Data Monetization for Credit Card Providers with Location Intelligence
Company Size
1,000+
Region
- America
- Asia
- Europe
- Pacific
Country
- Australia
- Canada
- United Kingdom
- United States
Product
- Mastercard Retail Location Insights (MRLI)
Tech Stack
- Location Intelligence
- Data Aggregation
- Quadkey Framework
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Revenue Growth
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
- Retail
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
- Supply Chain Visibility
Services
- Data Science Services
- System Integration
About The Customer
Mastercard is one of the world's largest and most recognizable financial services companies. Founded in 1966 as the Interbank Card Association, the company has grown significantly over the decades. As of 2018, Mastercard's revenue was ranked at #236 among Fortune 500 companies. The company's credit card and merchant networks are expansive and span the globe. In 2018, there were 231 million Mastercard credit cards in the US and 644 million cards in the rest of the world. With a total purchase volume of $811 Billion, Mastercard's network is the world's 2nd largest credit card network. Every hour, Mastercard customers make over 160 million transactions. These transactions represent Mastercard's core business, serving as the connection between consumers looking for a safe and seamless purchasing experience and their merchants.
The Challenge
Mastercard, one of the world's largest financial services companies, processes over 160 million transactions every hour. This transaction data is extremely valuable and represents a significant resource for the company. However, monetizing this data presents several challenges. Firstly, any data monetization strategy must prioritize data privacy and security to maintain Mastercard's promise of keeping payments safe and secure. This requires anonymizing and aggregating the data to remove individual identifiers and prevent the inference of specific identifiers once the data has been aggregated. Secondly, the data needs to be productized in a way that appeals to a diverse audience with varied needs. This requires delivering an intuitive and singular user interface while ensuring the user experience is tailored based on industry and role. Lastly, the spatial nature of the transaction data presents challenges in determining the spatial scales at which to aggregate data. This is particularly complex when working internationally, as different countries have distinct geographic units.
The Solution
Mastercard partnered with CARTO to launch the Mastercard Retail Location Insights (MRLI) solution. This solution was designed to meet the challenges of data privacy and security, provide insights at a wide range of spatial scales, and ensure a positive user-experience for professionals across dozens of industries. To ensure data privacy and security, Mastercard anonymizes and aggregates their data, removing individual identifiers and implementing safeguards to prevent the inference of specific identifiers. The MRLI solution uses a new Quadkey Framework for data aggregation that allows users to explore retail insights in a custom area without pre-defined boundaries. This allows for greater flexibility in examining and interpreting transaction patterns and trends. The solution also allows for filtering by industry categories for greater detail and segmentation, broadening its appeal to analysts across dozens of industries. Additionally, users can upload outside data points to view within the wider retail context, allowing for a greater degree of custom analysis.
Operational Impact
Quantitative Benefit
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