Customer-Personalized Video Segmentation for Real-Time Recommendations
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Solution Overview
Problem
Ecommerce websites face challenges in providing personalized and relevant product recommendations to customers, requiring significant computational and labor resources, especially when dealing with large inventories, which can lead to decreased sales and customer engagement.
Innovation Solution
A system and method that uses a descriptor taxonomy to automatically collect customer data, create a customer profile, select relevant video segments, and insert personalized content into web pages, reducing computational and labor requirements by organizing products and services using hierarchical descriptors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If personalized product recommendations and promotional content are created for each customer, then customer engagement and sales are improved, but computational resources and processing time are significantly increased
Solution Approach 1:
The patent segments the promotional content into reusable video segments that can be independently stored and retrieved. Instead of generating complete personalized videos from scratch for each customer, the system divides content into modular segments that can be efficiently selected and assembled based on customer profile data, reducing computational overhead.
Solution Approach 2:
The system performs preliminary actions by pre-processing and storing video content as reusable segments during off-peak times. Customer profiles are built incrementally as customers interact with the website, allowing the system to have customer data ready before video generation is needed, thus reducing real-time computational requirements.
2Ease of operation
If personalized content is created in real-time based on customer interactions, then customer engagement is improved, but processing time and system complexity are increased
Solution Approach 1:
The video content is segmented into reusable portions that can be independently managed and retrieved. This segmentation simplifies the real-time personalization process by allowing the system to work with smaller, pre-processed units rather than generating entire videos from scratch, thus reducing system complexity while maintaining personalization capabilities.
Solution Approach 2:
The system creates simplified copies of video content in the form of reusable segments. Instead of storing and processing complete original videos, the system works with copied segment data that can be efficiently assembled, reducing the complexity of real-time video generation while preserving the essential content for personalization.
3Measurement precision
If a large inventory of offerings is manually sorted and categorized, then product recommendations can be improved, but labor intensity and time consumption are significantly increased
Solution Approach 1:
The system implements self-service by automatically collecting customer data and generating profiles without manual intervention. The automated profile generation system processes customer interactions and creates personalized recommendations independently, eliminating the need for manual sorting and categorization while maintaining high accuracy in product recommendations.
Solution Approach 2:
The patent replaces manual mechanical processes of sorting and categorizing products with automated computational systems. The system uses algorithms to process customer interaction data and generate personalized recommendations automatically, substituting human labor with computational mechanisms that are both accurate and efficient.
Data Source
AI summary
A method of creating custom video sequences includes presenting an ecommerce website to a customer and automatically collecting electronic customer data from the ecommerce website by a server system. The electronic customer data describes at least one customer interaction with the ecommerce website is automatically collected concurrently with customer interaction(s). The method further includes, concurrently with automatically collecting the electronic customer data, creating a customer profile of a customer based on the electronic customer data, determining a set of offering descriptors based on at least one customer descriptor, automatically selecting a subset of video segments from a plurality of video segments based on the set of offering descriptors, and automatically sequencing the subset of video segments into a custom video. The method further includes automatically modifying a web page of the ecommerce website by inserting the custom video into the web page.