What's Missing From Your Approval Rate?
A near-perfect approval rate might look like a win, but without full visibility into blocked transactions, you could be missing hidden revenue opportunities.
Approval rate is calculated by dividing your total approved transaction count by your total attempted transaction count. It’s a straightforward metric with clear value: it represents the percentage of potential transactions that successfully contributed to your incoming revenue or the proportion of customers who had a satisfactory experience with your business.
Merchants often consider a high approval rate the holy grail of optimization—numerical proof they’ve successfully accepted payments from every legitimate customer who went through their checkout flow. In the name of maximizing approvals, they’ll execute strategies like:
Analyzing decline codes to identify addressable issues in their payments infrastructure
Employing network tokenization or account updater solutions to keep stored payment cards up-to-date and minimize churn
Identifying opportunities to set up local processors in regions where demand is high
But are more approvals always better? Could an approval rate that nears 100% actually be hiding lost revenue?
The Catch
An approval rate that approaches perfection might not be the unqualified success it appears to be. Before you celebrate, you must first ask what transactions were excluded from the approval rate calculation. For example, if a transaction was blocked before ever making it to the processor, did you count it as a transaction attempt? If not, that near-perfect approval rate isn’t as it seems. In fact, it could hide a whole segment of potential transactions who’ve been blocked early in the funnel (i.e. lost revenue opportunities).
One of the most common ways merchants lose revenue is through overly restrictive fraud filters or rules that block legitimate customers before they even attempt a payment. For example, customers from certain regions or those using specific payment methods might be preemptively blocked because they are deemed “high risk.” Similarly, mismatches in billing and shipping addresses or unusual purchasing patterns might trigger automatic rejections that could have otherwise been valid.
While these measures are designed to minimize fraud, they can inadvertently alienate good customers, leading to abandoned carts and lost sales. These false positives—legitimate transactions incorrectly flagged as fraudulent—create friction that impacts both revenue and customer trust. If you don't include these transaction attempts in your approval rate calculation, you’ll never know there’s an opportunity to recover them!
A/B Testing Solutions
To identify whether overly strict rules are impacting your revenue, experimentation is key. One effective approach is to run an A/B test:
Identify a subset of transactions that would typically be blocked by your fraud rules for example, those made with prepaid cards.
Adjust your rules through one processor to allow those transactions to proceed through the authorization process.
Monitor the approval rate and chargeback rate of those transactions across a specific time period (e.g. 2 months), and compare against the rates of transactions typically considered safe.
Identify the decline code breakdown of any of those transactions that did fail to determine if the processor still rejected them as potential fraud.
Perhaps you let more transactions through, but the majority of them failed; in that instance, more restrictive rules may be protecting your business from the added cost of processing declines and fighting chargebacks. Alternatively, if approval rates increase (or simply stay the same) while attempted transaction counts soar, you may be on the right path to driving revenue growth purely by easing up a bit on your fraud fighting strategy.
The data-driven insight derived from such an analysis can help you refine your fraud prevention strategy. Ultimately, you must balance the need to block fraudulent transactions with the goal of maximizing legitimate ones.
Find the Right Balance for Your Business
Optimizing payments doesn’t mean seeing a 100% approval rate through each of your processors. Instead, it means striking the right balance between revenue growth, customer satisfaction, and risk management. Achieving this balance requires more than just raw, context-less approval rate values; you need complete oversight into your comprehensive payments data.
Through our payments data aggregation and visualization platform, Pagos Insights, you get a unified view of your entire payments ecosystem. We standardize and harmonize data from all your processors, making it easy to compare performance across payment methods, customer segments, regions, and more. Monitor and analyze every stage of your payments funnel, so you know exactly where improvement opportunities exist. You can even go one step further and enrich your data with metadata to measure the impact of your A/B tests or even marketing campaigns.
Pagos doesn’t just show you the numbers—we help you understand them. With our meticulously crafted data visualizations, you can experiment with confidence and turn insights into action. Optimize your payments strategy and drive business success with Pagos! Contact us today to get started.