Aggregated POS Data Market Trend Analysis
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Solution Overview
Problem
Current market data collection methods, such as interviews and indirect techniques, provide limited and inaccurate information, often delayed, making it difficult for investors and stakeholders to understand market trends effectively.
Innovation Solution
A system utilizing aggregated point-of-sale (POS) data from multiple terminals to generate and report market trend data, including transaction details like payment types, volumes, and geographical regions, providing timely and accurate insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional interview and indirect techniques are used to collect market data, then the collection process is simple and low-cost, but the information provided is limited, inaccurate, and delayed
Solution Approach 1:
The patent uses payment network data as an intermediary to access transaction information. Instead of directly interviewing merchants or using complex survey systems, the system leverages existing payment network infrastructure to obtain accurate transaction data, thereby improving measurement precision without building a completely new complex collection system
Solution Approach 2:
The patent replaces manual interview processes with automated electronic data extraction from payment networks. The system automatically retrieves transaction data through programmed queries to payment networks, eliminating the need for human interviewers and their associated inaccuracies and delays
2Loss of time
If interviews with merchants are conducted to obtain market information, then data collection is straightforward, but significant delays occur and information may be inaccurate
Solution Approach 1:
The system performs preliminary actions by continuously maintaining connections with payment networks and pre-configuring data extraction protocols. When market data is needed, the system can immediately query payment networks for transaction information, eliminating delays associated with scheduling and conducting interviews
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring transaction data from payment networks and comparing it against expected market patterns. This real-time feedback loop allows the system to detect and correct inaccuracies promptly, ensuring both timely and reliable market information
3Loss of information
If aggregated POS data from multiple terminals is used, then comprehensive and accurate market trend reports can be generated, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent merges data from multiple payment networks and POS terminals into a unified aggregation system. By combining transaction data from various sources through standardized processing protocols, the system achieves comprehensive market coverage while managing complexity through integration rather than separate processing systems
Solution Approach 2:
The system employs universal data processing components that can handle multiple payment network formats and POS terminal types through standardized interfaces. This multi-functionality allows the system to aggregate data from diverse sources without requiring separate specialized processing systems for each data type
Data Source
AI summary
In one method, a request is received for a market trend report corresponding to a designated payment type over a designated timeframe. A payment type dataset is identified from aggregated POS data. The payment type dataset comprises POS datasets corresponding to the timeframe and to transactions categorized by payment type. Market trend data is generated as a function of the payment type dataset and is output as a report. The method may produce a variety of reports. For example, a report may display the percentage of transactions for each payment type in terms of numbers of transactions. A report may further show whether each payment type is increasing or decreasing in numbers of transactions over the timeframe.