Real-Time Commerce Choices via Multi-Dimensional User Analytics
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Solution Overview
Problem
Consumers face overwhelming choices in video content consumption, with irrelevant advertising disrupting their experience, and existing technologies fail to provide personalized and engaging interactions that align content and ads with user interests.
Innovation Solution
A system and method that utilize multiple dimensions of commerce and streaming data for advanced user profiling, providing real-time commerce choices by performing site, video, commerce, and user analytics to offer targeted advertising and interactive content experiences, including pop-ups with coupons or purchasing options, and integrating Blu-ray pairing with video portals for seamless content access across devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple dimensions of analytics are performed to provide personalized content and advertising, then user engagement and relevance are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments analytics into multiple dimensions: site/experience analytics, video analytics, commerce analytics, and user analytics. Each dimension processes specific types of data independently, allowing the system to handle complexity through modular organization while delivering comprehensive personalization.
Solution Approach 2:
The patent adds temporal dimension by performing real-time analytics during content consumption and cross-references with historical data. This multi-dimensional approach (content type, user behavior, timing, commerce context) enables sophisticated personalization without requiring a single monolithic complex system.
2Loss of information
If targeted advertising is provided based on user analytics, then advertising relevance is improved, but user privacy concerns and data collection requirements increase
Solution Approach 1:
The patent introduces an intermediary analytics layer that processes user data to generate aggregated profiles and preferences without exposing raw personal information. This intermediary system matches users with relevant advertising based on analyzed patterns rather than direct data exposure, reducing privacy risks while maintaining advertising effectiveness.
Solution Approach 2:
The patent transforms raw user data into anonymized parameters and aggregated metrics for advertising targeting. By changing the form of data from identifiable personal information to statistical parameters, the system maintains advertising relevance while mitigating privacy concerns through data obfuscation.
3Loss of time
If real-time analytics are performed during content consumption, then commerce choice timing is improved, but processing time and computational load increase
Solution Approach 1:
The patent performs preliminary analytics by pre-processing user behavior patterns and content preferences before commerce decisions are needed. Historical data is analyzed in advance to build user profiles, so that during real-time content consumption, only lightweight matching operations are required, reducing computational load while maintaining timely commerce recommendations.
Solution Approach 2:
The patent implements continuous background analytics that process user interactions as they occur, maintaining up-to-date user profiles without interrupting content consumption. This continuous processing distributes computational load over time rather than concentrating it at decision points, enabling real-time commerce choices with manageable processing requirements.
Data Source
AI summary
Multiple dimensions of commerce and streaming data are able to be used to provide advanced user profiling and realtime commerce choices. By performing site and experience analytics, video analytics, commerce analytics and user analytics, better commerce choices are able to be presented to the user.