Business Hours Validation via Transaction Data
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Solution Overview
Problem
Users are often frustrated when they arrive at a business location based on inaccurate hours of operation provided by online services, leading to disappointment and a loss of trust in the service, as the actual hours may differ from what is displayed.
Innovation Solution
A computer-implemented method that validates business hours by aggregating data items from disparate sources, such as credit card transactions and employee presence, to determine the likelihood of inaccuracy, and provides estimated hours of operation to users and businesses, while suggesting modified or corrected hours based on user interaction patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If businesses input their own hours of operation to an online service, then the service can provide hours information to users, but the accuracy of the hours information deteriorates because businesses may provide incorrect or outdated information
Solution Approach 1:
The system implements feedback loops where user interactions (visits, transactions) are continuously monitored and fed back to validate and update business hours information. This creates a self-correcting mechanism that improves accuracy over time without requiring manual verification of each business.
Solution Approach 2:
The system enables automatic validation of business hours using disparate data sources such as credit card transactions, employee check-ins, and customer visits. The system self-regulates by comparing multiple independent data streams to determine actual operating hours without human intervention.
2Measurement precision
If the system collects multiple data items to validate hours of operation, then the accuracy of validation improves, but the complexity of the system increases
Solution Approach 1:
The validation system is segmented into independent modules that each process specific types of data (transactions, visits, employee data). Each module independently validates hours based on its data type, and results are aggregated. This modular approach improves validation accuracy while managing complexity through separation of concerns.
Solution Approach 2:
The system uses a universal validation framework that processes multiple types of disparate data items through a common analysis engine. The same core logic handles different data sources (transactions, visits, employee check-ins), reducing overall system complexity while maintaining high validation precision.
Data Source
AI summary
A system for validating hours of operation may include one or more computing devices and a memory. The one or more computing devices may receive hours of operation of a business for a day of a week and receive data items that are associated with a time of the day of the week, wherein the data items are also associated with the business being open or closed at the associated time of the day of the week. The one or more computing devices may determine, based at least in part on the data items, a likelihood that the hours of operation of the business for the day of the week are inaccurate. The one or more computing devices may provide to an electronic device associated with the business an indication that the hours of operation for the day of the week are likely inaccurate when the likelihood satisfies a threshold.