Contextual Record Overlap Tracking via Match Time Analysis
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Solution Overview
Problem
Current systems lack the ability to effectively track and report contextual record movements and overlaps between partner populations, making it difficult to identify actionable opportunities for collaboration, as manual validation is required and visibility into historical movements is limited.
Innovation Solution
A system and method that utilize a partner ecosystem platform to automatically determine and display contextual record overlaps by calculating match times, providing visibility through activity timelines, account mapping matrices, and other display modes, allowing for the identification of recent opportunities and collaboration between partners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual validation is used to track record overlaps between partners, then measurement precision can be maintained, but productivity is significantly reduced and loss of time increases
Solution Approach 1:
The system enables automatic self-service tracking of record overlaps between partner populations. The computing system automatically determines contextual record overlaps, calculates match times, and generates reports without requiring manual validation, thereby maintaining measurement precision while dramatically improving productivity
Solution Approach 2:
The patent replaces manual mechanical processes with automated computational systems. The computing system uses automated algorithms to determine record overlaps, calculate match times, and generate visibility reports, substituting manual validation with automated electronic processing that maintains accuracy while improving efficiency
2Loss of information
If comprehensive tracking of historical record movements is implemented, then loss of information is reduced, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary computing system that acts as a mediator between partner populations and users. This system automatically captures, stores, and processes historical record movement data, providing comprehensive visibility without requiring complex user-side tracking implementations. The intermediary handles the complexity internally while presenting simplified information through activity timelines and reports
Solution Approach 2:
The system performs preliminary action by automatically capturing and storing record movement data as it occurs, rather than requiring retrospective analysis. The computing system proactively determines contextual record overlaps and calculates match times in real-time, maintaining comprehensive historical visibility without adding complexity to user operations
3Productivity
If automatic determination of contextual record overlaps is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The computing system is designed with multi-functionality to handle various tracking and reporting tasks within a single unified platform. It can determine contextual record overlaps, calculate match times, generate activity timelines, and create account mapping matrices all through one system, improving productivity without requiring multiple separate complex tools
Solution Approach 2:
The automated system performs self-service by automatically determining record overlaps and generating reports without requiring manual intervention. The system independently calculates match times, identifies actionable opportunities, and presents findings through multiple display modes, improving productivity while containing complexity within the automated processing layer
Data Source
AI summary
A system and method of reporting a contextual record, are described. Population data representing respective population segments of a first partner and a second partner is received. The respective population segments include a record overlapping between the first partner and the second partner. A first match time at which the record has a first record status for one of the partners is determined. In response to a change in the first record status to a second record status for one of the partners, a second match time of the record is determined. Report data, including the first match time and the second match time, is generated for display to represent a history of the record statuses.