Content Selection Interface Scoring for Faster Content Discovery
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The vast volume of available content and limited screen estate on user devices make it challenging for users to easily navigate and select content, while sub-optimal configuration of content selection interfaces at the provider side leads to longer identification times and inefficient processes, particularly in systems handling millions of user interactions.
Innovation Solution
A content selection interface configuration system that orders and scores groups of content based on user activity and data properties, allowing for prioritization of more interesting content and efficient interface configuration, using a UX engine to enhance user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the content selection interface displays a large volume of content to cater to diverse user preferences, then the variety and quantity of content available to users is improved, but the difficulty of navigation and content identification increases
Solution Approach 1:
The content selection interface is divided into multiple carousels, each displaying a manageable group of content items. This segmentation allows users to navigate through organized sections rather than overwhelming lists, reducing navigation difficulty while maintaining access to large volumes of content across multiple carousels.
Solution Approach 2:
Content items are pre-scored and ordered based on predicted user interest before display. This preliminary action of scoring and organizing content ensures that the most relevant items appear first in each carousel, reducing the time and effort users need to spend searching for interesting content.
2Adaptability or versatility
If manually curated groups of content are provided to support campaigns, then the relevance and targeted nature of content is improved, but the complexity of interface configuration increases
Solution Approach 1:
The system automatically scores and orders content groups based on user activity data and content properties without requiring manual configuration. This self-service approach maintains adaptability to user preferences and campaign requirements while eliminating the complexity of manual interface configuration.
Solution Approach 2:
The system dynamically adjusts content ordering based on changing user activity patterns and content properties. By monitoring user interactions and recalculating scores, the interface adapts to different campaigns and user preferences automatically, maintaining relevance without increasing configuration complexity.
3Adaptability or versatility
If the content selection interface is configured at the provider side with complex processes, then the ability to provide personalized content is improved, but the response time and processing lag increase
Solution Approach 1:
Content items are pre-scored based on user activity data and content properties before users request them. This preliminary scoring allows the system to quickly retrieve and display relevant content without performing complex real-time analysis, reducing response time while maintaining personalization capability.
Solution Approach 2:
The system continuously monitors user activity and uses this feedback to update content scores and ordering. This feedback mechanism enables the system to learn from user interactions and improve personalization over time without requiring complex real-time processing for each user request.
Data Source
AI summary
A content selection interface configuration system for configuring a content selection interface allowing user selection of content presented for viewing, the content selection interface configuration system configured to: provide one or more groups of content, each group of content including a plurality of content items; obtain data indicating at least one property of the content items of each group of content; obtain user activity including interactions by the user with content on a content selection interface; and determine a score each group of content of the plurality of groups of content based at least in part on the user activity of that user and the data indicating the at least one property of some or all of the content, wherein the score is indicative of a likely interest of the content in that group of content to one or more users of the content selection interface.