribers within six months of implementation, leading to increased revenue and market share.