ATM Network Data Warehouse for Real-Time Ad Targeting
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Solution Overview
Problem
Current methods for analyzing self-service terminal networks and selecting advertisements are inefficient, as they rely on manual reporting that takes weeks or months, and do not allow for real-time data analysis or personalized queries, making it difficult to optimize advertising content for specific fleets of ATMs.
Innovation Solution
A method and system for collecting and storing environment, transaction, and advertising data in real-time or near real-time in a data warehouse, enabling querying and analysis to determine the effectiveness of advertisements and selecting relevant content for display on self-service terminals based on location, transaction types, and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reporting methods are used to collect and analyze ATM fleet data, then data aggregation can be achieved, but the time lapse between data gathering and report finalization becomes unacceptably long (weeks or months)
Solution Approach 1:
The patent replaces manual mechanical data collection and analysis processes with automated electronic data gathering systems. Terminals automatically transmit transaction data, environment data, and advertising data to a central server, which then automatically analyzes the data using computer algorithms to generate reports and select advertisements, eliminating the weeks or months delay inherent in manual processing.
Solution Approach 2:
The system enables self-service data collection where terminals automatically gather and transmit their own transaction, environment, and advertising data without human intervention. The central server then autonomously processes this data to generate insights and advertisement selections, making the entire data analysis pipeline self-service and eliminating manual reporting bottlenecks.
2Loss of information
If aggregated reports are prepared from multiple deployers' ATM fleets, then general trends can be identified, but the reports cannot be customized or queried for specific fleet requirements
Solution Approach 1:
The patent implements local quality by maintaining separate data profiles for each deployer's ATM fleet while still benefiting from aggregated analysis. The system stores and analyzes data specific to each fleet's terminals, transactions, and environments, allowing customization of reports and advertisement selections for individual fleets while still utilizing the broader aggregated data for trend identification.
Solution Approach 2:
The system segments the aggregated data by deployer fleet, allowing the central server to process and analyze data in organized groups. This segmentation enables the generation of customized reports and advertisement selections for each specific fleet while maintaining the ability to perform overall trend analysis across all fleets, thus providing both general insights and fleet-specific customization.
3Productivity
If real-time data collection and analysis is implemented, then advertisement effectiveness can be rapidly assessed, but the system complexity and data processing requirements increase significantly
Solution Approach 1:
The patent implements a universal data warehouse system that handles multiple data types (transaction data, environment data, advertising data) and performs multiple functions (data storage, analysis, report generation, advertisement selection) through a single integrated platform. This multi-functional approach manages system complexity by consolidating diverse operations into one cohesive system rather than requiring separate systems for each function.
Solution Approach 2:
The central server acts as an intermediary between the distributed terminals and the data warehouse, managing data collection, transmission, and processing. This intermediary layer simplifies the overall system architecture by providing a single point of coordination, reducing the complexity burden on individual terminals while enabling real-time data aggregation and analysis across the entire network.
Data Source
AI summary
An ATM network is coupled to a data warehouse. Information about transactions, the timing of transactions and advertisements displayed on or near ATM terminals in the network are stored in the data warehouse. Complex queries performed on the data warehouse are then used to provide information about the effectiveness of advertisements displayed on or near the ATM terminals and also to enable choices of subsets of the terminals to be made to provide information about suitable subsets for advertising placement.