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The Butter Team

April 10, 2024

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Payment Insights

The ripple effect of Transaction Authorization Rates on profitability

The Butter Team

April 10, 2024

Your customers deserve Butter

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Payments are a vital process for any subscription business. A seamless payment process ensures income with which to operate, thrive, and grow. But once that flow is disrupted, companies can easily find themselves at tremendous risk.

Transaction Authorization Rate (TAR) is a critical metric that could be the culprit behind your stunted revenue growth. From error codes to fraud claims, building a trusted reputation throughout your payment network takes effort. A higher TAR can help you identify areas of opportunity when it comes to your failed payment recovery strategy (i.e., chargebacks and decline codes) and is an indicator of a clean MID (Merchant ID number, used to process payments)—key to a payments strategy that maximizes profits.

If you’re a subscription business looking to increase recurring revenue, keep reading to uncover the compounding impacts of transaction authorization rates on subscriber churn, lost revenue, and declining profits.  

What is Transaction Authorization Rate?

TAR, also known as payment acceptance rate, is the rate of successful transactions compared to the number you attempt, including retry attempts for failed payments. The formula divides the number of approved transactions by the total number of attempted transactions (both approved and declined) and then multiplies the result by 100 to get a percentage. 

For example, if you have 135 approved transactions out of 150 total attempted transactions, your TAR is 90%. What’s a good benchmark? Payment acceptance rates of 90-95% are best in class, indicating a seamless checkout flow and renewal processes for your subscription payments, and that clean MID mentioned before. Why does this matter? 

Why TAR matters to subscription-based companies

For subscription-based companies, payment failures threaten revenue—and reputation. If you’re working with a PSP for example who consistently flags card-not-present decline codes, that PSP is costing you your subscribers and your profits (i.e. chargeback fees). A high authorization rate rewards "good actors,” top of funnel customer payments will have a higher success rate because your TAR and MID have signaled to PSPs, banks, and card networks that transactions initiated by your merchant ID are trustworthy. Think of TAR as a way to "prime the pump” - the increase in accepted payments creates a snowball effect .  Payments you process overall become less prone to fraud flags, chargebacks, and disputes. A high TAR is one of the core indicators to overall positive payment health, critical for maximizing profits. 

Three strategies for improving TAR

Like trust, TAR is challenging to build up; it takes time and proper analysis to stop payment failure and prevent future payments from being questioned. Laying the foundation to improve low authorization rates requires tactics that address the critical problems of failed payments.

1. Optimize your retry timing

  • Fixed schedules for payment recovery may seem convenient, but in the dynamic landscape of digital transactions, they are more like a “one-size-fits-none” solution.
  • Payment failures demand a more dynamic approach to understanding the reasons why they were rejected. Without this knowledge, fixed retries can often lead to more attempts on payments that are likely fraudulent or nearly impossible to recover.
  • By tailoring retry schedules to the quality of each payment attempt, Butter offers a dynamic approach that avoids excessive retries. This means that payments with a higher likelihood of success receive more attention and retries, while less likely transactions are spared from unnecessary attempts - leading to improved TAR.

2. Track and analyze failed payments

  • Every failure is different — some might be rejected for incorrect card information while others might be flagged for possible fraud. You can't know why a payment was rejected without looking at the precise data included in every failure. Analyzing this data does more than identify error codes; it helps spot patterns that can refine your payment processes.
  • Butter’s machine-learning model considers up to 128 elements of transaction data. With a well-built checkout process, merchants can gather payment data to help Machine Learning (ML) models better understand their failed payments. An all-encompassing approach makes it easier to go beyond error codes to understand and avoid the root causes of payment problems.

3. Create an efficient payment recovery process

  • Every effort counts when maintaining a streamlined operation. Creating an efficient payment recovery process ensures that your retries are helping your business, not continuing to hurt it. Each retry needs to contribute to restoring a robust TAR, not set you back further.
  • Recovering payments in fewer attempts requires an approach dedicated to the details of every transaction. Brute force tactics, such as repeated or indiscriminate retries, are often ineffective and can even exacerbate the problem. A precise, data-driven strategy analyzes the specifics of failed payments to identify patterns and tailor recovery efforts accordingly. It prioritizes attempts' quality over quantity, ensuring that actionable insights inform each retry.

Developing this data-driven strategy requires meticulous payment data analysis — including error codes, transaction histories, and customer behaviors. However, these can lack depth and efficiency without the right analytics or machine learning tools.

Butter’s solution goes beyond the basics, differentiating between the traits that define recoverable and non-recoverable payments. These nuances demand a holistic approach to analyze what factors influence unsuccessful transactions quickly.

Butter is your path to increased revenue and financial performance

Butter’s platform is built on industry-leading machine learning, developed by subscription payment experts. More than a manual setting or resetting of retry dates and times, our models recover payments by learning from your unique payment history and dunning processes to inform retry schedules that drive subscriber retention and deliver top and bottom line revenue.

If you’re looking for ways to shatter your subscriber and revenue retention goals, and improve authorization rates in the process, book your consult. Or get started with a free payment health analysis - identify exactly why you’re losing revenue within your payments processes, how to optimize, and how much revenue you could be recovering. Request your analysis here.

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