Customer Metric Management Circuit for Financial Data Integration
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Solution Overview
Problem
Merchants face challenges in understanding customer behavior and sentiment, which hinders their ability to effectively improve business strategies, as they lack comprehensive data on customer likelihood to return, spending habits, and social media interactions.
Innovation Solution
A financial institution computing system that integrates an account database for transaction statistics and a social media database to create a probability model of customer behavior, predicting future transactions and providing personalized incentives based on transaction history and social media activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If merchants use traditional transaction-only data analysis, then implementation simplicity is maintained, but customer behavior understanding precision is insufficient
Solution Approach 1:
The patent merges transaction data from account databases with social media data from social media databases to create a comprehensive customer metric management system. This combination allows merchants to understand customer behavior through multiple data dimensions (transaction history, social media activities, sentiments), resolving the contradiction by integrating diverse data sources to improve measurement precision while managing complexity through systematic data processing architecture
Solution Approach 2:
The patent introduces customer metric management circuits as intermediary components that process and analyze integrated data from multiple sources. These circuits act as mediators between raw data and actionable insights, transforming complex multi-source data into customer probability models and behavior predictions, thereby improving understanding precision while abstracting away the complexity of data integration from merchants
2Measurement precision
If merchants collect comprehensive customer data including social media activities, then customer metric accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing system into distinct functional components: account databases for transaction data, social media databases for social activities, and customer metric management circuits for analysis. This segmentation allows each component to handle specific data types and processing tasks independently, improving customer metric accuracy through comprehensive data collection while managing complexity through modular architecture
Solution Approach 2:
The customer metric management circuits perform multiple functions including data integration from diverse sources, probability model generation, customer behavior prediction, and incentive optimization. This multi-functionality consolidates complex processing tasks into unified components, improving metric accuracy through comprehensive analysis while reducing overall system complexity by eliminating the need for separate specialized systems
3Measurement precision
If merchants implement probability modeling using multiple data sources, then customer return prediction accuracy improves, but system resource consumption increases
Solution Approach 1:
The patent implements preliminary data processing and probability model generation by customer metric management circuits before merchants need actionable insights. The system pre-processes transaction and social media data to create customer probability models and behavior predictions in advance, improving prediction accuracy while reducing real-time computational resource consumption by merchants who receive pre-analyzed results
4Loss of information
If merchants analyze both transaction and social media data, then customer insights completeness improves, but implementation difficulty increases
Solution Approach 1:
The patent implements self-service functionality where customer metric management circuits automatically integrate data from account databases and social media databases, generate probability models, and provide customer insights without requiring manual intervention. This automation improves customer insights completeness by systematically processing all available data while significantly easing implementation for merchants who simply need to access the provided insights
Data Source
AI summary
A financial institution computing system includes an account database configured to store a plurality of transaction statistics with respect to a financial account of a customer, a social media database configured to store a plurality of social media activities of the customer, and a customer metric management circuit. At least one of the plurality of transaction statistics is indicative of a first transaction between the customer and a merchant. The customer metric management circuit is configured to determine a probability model of the customer based on the plurality of transaction statistics and the plurality of social media activities of the customer. The probability model indicates a probability that the customer will conduct a second transaction with the merchant in the future. The customer metric management circuit is further configured to provide the probability model of the customer to a device associated with the merchant.