Transaction Data Spending Distribution Media Optimization
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Solution Overview
Problem
Current systems for processing transaction data from payment cards lack effective methods to optimize media content presentation based on spending distributions, leading to inefficient advertising and customer engagement.
Innovation Solution
A system that identifies transaction data associated with account identifiers to determine spending distributions, schedules media content presentations across categories, and adjusts content based on these distributions to optimize engagement and advertising effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If transaction data is processed and analyzed to determine spending distributions, then media content presentation can be optimized for customer engagement, but system complexity increases due to additional processing and analysis requirements
Solution Approach 1:
The system segments media content into different categories and schedules their presentation based on spending distribution patterns. Transaction data is segmented by merchant category, and the spending distribution is calculated across these segments to determine optimal presentation timing and frequency for each category.
Solution Approach 2:
The system performs preliminary analysis of transaction data to determine spending distributions before scheduling media content presentations. By pre-calculating the spending distribution across different merchant categories, the system can proactively schedule optimized media presentations without requiring real-time complex processing during media delivery.
2Productivity
If media content presentations are scheduled based on spending distribution, then advertising effectiveness improves, but the difficulty of detecting and measuring customer behavior patterns increases
Solution Approach 1:
The system uses transaction data as feedback to continuously refine and update spending distribution calculations. By analyzing actual transaction patterns and comparing them against scheduled media presentation performance, the system iteratively improves its ability to detect and measure customer behavior patterns, making the measurement process more accurate over time.
Data Source
AI summary
In one aspect, a computing apparatus is configured to profile the spending distribution of users who have made purchases from a merchant and who have paid for the purchases via a transaction handler (e.g., using credit cards, debit cards, prepaid cards). The spending distribution is determined based on transaction data of the users, where the transaction data records the transactions of the users for purchases from various merchants. The spending distribution is profiled to indicate the preference of the customers of the merchant as a whole and thus can be used to customize the ratio of media content provided to the customers of the merchant, such as the presentation ratio of advertisements from different merchants, or from merchants of different categories.