Personalized EPG Channel Line-up for Connected TV
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Solution Overview
Problem
The exponential increase in linear TV channels makes it difficult for viewers to discover channels of interest, leading to platforms curating a limited number of channels, resulting in a one-size-fits-all experience that neglects the distribution and discovery of various channels needed to retain customers, and existing solutions fail to drive personalization using viewership data for linear channels.
Innovation Solution
A system and method for channel line-up personalization in Electronic Program Guides (EPGs) using viewership data, comprising a platform frontend, backend, viewership data processor, CLIP backend, recommendation engines, and a recommendation adaptor, which processes and aggregates data to provide personalized channel recommendations based on user behavior and metadata, enabling customized channel orders and program listings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If platforms manually select a limited number of channels for the EPG, then the user interface becomes simpler and easier to manage, but channel diversity and personalization are reduced, leading to a one-size-fits-all experience that fails to retain customers
Solution Approach 1:
The system dynamically generates personalized channel line-ups for each viewer based on their viewing history and preferences. The EPG channel order is no longer static and manual but dynamically adapted to each user, resolving the contradiction between operational simplicity and personalization versatility.
Solution Approach 2:
The system automatically profiles viewers and generates personalized channel recommendations without requiring manual platform intervention for each user. The automated profiling and recommendation engine serves the personalization function self-service style, maintaining simplicity while enabling versatility.
2Device complexity
If platforms curate a fewer number of channels, then the platform becomes easier to manage and deploy, but channel distribution and discovery opportunities are curtailed, reducing customer satisfaction and retention
Solution Approach 1:
The system segments the channel lineup into personalized subsets for each viewer based on their preferences and viewing behavior. Instead of managing one global curated list, the platform creates multiple segmented channel lists, increasing the effective number of distributed channels while keeping individual user experiences manageable.
Solution Approach 2:
The system changes the parameter of channel selection from a fixed manual count to a dynamic parameter based on viewer profiling. The number and order of channels presented to each user varies according to their profile, allowing the platform to distribute more channels effectively without increasing operational complexity.
3Loss of information
If existing EPG personalization approaches are used that require explicit viewer inputs or focus on content-level recommendations, then content recommendations can be provided, but linear channel personalization driven by viewership data is not achieved
Solution Approach 1:
The system implements a feedback loop where viewership data from linear channel viewing is continuously collected, processed to update viewer profiles, and used to generate personalized channel recommendations. This closed-loop feedback mechanism enables automatic linear channel personalization based on actual viewing behavior without requiring explicit user inputs.
Solution Approach 2:
The system replaces the manual/content-level recommendation approach with an automated viewership-data-driven mechanism. Instead of relying on explicit user inputs or content metadata alone, the system substitutes this with automated analysis of actual viewing behavior data to drive linear channel personalization.
Data Source
AI summary
A system and method to enable personalisation of channel line-up and channel information for linear channels on connected TV.