Predictive User Path Mapping for Complex Software Navigation
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Solution Overview
Problem
Users of complex computer programs often face difficulties in accessing advanced features due to inadequate help menus and lack of knowledge among support personnel, leading to inefficient assistance in resolving user inquiries.
Innovation Solution
A system that compares user input logs to historical logs to identify corresponding paths and predict endpoints, providing users with a predicted path and deviations to help them access desired features, and allows support engineers to guide users through the correct steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If help menus are provided to assist users, then user support is available, but the help menus themselves become difficult to navigate and often only cover basic features
Solution Approach 1:
The system creates simplified copies of the actual program interface by generating visual representations of navigation paths that mirror the program's menu structure. These visual path representations serve as simplified guides that replicate the essential navigation sequence without requiring users to navigate the complex actual menu hierarchy, thereby providing easy-to-follow assistance while avoiding the complexity of the full help system.
Solution Approach 2:
The system introduces an intermediary component that acts as a mediator between the user and the complex program interface. This intermediary generates and displays visual navigation paths that bridge the gap between the user's current state and the desired feature, translating complex menu navigation into simple, step-by-step visual guidance without requiring users to directly navigate the complex help menu structure.
2Reliability
If telephone support is provided with automated systems or help desk personnel, then further assistance is available, but the solution is not easily obtained due to lack of knowledge or programming coverage
Solution Approach 1:
The system performs preliminary analysis by automatically capturing and analyzing the user's navigation path and current interface state before support is requested. This preliminary action prepares diagnostic information in advance, allowing support personnel to immediately access pre-analyzed data about what the user is trying to accomplish and where they are stuck, eliminating the time needed for users to describe their problem and allowing immediate provision of accurate solutions.
Solution Approach 2:
The system implements feedback by automatically transmitting the user's navigation path, current screen state, and attempted actions directly to support personnel. This real-time feedback mechanism ensures that support personnel receive accurate, up-to-date information about the user's specific situation, enabling them to provide reliable solutions without guessing or relying on incomplete user descriptions, thereby reducing resolution time while maintaining high reliability.
3Adaptability or versatility
If comprehensive help coverage is provided for all potential feature implementations, then all user inquiries can be addressed, but the help system becomes increasingly complex and difficult to maintain
Solution Approach 1:
The system applies dynamics by making the help system adaptive rather than static. Instead of maintaining fixed, comprehensive help documentation for all possible features, the system dynamically generates visual navigation paths based on the user's actual navigation behavior and current context. This dynamic approach allows the help system to provide relevant guidance for any feature implementation without requiring pre-written help for every possible scenario, maintaining versatility while avoiding the complexity of exhaustive documentation.
Solution Approach 2:
The system achieves universality by creating a single, unified help mechanism that can assist with any feature implementation through visual path generation. Rather than maintaining separate help systems for different features, this universal approach uses the same core functionality of capturing navigation paths and generating visual guides, allowing the system to adapt to and support any feature without increasing overall system complexity.
Data Source
AI summary
A first signature log generated by a first processing system is received, the first signature log including a first listing of at least a recorded series of user inputs received by a computer program. The first listing of the recorded series of user inputs can be compared to at least one historical log indicating at least one historical path, each historical path including at least second listing of a series of historical user inputs that corresponds to a historical endpoint in the computer program. The at least one historical path to which the recorded series of user inputs at least partially corresponds and a deviation between the signature log and the historical log can be identified. Based on a predicted endpoint, a predicted path corresponding to the predicted endpoint can be selected, and the predicted path and the deviation between the signature log and the historical log can be output.