Data Science

Recommendation Intelligence Engine

Client: Leading Subscription Video-on-Demand (SVOD) Platform

Executive Summary

Challenge: High churn rates as users struggled to find relevant content among 50,000+ titles.

Solution: A data-driven engine delivering hyper-personalized content suggestions in real-time.

Results: 35% increase in retention and 50% boost in click-through rates.

The Challenge

The client had a massive library, but 80% of traffic went to only the top 1% of content. Users switched to competitors when they felt 'not understood.'

Choice Paralysis:Users spent more time searching than watching.

Static Logic:Simple genre tags failed to capture user mood nuances.

Poor Conversion:Generic notifications resulted in low open rates.

The Solution

Shifts from 'Product-Centric' to 'User-Centric' logic using behavioral deep learning.

Behavioral Deep Learning: Analyzes how users interact (pause, skip, re-watch).
Contextual Awareness: Suggests content based on time, device, and location.
Predictive Churn Prevention: Triggers personalized 'We Miss You' offers.