Virtual Dynamic Representative for Taxonomic Group Data Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing customer management systems struggle to accurately organize and analyze large groups of entities with time-varying parameters, often resulting in outdated, redundant, or inconsistent records, which complicates tasks like marketing and customer relationship management.
Innovation Solution
A computerized account-management system that creates a virtual dynamic representative of taxonomic groups by identifying vertical and horizontal parameters, retrieving relevant records, assembling values, selecting the most desirable values, and configuring a virtual record to represent the group, allowing for efficient organization and updating of records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional customer management systems store and manage large numbers of individual customer records with time-varying parameters, then the system can maintain detailed historical information, but the system becomes unable to efficiently organize and analyze these records due to outdated, redundant, or inconsistent data
Solution Approach 1:
The patent merges multiple individual customer records into a single aggregated customer profile that consolidates information across multiple data sources and time periods. This aggregation process combines disparate records while eliminating duplicates and inconsistencies, thereby improving reliability without proportionally increasing system complexity.
Solution Approach 2:
The patent introduces an intermediary aggregation layer between raw customer records and analysis systems. This intermediary profile serves as a mediator that pre-processes and standardizes data before it reaches downstream applications, reducing the complexity burden on both data storage and analysis systems while maintaining data accuracy.
2Reliability
If the system updates customer records frequently to maintain current information, then the data becomes more accurate and relevant, but the computational resources and processing time required increase significantly
Solution Approach 1:
The aggregated customer profile automatically updates itself by monitoring changes in source records and selectively incorporating relevant updates without requiring full system reprocessing. This self-service mechanism maintains data currency by only processing necessary changes, thereby reducing computational resource consumption compared to comprehensive frequent updates.
Solution Approach 2:
The system implements periodic aggregation cycles where customer profiles are updated at scheduled intervals rather than continuously. This periodic action allows the system to balance data currency with resource consumption by performing intensive processing only when necessary, rather than maintaining constant update operations.
3Quantity of substance
If the system maintains detailed individual records for each customer interaction over twenty years, then comprehensive historical data is preserved, but the ability to accurately identify current customer characteristics deteriorates due to outdated information
Solution Approach 1:
The patent extracts and separates current relevant characteristics from historical data by creating distinct fields in the aggregated profile. One field captures contemporary customer attributes while another preserves historical transaction patterns. This extraction allows the system to maintain both comprehensive historical data and accurate current characteristics without allowing outdated information to contaminate present-day assessments.
Solution Approach 2:
The customer profile is segmented into multiple temporal layers, with distinct sections for recent behavior, historical patterns, and demographic information. This segmentation allows different parts of the data to be weighted differently in analysis, ensuring that current characteristics drive immediate decisions while historical data provides contextual background without dominating present assessments.
4Adaptability or versatility
If the system uses different data collection mechanisms over time to adapt to evolving business models, then the system remains adaptable to changing requirements, but inconsistencies and gaps in the data increase
Solution Approach 1:
The aggregated customer profile employs a universal data structure that can accommodate multiple data collection mechanisms and formats. The profile framework is designed to ingest information from diverse sources including traditional transactions, digital interactions, and third-party data, standardizing them into a common format. This universality allows the system to adapt to evolving data collection methods while maintaining consistency in the final integrated view.
Data Source
AI summary
A method and associated systems for generating a virtual dynamic representative of a taxonomic group with unique inheritance of attributes. Each record of a continuously updated database identifies a “vertical” attribute of an entity associated with that record, and further identifies a “horizontal” attribute upon which a business decision may be based. An account-management apparatus selects a subset of these records that are associated with a particular value of the vertical attribute and identifies the most desirable value of the horizontal attribute that is associated with any of the selected records. The apparatus then creates a virtual representative of the subset that represents the subset as a taxonomic group associated with the particular value of the vertical attribute and associates all records of the group with the most desirable value of the horizontal attribute.