Let’s take a look about how you can surface the underlying details of your overall approval rate to determine if there are aspects of your user experience and payment processing that are hurting your bottom line.
In the Peacock Service Panel, the Default Dashboard includes a graph of your top-level approval rate trends over time, broken down by processor. This is a key data visualization because it aggregates all of your approval rate data into one view and gives you a read on how you're performing—the higher the approval rate, the more sales you make, and therefore the more revenue you receive. No company can get 100% approval of all transactions if you have more than a few customers, but understanding how many are approved—especially when broken down by different variables—gives you insight into how you can improve.
Like any aggregate measure, the approval rate measurement is inclusive of many different card types, card locations, currencies, and more. So when assessing if your trend is good—or how much more opportunity there may be to improve your payments performance—it’s important to look at the trends broken down by these variables. For example, examining approval rate by card type shows you how different cards perform over time, and how they relate to each other.
For that, Pagos provides the Card Type Report, which breaks down approval rate and volume trends by card type, showcasing how many payments are coming in across the different card types and how each card type is performing overall.
Consider a situation in which you look at the Payment Type Transactions graph in the Card Type Report and notice just under 70% of your processed transactions in the last 7 days came from credit cards; the rest are split between prepaid, debit, and some are unknown. With this, you now know your credit card approval rate will have a big impact on your overall approval rate and revenue.
To dig a little deeper into this, you look at the Credit vs. Debit Approval graph in the same report for the same 7 days to view how the decline code distribution for credit cards differs from debit cards. When viewing the details in this way, you notice:
- The approval rate for credit cards is 93.15% overall, with the most frequent declines as decline_already_voided and do_not_honor
- The approval rate of debit cards is 99.94%, with only a small percentage being declined as decline_gateway.
You've learned credit cards make up the largest share (70%) of your transaction volume. In exploring the decline codes assigned to credit card declines, you learn the following:
- Some declines were for transactions that have already been voided (decline_already_voided). This is a signal there may be an issue in the payment processor integration.
- You have a number of CVV-based declines (decline_cvv_negative) for credit card transaction. These can be mitigated by changing the user experience, or A/B testing changes in CVV collection.
- You've been attempting to process transactions for a number of expired cards (expired_card), which signals opportunities to either update your tokens or contact your customers to update their card on file.
Reducing any of these declines would provide both increased revenue and happier users who are probably being declined for technicalities.
It’s impossible to know if anything can be done to address declines without opening up the details in your own data to come up with strategies to address. How much would an additional 1% in approved transactions mean to your revenue and your customers?
Updated 13 days ago