Think about the swathes of data that your business uses every day to make smarter decisions. Without it, you are operating in a vacuum of personal opinions and guesswork. That’s why data, and the tools that help you collect and analyze it, are so important.
Yet for some reason, payments data has not been treated with the same priority. Rather, payments are seen as a process. The only data point that seems to matter is the one registered by your accounts receivable team, reconciling when the payment has arrived. Everything else comes a poor second.
Yet every individual transaction generates a treasure trove of data. Used effectively, payments data is much more than a passive management reporting tool. It is actionable.
Aggregated and explored, it can unlock patterns and insights to improve every aspect of your payments strategy. This could be from the methods you should offer your customers to automating their payment experience. Or from ensuring more payments go through successfully to comparing the total economic impact of different payment service providers (PSPs).
Payments data needs to be a priority for your PSP too
Of course, knowing the value of payments data is only half the story. If you can’t collect and visualize the data in a meaningful and timely way, then the value is just theoretical.
So it’s crucial that the PSPs you work with prioritize data visibility as much as you. Whether a payment platform is integrated into a wider suite of solutions, or you’re using it in a standalone fashion, your payments data should be at your fingertips whenever you need it.
The larger your business, the more likely you’ll work with multiple PSPs. You’ll want to connect all of that data to see the whole picture. But you’ll also want to get forensic. You’ll want to segment it, so you can drill down into each country and market you operate in. That’ll let you optimize payments strategies locally, and compare the total economic impact that each PSP is delivering.
Here’s a look at some of the key payments data points that your business should be looking at. Each insight can help you elevate payments from a financial process to a core part of your BI strategy.
1. Customer preference
Knowing how your customers want to pay, and how that preference differs from product to product and country to country, is the definition of having a data-driven customer centric strategy. Many businesses commission research to find the answers. But if you’re already offering multiple payment methods to your customers, you should have this data residing in your systems.
Extract the data and use it to inform the most attractive payment methods for each product and market. This insight can transform payments into a marketing tool to help you win new customers. Equally you can use this preference data to stop investing in payment methods that are not gaining you new business.
2. Conversion rates
Improving the customer experience is a key outcome of payments data. For example, what is your data telling you about how easy it is for your customers to sign up to a payment method? If it’s showing that customers are failing to complete a set up, then it may be that the process is too complex and lengthy.
Worse still, if you’re seeing a lot of people leave a payment sign up page without even starting. That could point to an issue with the design, rendering or functionality of the form. Equally if a payment method is converting well, what is it about that process that you can apply to the other payment types you offer?
3. Authorization rates
As you will know, payment authorization rate, sometimes known as payment success, is the measure of how many attempted transactions are completed. There are a number of reasons why a payment may fail. Your customer may not have the necessary funds in their bank account, a card may have expired, or fraudulent intent has been identified.
The immediate role of your data is to flag when a payment has been unsuccessful, and why. Automation is key here. Triggering a message to your customer in real-time, when they are still in purchasing mode, makes them more likely to retry straight away.
Better still if you can take the onus away from your customers. Increasingly PSPs are using data and machine learning to automate first time and retry payments. By using data to “learn” when a customer is more likely to have money in their bank account, or credit on their cards, your business can schedule a payment for a day and time when it is more likely to be successful.
And when you move from detecting payment failures to preventing them, you reduce checkout abandonment and the costs associated with chasing outstanding invoices.
As all businesses know, a chargeback brings multiple concerns. Most obviously, when a transaction is queried and the funds returned to your customer, you lose revenue from the sale that never was. Then you get a second hit when your PSP and bank levies their charges. Add to that the reputational risk to your brand if you don’t deal with legitimate queries swiftly, or if your business becomes a soft touch for fraudulent claims, and you soon understand how critical it is to get a grip on chargebacks.
Two key payments data points are important. Firstly, knowing when a chargeback request has been made. The sooner you know, the sooner you can investigate it and respond. The second key data point is understanding the reason why the transaction has been disputed. Each chargeback will come with an alphanumeric “reason code” that explains why your customer wants their money back. Each PSP will have their own set of codes, such as our chargeback codes list.
Much like payment authorization, speed and visibility are key requirements of chargeback data. “How soon will I be made aware of a chargeback?”, and “How much information will I be told?” are two questions you should ask every PSP. But more payment insights can give you so much more.
For example, by aggregating your chargeback data over time, you can benchmark your business against your sector, and also compare PSPs against one another. Knowing that a particular payment method or PSP is consistently resulting in more chargebacks is an incredibly valuable insight. This complete data view of chargebacks will also let you predict the amount of chargebacks you are likely to face and budget accordingly. And peaks will be easier to spot too, which may be a sign of something wrong with your products, that your customer service has gone awry, or your business has become a target of fraud.
5. Clearing and reconciliation
SMBs with precarious liquidity and tight margins have always prioritized cash flow. But with the Covid-19 economic downturn, cash flow has also come into sharper focus for larger enterprise businesses. Knowing how long it takes for your customers’ money to land in your bank account is arguably the most important payments metric of all.
The key here is not simply knowing the various clearance times of each payment method and PSP. Rather, it’s about being able to pull through the ‘live’ data into your other finance and banking systems. Equally, if your payments data is set up to speak with your accounting software, then you’ll be able to automate much of the reconciliation process, identify habitual late payers, and reward customers who pay on time.
Find out more about how merchants use data in our new report Black Boxes and Paradoxes: The Costs of Disconnected Payments
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