Intelligent Support System for Web User Experience
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Solution Overview
Problem
Existing web-based business applications face challenges in categorizing user experiences and providing timely support due to anonymous and self-service aspects, leading to difficulties in addressing user issues and retaining customers.
Innovation Solution
A computer-implemented system that accesses user feedback, applies intervention trigger logic to identify issues, and generates real-time interventions to improve user experience, including providing information, redirects, and enhanced interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If anonymous and self-service aspects are implemented in web-based business applications, then user independence and system scalability are improved, but the ability to categorize user experiences and provide timely support deteriorates
Solution Approach 1:
The system implements feedback mechanisms by collecting user feedback data through feedback collection software, analyzing this data through intervention trigger logic, and using the analysis results to generate intervention elements that are presented back to users. This closed-loop feedback system enables the anonymous self-service platform to capture, categorize, and respond to user experiences automatically.
Solution Approach 2:
The patent introduces an intermediary analysis system that acts as a mediator between anonymous user interactions and support responses. The intervention trigger logic serves as an intermediary that processes user feedback data, identifies patterns and triggers, and generates appropriate intervention elements, thereby enabling categorization of user experiences without requiring user identification.
2Reliability
If real-time analysis and response to user feedback are implemented, then user satisfaction and retention are improved, but system complexity and processing requirements increase
Solution Approach 1:
The system segments the complex task of user experience analysis into distinct functional modules: feedback collection software that gathers user input, intervention trigger logic that analyzes the collected data, and intervention generation components that create responses. This segmentation allows each module to specialize in specific processing tasks, managing system complexity through modular architecture while enabling real-time analysis.
Solution Approach 2:
The system implements self-service by enabling automated analysis and response generation without requiring human intervention. The intervention trigger logic automatically processes user feedback data and generates appropriate intervention elements, allowing the system to serve itself in real-time, thereby improving user retention while keeping operational complexity manageable through automation.
3Ease of operation
If intervention elements are generated and presented to users in real-time, then user experience improvement is achieved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary action by pre-processing and analyzing user feedback data as it is collected, rather than batching processing later. The intervention trigger logic continuously evaluates incoming feedback data in real-time, identifying triggers and generating intervention elements immediately. This preliminary real-time processing improves user experience quality by providing timely interventions while managing computational resources through efficient continuous processing.
Data Source
AI summary
According to one embodiment, a computer-implemented method for providing intelligent support includes using at least one computer system to access information associated with a user experience for a particular user of a web page, the accessed information including user feedback collected from the particular user using feedback collection software; accessing intervention trigger logic; identify at least one intervention trigger by applying the intervention trigger logic to at least a portion of the accessed information; and generate one or more intervention elements for presentation to the particular user, in response to the identification of at least one intervention trigger, to improve the user experience for the particular user.