Transaction Data Recommender for Hotels

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Solution Overview

Problem

Hotels and other establishments lack the ability to provide objective and data-driven recommendations for merchants and attractions to their customers due to limited staff or the absence of a concierge service, relying instead on personal experiences which may not be comprehensive or accurate.

Innovation Solution

A system utilizing a recommender computing device that processes historical transaction data from a payment processor to generate a ranked list of recommended merchants based on the activities of previous customers, allowing hotels to provide data-driven recommendations without the need for a concierge service.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a concierge service is provided to give merchant recommendations, then the quality and objectivity of recommendations improves, but the operational cost and complexity increases

Engineering Contradiction:

Improverecommendation accuracyVSAvoidservice structure

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system enables self-service by automatically generating merchant recommendations using transaction data without requiring human concierge intervention. The payment processing system itself performs the recommendation function by analyzing historical transaction patterns and identifying frequently visited merchants, eliminating the need for dedicated staff while maintaining objective, data-driven recommendations.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical human concierge system with an automated computational system. Instead of relying on human knowledge and judgment, the system uses algorithmic processing of transaction data to generate recommendations, substituting human labor with automated data analysis and pattern recognition.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If historical transaction data is processed to generate recommendations, then the objectivity and reliability of recommendations improves, but the data processing complexity and time increases

Engineering Contradiction:

Improverecommendation reliabilityVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary action by pre-processing and storing transaction data in an optimized format during normal payment processing operations. Data is aggregated and structured in advance, so when recommendations are needed, the system can quickly query pre-organized information rather than processing raw transaction data from scratch, reducing retrieval time while maintaining comprehensive analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system maintains continuity of useful action by continuously processing and analyzing transaction data as transactions occur, rather than batch-processing periodically. This ongoing analysis ensures recommendations are always based on the most current data while distributing the processing load over time, preventing large time losses at any single moment.

Inventive Principle:

Principle #20Continuity of useful action

3Loss of information

If comprehensive transaction data is analyzed to provide accurate recommendations, then the relevance and quality of recommendations improves, but the information processing requirements and system complexity increases

Engineering Contradiction:

Improveinformation completenessVSAvoidsystem architecture

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system applies extraction by isolating and focusing on specific relevant fields from comprehensive transaction data, such as merchant identifiers, transaction frequencies, and customer patterns. Rather than processing all raw transaction information, the system extracts only the essential elements needed for recommendation generation, reducing processing complexity while maintaining recommendation quality.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent implements universality by designing a multi-functional payment processing system that simultaneously handles transaction processing, data aggregation, pattern analysis, and recommendation generation. This integrated approach allows the same system infrastructure to serve multiple purposes, reducing overall system complexity compared to having separate specialized systems for each function.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10163147B2Systems and methods of location based merchant recommendations

Publication Date: 2018.12.25 MASTERCARD INT INC

AI summary

A method for generating a list of recommended merchants based on an input merchant is provided. The method uses a recommender computing device. The method includes receiving an input merchant identifier, retrieving a first electronic data signal based on the input merchant identifier including historical transaction data of the input merchant including historical payment transactions initiated by candidate cardholders with the input merchant, and storing a list of the candidate cardholders. The method further includes retrieving a second electronic data signal that includes historical transaction data for at least some of the candidate cardholders included in the list of candidate cardholders and a candidate merchant identifier that identifies the candidate merchants, generating a list of candidate merchants from the second data signal including a ranking of the candidate merchants, and generating a list of recommended merchants based on the list of candidate merchants.