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As far as external data goes, payment is one of the most valuable categories. Payment datasets usually come with high ticket sizes. Nonetheless, there’s always demand for payment data across job types and industries: quant investors, market analysts, cybersecurity companies, ecommerce platforms, brick-and-mortar retailers. And so payment data monetization is a lucrative opportunity.
In this guide, we’ll look at what payment data actually is, before examining the revenue opportunity using examples of successful data monetization. We’ll also cover some of the business use cases for payment, which will inform your data monetization strategy, before looking at how you can monetize data, common challenges, and some main ‘Dos’ and ‘Don’ts’ based on our experience working with leading data sellers.
What is payment data?
Payment data refers to information that’s captured at the point of sale (POS), which is why payment data also often called POS data. It’s collected whenever a transaction takes place between a consumer and merchant via digital means. A payment dataset usually comprises the following data points:
- Transaction activity
- Payment patterns and preferences
- Product data
- Location of purchase
- Merchant details
Payment data also refers to metadata (data about the data) which tells you about data quality, data provenance, where it’s stored, and what it means. You can collect metadata by assembling quantitative and qualitative information on partners, products, and public data that contextualizes and corroborates the internal data. For example, reports and surveys that confirm public sentiment or tech trends.
In short, payment data can tell you about consumers' buying behavior, preferences, and patterns, providing invaluable insights into market trends and customer habits. It helps businesses in making informed decisions and developing effective strategies. Moreover, it can aid in fraud detection and risk management.
How big is the opportunity of payment data monetization?
The best way to conceptualize the opportunity presented by monetizing payment data is to understand the size of the digital payment. Grand View Research found that, globally, the digital payment market size was estimated at USD 96.07 billion in 2023 and is expected to grow at a compound annual growth rate (CAGR) of 21.1% from 2024 to 2030. According to the data published by The World Bank, at the end of 2021, more than 2/3 adults worldwide were making or receiving digital payments. This number is expected to increase more in coming years.
So the amount of payment data is set to increase as the market for it grows. With such promising economic conditions, if anything, it’s surprising that more organizations haven’t begun monetizing payment data. Banks in the U.S. alone have one exabyte of data stored which they could monetize. Some pioneering organizations have already started doing so. Let’s look at two examples.
Neobanks
The neobank Revolut sells aggregated panels of payment data. With over 30 million users worldwide, there’s a dizzying amount of payment data Revolut can capture and monetize. The neobank’s data monetization is enabling them to add net-new revenue to their growing company and product, as well as informing their customer personalization and retention strategies. Namely, the payment data they collect enables them to help banking users save and spend more efficiently.
Credit scoring platforms
ClearScore, a credit scoring platform, utilizes payment data to provide a more accurate and comprehensive credit score to its users. The platform analyzes payment patterns, transaction activity, and other relevant data points to evaluate a user's creditworthiness. It then makes this data available to purchase in the form of anonymized payment datasets.
Why businesses are buying payment data
There are dozens of use cases for digital payment data. That’s why it’s one of the most valuable data categories you can monetize. Let’s have a look at three of the most common reasons businesses are investing in external payment data.
End-to-end consumer analytics
By analyzing payment data, banks can understand their customers' spending habits and financial goals. This information allows them to offer tailored advice and suggestions on saving money, based on the individual's purchase activity. For example, if a customer frequently spends on dining out, the bank might recommend budgeting tips or suggest cashback offers at restaurants to help them save. Ultimately, leveraging payment data enables banks to provide personalized experiences that cater to the unique needs and preferences of each customer, fostering a stronger relationship and enhancing customer satisfaction.
Early bug and payment failure detection
Payment and point-of-sale (POS) data can swiftly identify bugs and payment failures for both payment service providers and merchants. By monitoring transaction patterns and anomalies, providers can promptly address any technical issues or glitches in the payment process. This proactive approach ensures seamless transactions, boosts customer confidence, and minimizes revenue loss for merchants. The end result is a smooth payment experience for all parties involved, and a positive ROI for the data purchased.
Credit scoring and loan approval
Insights into personal consumer finances are a reliable way of understanding their credit history. Especially with the massive uptake in consumer ‘Buy Now, Pay Later’ services like Klarna, payment data can shed light on spending and loaning history in a way that traditional credit scoring services cannot. For that reason, lending companies are investing in payment data to inform their loan approval decisions. For example, Nova Credit empowers consumers to share their transaction and payment data to the credit scoring platform for reimbursement. Buying this payment data enables the platform to amass more insights which enables them to make better informed decisions on loan approval.
How easy is it for merchants to monetize payment data?
Monetizing payment data can be a lucrative venture for merchants, but it requires careful planning and execution. Here are three key steps to make the process smoother:
1. Evaluate your current people, process, technology
Before diving into payment data monetization, merchants should assess their existing infrastructure, team expertise, and technological capabilities. Understanding the resources available will help identify potential gaps and areas for improvement to ensure a seamless monetization process.
2. Select which data points to monetize based on demand
Not all payment data is equally valuable. Merchants should analyze market demand and consumer preferences to determine which data points are most sought after by potential buyers. This could include transaction volumes, customer demographics, purchase behavior, or other relevant metrics that hold value for third-party organizations.
3. Join a data monetization platform
To effectively monetize payment data, merchants can leverage data monetization platforms that connect them with potential buyers while ensuring data privacy and security. These platforms offer a streamlined process for data exchange, facilitating negotiations, agreements, and transactions between merchants and data buyers. By joining a reputable platform, merchants can maximize the value of their payment data while minimizing risks and administrative burdens.
How is payment data aggregated?
Payment data can be anonymized and aggregated into payment panels. Creating a data product or panel from aggregated payment data involves several steps to ensure accuracy, compliance, and marketability:
1. Data Collection and Aggregation
Begin by collecting payment data from various sources such as point-of-sale systems, online transactions, and mobile payments. Ensure that the data collected complies with relevant privacy regulations such as GDPR or CCPA. Next, aggregate the collected data into a unified dataset, anonymizing sensitive information to protect customer privacy.
2. Data Processing and Enrichment
Once aggregated, process the payment data to ensure consistency and accuracy. This may involve cleaning the data to remove duplicates or errors and standardizing formats for easier analysis. Additionally, enrich the dataset by incorporating relevant metadata such as transaction timestamps, geographic locations, and merchant categories to provide valuable context for analysis.
3. Market Research and Packaging
Conduct market research to identify potential buyers and understand their specific needs and preferences. Package the aggregated payment data into a data product or panel that aligns with market demand, highlighting key insights and use cases that demonstrate its value. Consider partnering with data monetization platforms or reaching out directly to potential buyers to market and sell your data product effectively.
Payment data monetization: Dos and Don’ts
Feeling inspired to kickstart your payment data monetization strategy? We’ll round off this article with some main How to Sell Data Dos and Don’ts:
Do
- Audit your existing data governance before monetizing your payment data
- Invest in the right infrastructure to share data securely
- Look at how your competitors are packaging and pricing their pricing data products
Don’t
- Neglect privacy laws and regulations when sharing data
- Overlook the importance of data quality and accuracy
- Ignore feedback from your data buyers to iterate on you data products
Data monetization is a combined effort, requiring partnerships - just like any other business. To find out how Data Commerce Cloud™ can support your data monetization strategy, get in touch.
