Indirect Customer Identification via Payment Data Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing customer identification methods in retail environments are invasive, prone to inaccurate data entry, and can slow down transactions, while direct identification techniques face challenges due to customer resistance and regulatory changes.
Innovation Solution
A system and method that automatically updates a retailer's transaction database by extracting a reverse append name from a payment mechanism to associate customers with transactions and accounts, using a scoring system and demographic data to make educated guesses about customer identity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct customer identification methods are used, then customer identification accuracy is improved, but customer resistance increases and transaction time increases
Solution Approach 1:
The patent uses an intermediary approach by extracting the customer name from the payment mechanism (credit card) and using it as a key to look up customer records in the database. This intermediary method avoids direct customer interaction while still achieving accurate identification through the payment data that already contains the customer's name.
Solution Approach 2:
The system performs self-service identification by automatically extracting the customer name from the payment mechanism and autonomously matching it with customer records in the database without requiring any active participation or input from the customer. The system serves itself by using the payment data to trigger the identification process.
2Measurement precision
If direct customer identification methods are used, then customer identification accuracy is improved, but customer resistance increases
Solution Approach 1:
The patent uses an intermediary approach by extracting the customer name from the payment mechanism (credit card) and using it as a key to look up customer records in the database. This intermediary method avoids direct customer interaction while still achieving accurate identification through the payment data that already contains the customer's name.
Solution Approach 2:
The system performs self-service identification by automatically extracting the customer name from the payment mechanism and autonomously matching it with customer records in the database without requiring any active participation or input from the customer. The system serves itself by using the payment data to trigger the identification process.
3Measurement precision
If manual customer information entry is required, then data accuracy can be verified, but transaction speed decreases
Solution Approach 1:
The system performs preliminary action by pre-extracting the customer name from the payment mechanism before the transaction completes. The name is extracted and used to automatically match with customer records in the database, so that when the transaction is processed, the customer identification is already complete without requiring additional manual input or verification steps.
Solution Approach 2:
The system performs self-service identification by automatically extracting the customer name from the payment mechanism and autonomously matching it with customer records in the database without requiring any active participation or input from the customer. The system serves itself by using the payment data to trigger the identification process.
Data Source
AI summary
A database system and method is presented that updates a retail transaction database for each transaction by extracting a name from a payment mechanism. Associations already made between the customer records, the transactions database, and the payment account database are used in conjunction with the extracted name to create additional associations between customers and transactions and between customers and payment accounts. In addition, new customer records can be created by searching demographic databases using the reverse append name and data associated with the transaction already in the database.