Contextual Goal Tracking Metrics for Non-Financial Objectives
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Solution Overview
Problem
Goal tracking applications struggle to automatically track progress for goals without explicit monetary amounts or end dates, such as buying a house in a certain timeframe, as they cannot effectively monitor non-financial aspects or provide timely recommendations for user actions.
Innovation Solution
An electronic system that utilizes contextual information, including user profiles and external data sources, to suggest actions for achieving goals by calculating metric components like time urgency, interest, and affordability, and transmitting personalized recommendations to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional goal tracking applications only monitor explicit financial metrics, then they can accurately track monetary progress, but they cannot effectively track goals without explicit monetary amounts or end dates
Solution Approach 1:
The patent transforms the tracking parameters from purely financial metrics to multi-dimensional metrics including time urgency, interest level, and affordability. This allows the system to track diverse goals beyond monetary progress by changing the measurement parameters to include qualitative aspects like user interest and temporal constraints.
Solution Approach 2:
The system creates a universal goal tracking framework that handles both traditional financial goals and non-financial goals using the same metric calculation approach. By defining standardized metric components (time urgency, interest, affordability) that can be applied across different goal types, the system achieves multi-functionality in tracking diverse objectives.
2Extent of automation
If goal tracking applications manually update progress, then they can capture detailed user input, but they cannot automatically track progress for goals without explicit monetary amounts or end dates
Solution Approach 1:
The system enables automatic progress tracking by having goals self-evaluate through metric calculations. The framework automatically computes time urgency, interest, and affordability metrics based on current data, allowing the system to self-monitor progress without requiring manual user updates for each goal status.
Solution Approach 2:
The system implements continuous feedback loops where metric calculations are performed automatically and results are used to generate recommendations. This feedback mechanism enables the system to automatically detect when goals are at risk or making progress, triggering appropriate notifications and suggestions without manual intervention.
3Loss of information
If goal tracking applications provide generic notifications, then they can keep users informed, but they cannot provide timely recommendations for user actions
Solution Approach 1:
The notification system dynamically adjusts its behavior based on real-time metric calculations. Instead of static, periodic notifications, the system continuously evaluates time urgency, interest, and affordability metrics to determine when and what to notify users about, making the notification timing and content adaptive to current goal status.
Solution Approach 2:
The system performs preliminary metric calculations and risk assessments before critical deadlines occur. By continuously monitoring time urgency metrics and calculating potential outcomes in advance, the system can proactively notify users of upcoming deadlines or potential goal failures before they occur, allowing users to take preventive actions.
Data Source
AI summary
A computer-implemented method may include retrieving, using at least one processor, a goal associated with a user from a user profile; generating, using the at least one processor, based in part on contextual information associated with the user, a plurality of metrics for the goal; based on the plurality of metrics and using the at least one processor, generating an action recommendation with respect to completion of the goal; and presenting the action recommendation to a user device of the user.