The Data

In general, payment processing fees can be broken down into three distinct cost categories:

• Interchange — Fees associated with the issuing banks (learn more in our Interchange guide)
• Assessments — Fees from the card brands (also known as card networks)
• Processor — Fees from the gateway or payment service provider (PSP)

Each fee category is influenced by several factors, including what card product a customer uses for their transaction, how you process it (e.g. with or without a postal code), where you as a business are located, and how your processor fees are constructed. Fee subcategories dig into this next level of detail for each of the categories. Under the Assessments category, for example, the subcategories include processing, cross-border, brand, and chargeback fees, along with usage fees for data integrity, authorization retries, and services like account updater.

In this use case, we'll explore how you can use a combination of Assessment fee subcategories and data set comparisons to baseline the costs associated with transaction retries. This is an important assessment for any business to conduct, as your transaction retry strategy can significantly impact your overall payment processing costs.

Exploring the Data in Peacock

Using the Fees Dashboard in Peacock, you can not only view all assessment fees aggregated across each of your payment processors, but you can even dig into the distribution of these fees by subcategory. By doing so, you can start to tease out any specific assessment fees that you might be able to address with changes in your payment strategy. For example, if you notice in the Fees Subcategory Costs chart that your business faces a large amount of never_approve_reattempt_fee subcategory fees, you might be improperly retrying transactions that card brands prohibited you from retrying based on the assigned issuer decline code.

Typically, the processing fees and chargeback fees subcategories make up the biggest share of fees, but this doesn't mean other fees aren't worth exploring. Even a fee that only accounts for a small percentage of your overall fee volume could be costing you thousands of dollars.

Drawing Conclusions

Let’s assume that you are a merchant who has the ability to retry declined transactions, but you haven’t adjusted your logic for the new card brand rules around retries. By not complying with the new rules, your business will likely incur fees alongside your retries. To evaluate where you are today and decide on a cost-efficient retry strategy, you need to analyze your fee data. The two pieces of information you need to assess with regards to these fees are:

• The specific details of where you’re being charged fees
• The distribution of decline codes over time for the failed transactions you’re retrying

For the first piece of information, you look at the Fees Subcategory Costs chart in the Fees Dashboard where you see that 1% of your assessment fees last month were in the never_approve_reattempt_fee subcategory. Coming in at over $46,000, this is a pretty big cost! To explore this subcategory further and view it independent of all other fees, you click on it in the chart's legend.

You can clearly see that the amount your business spent on these retry-specific fees increased by nearly 50% in the last month. But why?

The next step here is to dig into the second bullet above: decline code distributions. Specifically, you navigate to the Decline Code Transactions chart in the Declines Dashboard to view the distribution of decline codes that are prohibited from retries. Based on card brand rules, you know one of the main prohibited retry decline codes is decline_stop_all_recurring; you start by looking at the number of transactions in the last couple months that were declined with this specific decline code.

The marked increase from March to April of decline_stop_all_recurring declines clearly matches that of fees in the never_approve_reattempt_fee subcategory. It appears your business is retrying decline_stop_all_recurring declines—against the rules set by card brands—and you’re being charged fees for those retries!

This is just one example of how you can use cost data in Peacock to identify areas of your payment processing strategy that are directly hurting your profitability. If you’ve successfully identified an issue in your fee data using Peacock, please share your use case with us!