Case Study Showcase
Content Recommendation Engine
High-performance hybrid streaming recommendation engine
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Company Profile
A rapidly growing video-on-demand platform with 10M+ subscribers.
Industry
Media & Entertainment
Region
Global
About the Client
The client is a leading streaming service specializing in niche international content with over 50,000 titles.
0%
Watch Time Increase
0 Months
Speed to Result
0M+
Daily Active Users
Challenge
The primary challenge was the "cold start" problem—how to recommend new content to new users without historical data.
- Rising churn due to poor content discovery.
- Inability to personalize for new users.
- High latency in updating recommendations.
- Manual curation was slow and biased.
The Solution
Hybrid Neural Recommendation Engine
WebbyButter engineered a multi-stage recommendation pipeline with a Transformer-based model that treats watch history as a sequence.
The Outcome
Streaming Growth at 10x Velocity
Within four months, average watch time increased by 55%. Search-to-play time decreased significantly.
0%
Watch Time Growth
0%
Churn Reduction
0ms
API Latency
"WebbyButter's AI engine is the reason our users stay longer and come back more often."
VP of Engineering, Streaming Co.
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