Travel Prediction via Financial Transaction Data Analysis
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Solution Overview
Problem
Travelers face challenges in finding relevant businesses and services at unfamiliar locations, and businesses struggle to identify and offer discounts to travelers, while existing solutions lack efficient methods to predict future travel patterns based on financial transaction data.
Innovation Solution
A system that retrieves historical financial institution transaction data to predict future travel and provides travel-related information, such as merchant offers, by identifying users as travelers based on transaction location and history, using a computing platform with a travel prediction module and communication module to deliver tailored information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If businesses use conventional strategies like handing out flyers to reach travelers, then they can make travelers aware of their business, but the cost and complexity of the marketing approach increases significantly
Solution Approach 1:
The patent introduces a financial institution as an intermediary that possesses traveler identification capabilities through transaction data analysis. This intermediary bridges the gap between businesses and travelers, enabling targeted marketing without requiring businesses to implement complex direct marketing strategies themselves
Solution Approach 2:
The system performs preliminary identification of travelers through analysis of financial transaction patterns before the actual marketing action occurs. By pre-identifying travelers based on spending patterns and location data, the system enables businesses to target the right audience in advance, avoiding wasted marketing resources
2Productivity
If businesses offer substantial discounts to travelers, then they can entice travelers to use their business, but the loss of revenue increases
Solution Approach 1:
The patent applies different discount qualities to different customer segments. By identifying travelers versus local residents through transaction data analysis, the system enables businesses to offer substantial discounts locally targeted at travelers while maintaining regular pricing for local customers, thus optimizing revenue while still attracting travelers
3Measurement precision
If the system analyzes detailed historical transaction data to predict future travel, then the accuracy of travel prediction improves, but the processing time and computational resources increase
Solution Approach 1:
The patent extracts only the most relevant features from historical transaction data for travel prediction, such as spending patterns, location frequencies, and transaction timing. By selecting only the critical data elements rather than processing the entire transaction history, the system achieves accurate predictions with reduced computational overhead and faster processing times
Data Source
AI summary
Methods, apparatus and computer-program products are described for providing travel-location merchant offers to users who are determined to be travelling based on Point-Of-Sale (POS) transaction data. Embodiments of the invention compare the location of the POS transaction to the user's domicile location and if the transaction occurs a predetermined distance or greater from the domicile location, the user is determined to be travelling. Once the travelling determination is made, travel-location merchant offers are identified and communicated to the user.