Reward Calculation System for Receipt Data Acquisition
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Solution Overview
Problem
Users are unlikely to transmit receipt information without motivation, as existing systems do not provide clear incentives for doing so, limiting the acquisition of specific purchase details from receipt images.
Innovation Solution
A reward calculation system that calculates and displays estimated rewards based on user attributes and payment information, motivating users to transmit receipt images by offering points that can be redeemed, with higher points given for more valuable receipt information and past transmission history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If reward points are given only after receipt transmission, then businesses can acquire receipt information, but users lack motivation to transmit receipts
Solution Approach 1:
The system performs preliminary calculation and display of estimated reward points before the user actually transmits the receipt. This gives users an immediate incentive and motivation to complete the transmission action, as they can see the potential benefit in advance rather than waiting for post-transmission processing.
Solution Approach 2:
The system provides immediate feedback to users by displaying estimated reward points based on their payment information and user attributes. This feedback loop motivates users to transmit receipts by showing them the tangible benefit they will receive, creating a positive reinforcement mechanism.
2Ease of operation
If estimated reward is displayed before receipt transmission, then user motivation increases, but system complexity increases
Solution Approach 1:
The system calculates estimated rewards by changing and evaluating multiple parameters including payment information, user attributes, and transmission history. This parameter-based approach allows for flexible and personalized reward estimation without requiring complex system architecture, as it relies on variable substitution and calculation rather than complex processing logic.
Solution Approach 2:
The system automatically performs the reward estimation calculation and display without requiring manual intervention or complex configuration. The calculation is self-executing based on available data, reducing the operational complexity while providing personalized estimates to each user.
3Loss of information
If higher points are given for valuable receipt information, then data collection quality improves, but reward calculation complexity increases
Solution Approach 1:
The system applies different reward point values to different types of receipt information based on their local quality and value. Rather than using a uniform calculation method, it assigns specific weights and point values to different transaction attributes, allowing for differentiated reward structures that reflect the actual value of the data being collected.
Solution Approach 2:
The reward calculation system uses parameter changes by adjusting point values based on user attributes, payment information, and transmission history. This allows the system to dynamically calculate rewards that reflect data quality without requiring a fundamentally complex algorithm, as it relies on parameter substitution and weighted calculation.
Data Source
AI summary
Provided is a reward calculation system including at least one processor configured to acquire payment information about a payment of a transaction object traded on a user terminal used by a user; acquire a user attribute of the user; calculate an estimated reward potentially provided to the user terminal, based on at least the payment information and the user attribute; cause the user terminal to display the estimated reward; and acquire, after the estimated reward is displayed, receipt information included in a receipt image in which a receipt issued for a transaction of the transaction object is displayed.