Adaptive Tax Preparation Interface for Dynamic User Experience
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Solution Overview
Problem
Traditional tax return preparation systems are inflexible and generic, leading to irrelevant and confusing user experiences, which results in dissatisfaction and a lack of personalized assistance, ultimately deterring users from becoming paying customers.
Innovation Solution
A software system that dynamically identifies user preferences and adapts user experiences in real-time, filtering out non-compliant options to provide personalized and relevant interactions, improving user satisfaction and conversion rates by aligning user experience options with user preferences while maintaining compliance with business rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional tax return preparation systems use fixed, predetermined question sequences for all users, then the system structure is simple and easy to implement, but the user experience becomes generic and irrelevant to individual user needs
Solution Approach 1:
The patent implements dynamic user experience by allowing the question sequence and presentation to adapt in real-time based on user responses, preferences, and observed behavior. The system transitions from static, pre-packaged question sequences to dynamic, user-specific pathways that evolve during the interview process, resolving the contradiction between personalization and complexity through adaptive logic.
Solution Approach 2:
The system changes key parameters of the user experience including question selection, presentation format, and sequencing based on user characteristics and real-time interactions. By dynamically adjusting these parameters rather than maintaining fixed values, the system achieves personalization while managing complexity through parameter-driven adaptation.
2Productivity
If the system presents all pre-determined questions to every user, then complete tax information is collected, but users experience unnecessary length and confusion
Solution Approach 1:
The system extracts and removes questions that are not relevant to the specific user based on their characteristics, preferences, and responses. By taking out unnecessary questions from the complete set, the system maintains comprehensive information collection while significantly reducing the interview duration and user burden, directly addressing the efficiency-time contradiction.
Solution Approach 2:
The system applies partial action by presenting only the subset of questions necessary for each user rather than the complete question set. This partial approach ensures sufficient information is gathered for accurate tax preparation while avoiding the excessive action of presenting all possible questions, thereby optimizing the balance between completeness and efficiency.
3Adaptability or versatility
If the system uses hard-coded, static analysis features, then the system is stable and reliable, but it cannot adapt to changing user needs or circumstances
Solution Approach 1:
The patent transforms static, hard-coded analysis features into dynamic components that can adapt to changing user needs while maintaining system stability. The analysis features evolve based on user responses and observed behavior, allowing the system to respond to changing circumstances without compromising the reliable collection of essential tax information.
Solution Approach 2:
The system implements feedback mechanisms where user responses and behavior are continuously analyzed to adjust the interview process and analysis in real-time. This feedback loop enables the system to adapt to changing user needs dynamically while maintaining reliability through structured analysis of user inputs and systematic adjustment of the preparation process.
4Ease of operation
If irrelevant and confusing questions are presented to users, then all potential user scenarios are covered, but user satisfaction and trust decrease
Solution Approach 1:
The system extracts and removes irrelevant and confusing questions from the interview process by analyzing user characteristics, preferences, and responses in real-time. This extraction maintains comprehensive coverage of necessary user scenarios while eliminating questions that do not apply to the specific user, thereby improving ease of operation without sacrificing information completeness.
Solution Approach 2:
The system applies local quality by tailoring the question set and presentation to each user's specific characteristics, preferences, and circumstances. Rather than applying a uniform question set to all users, the system customizes the local experience for each user, ensuring relevant questions are asked while maintaining comprehensive scenario coverage through adaptive logic.
Data Source
AI summary
A method and system adaptively improves potential customer conversion rates, revenue metrics, and/or other target metrics by providing effective user experience options to some users while concurrently testing user responses to other user experience options, according to one embodiment. The method and system selects the user experience options by applying user characteristics data to an analytics model, according to one embodiment. The method and system analyzes user responses to the user experience options to update the analytics model, and to dynamically adapt the personalization of the user experience options, according to one embodiment. The method and system filters out user experience options from delivery to users, if the user experience options are non-compliant with one or more business rules, to maintain business relations for the service provider and to maintain user confidence in the services provided by the service provider (e.g., a tax return preparation system), according to one embodiment.