Decline Rate: It's Not a Number, It's a Customer (That You Lost)


Svante Westerberg

Product Marketing

September 8, 2022

September 8, 2022

September 8, 2022

This post was written in conjunction with Billy Chen—a Pagos angel investor and strategic fintech advisor—who offers his personal insight and experience in the payment industry.

Authorization rate (i.e. auth rate) is a metric that the payments industry has focused a lot of energy and messaging around over the last few years. While I believe there’s still a lot that businesses and other players across the payments ecosystem can learn from and act upon with regards to authorization rates, I suggest we also focus on auth rate’s darker flipside: decline rate. Decline rates can help businesses better contextualize their performance—both internally and with their payments service providers. 

Decline rate isn’t just a metric: it’s an explicit representation of ecommerce customers with failed (and thus, negative) experiences. Imagine a supermarket where 1-3 out of every 10 customers have to walk out leaving the shopping cart full of groceries behind at the cashier because their chosen payment method was declined. Sounds nuts, right? Yet this is considered "industry standard" for global digital commerce today. That’s right—decline rates for global ecommerce can range anywhere from ~5% to 30%, sometimes even higher for some combinations of business models and geographies.

A Better Way to Look at Decline Rates

To begin with, I think it’s critical to translate a decline rate percentage into what it really is. For example, each declined transaction could represent any of the following:

  • An existing customer you just lost 

  • A subscriber who's service now is interrupted 

  • A new potential customer who just went to your competitor

This seems obvious, but it’s rare to see decline rate directly translated into key business metrics. One approach to do just that is to tie your decline rate to your customer lifetime value (LTV). 

Here’s one way to create such a combined metric: (decline rate X number of orders) X average customer LTV 

I'll demonstrate how this works by calculating the decline rate/LTV metric for a subscription-based business model. Let's say the following is true for this business:

  • Each subscription costs $5/month

  • The average customer subscribes for 2 years (= $120 LTV)

  • The daily order count is 50,000

  • The decline rate is around 15%

Given these base metrics, the decline rate/LTV metric calculates out to around $900,000: (15% X 50,000) X $120 = $900,000

This would mean this subscription business is potentially losing $900,000 in customer LTV per day! On the bright side, it also means for every 1% they can reduce their decline rate, they can increase their gross customer LTV/year by $3.3 million (1% X $900,000 X 365 = $3.3M)!!

[Note: The use of “orders” instead of “transactions” in the calculations above is important. The order count represents the customer's direct action, whereas the transaction count includes multiple authorization retry attempts, which aren't done by the customer's volition.]

This metric model is a bit oversimplified, as the business in question could take action in the moment to decrease their overall decline rate by prompting the customer to provide a different method of payment to replace the declined one. There are also certain declined transactions that can be re-tried or potentially successfully re-routed to a secondary payment service provider (PSP) or acquiring bank. That being said, I’ve found most businesses don't even know their exact decline rate and—much less—which declined transactions to act on and what kind of action has the highest potential for success.  

What is the Commerce Data Gap and How Do You Bridge It?

I had to learn a lot of what I know on this topic the hard way in previous roles running payments for global digital commerce businesses at massive scale and growth pace. It was fascinating to see the amount of detailed data available on all aspects of the customer lifecycle except for what is arguably one of the most critical points of the interaction, both with a potential customer and an existing one: the payment. I call this the commerce data gap. 

A lot of businesses feel like decline rates are something outside of their control, which is only partly true. Yes, you do ultimately depend on an issuing bank and payments scheme to either approve or decline your transaction, but you can definitely increase your chances for success by having better intelligence both on how to best send a transaction for processing and what comes back in the response. The key challenge in my experience has been to easily access and turn payments data (whether from one or many payment service providers) into actionable insights.

This leads me to my role as an early investor in Pagos, which was very much motivated by my experiences and pain points running large global payments operations. I saw that by leveraging Pagos’ unique payments intelligence services, pretty much any digital commerce merchants can bridge their commerce data gap and decrease their decline rates—without needing to change their existing payments infrastructure. 

Democratizing Payments Optimization 

Decline rate is one of the metrics businesses usually just accept at face value, but one that could have a huge impact on both top and bottom lines. The way a business can gain more control of their own destiny is by having quick and easy access to payments intelligence that not only clearly shows you what your actual performance is (across all your PSPs), but also what different decline reason codes mean and what actions to take. If you also add detailed monitoring on this and other key payments metrics, you'll be able to catch a potential payments operations issue before it becomes a million dollar problem, as well as discover new opportunities for continuously decreasing your decline rate. With Pagos’ Payments Intelligence tools, all these benefits (and much more) are finally easily available for any size or type of business—something that historically wasn’t feasible even for the largest global merchants.   

The bottom line is that all players involved in processing digital commerce payments would benefit from lower decline rates—from your customer all the way to the issuing bank (or payment scheme), and every player in-between. If only my payments teams and I had had access to Pagos’ services 10 years ago…

Billy Chen is an angel investor and advisor, former VP at Finix, and Director of Payments at Uber.

To learn more about Pagos, head over to or explore the Pagos Product Documentation. For more on decline reason codes, check out this Pagos Blog.

If you want to share examples of challenges with your decline rates (we would love to keep the conversation going), please contact us:

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