Client-Side Scripts for Real-Time User Interest Detection
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Solution Overview
Problem
Legacy techniques fail to capture instantaneous user interests based on real-time user interactions with web page components, limiting the ability to present targeted advertisements effectively.
Innovation Solution
The implementation of scripts that execute on the client device to evaluate page content, using key-value pairs and enhanced Boolean operators, allowing for conditional content delivery based on user interactions, thereby determining user interest in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If legacy techniques are used to identify user demographics, then user identification can be performed, but instantaneous user interests based on real-time interactions cannot be captured
Solution Approach 1:
The system executes scripts on the client device that proactively capture user interactions with web page components before the user navigates away. These scripts monitor clicks, hovers, and other interactions in real-time, preserving the interaction data before it would otherwise be lost. This preliminary capture action enables subsequent analysis of instantaneous user interests.
Solution Approach 2:
The patent introduces an intermediary script layer between the user and the web page content. These scripts act as mediators that observe and record user interactions without disrupting the normal browsing experience. The scripts capture interaction data and transmit it to servers for analysis, serving as an intermediary that bridges the gap between user behavior and advertising delivery systems.
2Productivity
If real-time user interaction tracking is implemented, then instantaneous user interests can be determined, but system complexity increases
Solution Approach 1:
The system divides the advertising technology stack into distinct segments: client-side scripts that capture interactions, server-side systems that analyze data and determine interests, and advertising delivery systems that present targeted content. This segmentation allows each component to specialize in a specific function, reducing overall system complexity while maintaining high productivity in advertising targeting.
Solution Approach 2:
The client device autonomously executes scripts that capture its own interaction data without requiring external intervention. The system performs self-service by automatically monitoring, recording, and transmitting its own behavioral data, eliminating the need for additional tracking infrastructure and reducing system complexity.
3Measurement precision
If comprehensive user interaction data is collected, then more accurate user interest determination is achieved, but data processing time increases
Solution Approach 1:
The system extracts only the most relevant interaction features from comprehensive user data, such as click patterns, time spent on specific components, and navigation paths. By extracting key indicators of user interest rather than processing all raw interaction data, the system maintains high measurement precision while reducing data processing time and computational requirements.
Data Source
AI summary
The disclosure is directed to approaches for combining server-side decisions based on user attributes and/or demographics with client-side decisions based on expressed or implied user interests determined based on the contents of a web page being visited by the user. A server is responsive to an occurrence of an operation of a client device at the web page. Processing steps determine particular executable web page content to send to the client device (e.g., where the particular executable web page content is determined in response to a particular client-side operation). The web page is rendered with the aforementioned executable web page content. Server-side processing receives messages that are emitted conditionally, based on the occurrence of a user event. An event log message comprises a portion of the web page, such as a string, indicating or implying user interest. A targeted advertisement is presented to the user based on the user interest.