The Hidden Gold in Your Payments Data
“The only true wisdom is in knowing you know nothing.” -a quote famously credited to Socrates, the great Greek philosopher (or was it the Brazilian soccer player…?)
While we have no intention of getting into an argument about philosophy (or soccer, for that matter), we here at Pagos do know that there is a lot of knowledge to be found in payments data. Unfortunately, a lot of this knowledge is not readily (or not at all) available to most businesses. This was a known fact causing serious pain points for a fast-growing number of companies that have now discovered Pagos’ unique capabilities to unlock their payments data.
With the new levels of awareness that our suite of payments intelligence microservices bring, most of our customers also end up finding previously hidden issues and opportunities. Which brings us from philosophy to psychology—metacognition to be exact—with the phrase “you don’t know what you don’t know.” In Pagos-speak, we call this flying blind.
Having blind spots in your business—especially your payments stack—can cost you. We would argue that pretty much all businesses have some form of hidden gold in their payments data that can help them uncover and address those costly blind spots. And what could be more relevant today—in an economy where companies, teams and people are being asked to do more with the same (or less) resources—than finding ways to optimize your existing payment stack?
To demonstrate what we mean when we talk about the gold you can find in your payments data using the Pagos suite of products, let’s dig into some real world examples! In each of the sections below, we’ll look at the areas of payments data where our existing clients have found blind spots they hadn’t previously identified, and the actions they took in response.
Exploring Approval Rate by Country
Client’s Business Model: US-based digital goods merchant, accepting credit cards, selling in USD, single payment service provider (PSP)
- Use Case: Visualizing sales and authorization performance by issuing bank using Peacock by Pagos
- Awareness/Advice Acquired: Realized a relatively significant portion of their total volume came from cards issued in Australia, and those cards had a significantly lower approval rate compared to US-issued cards
- Action Taken: Switched to processing AU-issued cards locally in AUD with significantly higher approval rates
- Hidden Gold: Actions taken resulted in better consumer experiences and increased revenue for the business
Understanding Sub-Merchant Performance
Client’s Business Model: Marketplace operating as the payment aggregator, has thousands of sub-merchants, using multiple PSPs
- Use Case: Filtering all data down to the soft descriptor level in Peacock by Pagos
- Awareness/Advice Acquired: For the first time, the business could see both payments performance and chargeback data from the top level (them as merchant of record) and down to the individual sub-merchant level, plus across the 3 key PSPs they’re using; this serious slicing and dicing of data lead to them creating entirely new benchmarks and metrics
- Action Taken: With this new, detailed knowledge of each sub-merchant’s performance, profitability, and risk, the business created custom Peacock dashboards per sub-merchant group and used Canary by Pagos to monitor and send alerts of data anomalies—again, down to the sub-merchant level
- Hidden Gold: By catching performance opportunities and/or risk issues within the hour (instead of end of month/quarter), this business can increase their revenue and decrease costs
Digging Into Declines
Client’s Business Model: Global merchant in the travel industry, using a combination of fraud tools, including integrated fraud tools from their PSPs
- Use Case: Visualizing trends in decline codes—both aggregate and per PSP—against real-time data in Peacock (made possible by the ability to load historical data into the Pagos platform while simultaneously pulling real-time data from three PSPs via a no-code integration)
- Awareness/Advice Acquired: With the new ability to look at normalized data (apples to apples) across all their PSPs, one decline code that jumped out from one of their PSPs was “Gateway decline”
- Action Taken: After further investigation, it became clear that the unusually high % of “Gateway declines” were actually false positives caused by rules within the integrated fraud tool (from the PSP), requiring updates/corrections
- Hidden Gold: Fixing this issue resulted in increased approval rate and increased revenue
Going From Unknown Unknowns to Known Knowns
The examples above range from basic to more advanced, but here’s the thing: even “basic” payments issues can be difficult for a business to uncover, measure, and act upon. To confidently find the gold hidden in your payments data, you need the ability to easily (and quickly) go from a high-level/wide, birds-eye view of your data, to a laser focused, deep dive. And, if the gold is in the shape of catching some form of anomaly before it becomes a serious issue (with serious costs attached),well, you know what they say: the early bird gets….
This is where Pagos comes in. With our suite of microservices, removing blind spots and finding the hidden gold in your data doesn’t have to feel like an impossible dream. You can be in the driver’s seat to uncover issues or opportunities and quickly act to improve both your top and bottom line—all without making any changes to your existing payment stack.
If you want to share examples of blind spots in your own payments data (we would love to keep the conversation going), please contact us: