Can’t my team handle failed payment recovery in-house?

Payment failure is a bigger problem than you think, costing merchants an estimated $443 billion per year. In fact, 87% of organizations report losing customers because of failed payments. The reason is simple: when customers can’t make quick, easy payments they walk away.

With countless reasons why a payment may fail, most payment service providers (PSPs) don’t  help you fix the problem. Instead, they apply the same strategy to every failed payment even if a different approach is required - for example, a stolen card vs. insufficient funds. That kind of one-size-fits-all solution limits how much lost revenue you can recover.

A custom payment recovery strategy will boost your revenue, but building an in-house team to manage that strategy strains internal resources. For most merchants, a multi year, multi-million investment in failed payments isn’t practical. 

Butter’s team of experts can help you address the issues behind failed payments so you can recover more lost revenue — 166+%.

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Common challenges for in-house payment recovery

Most online merchants have a fairly simplistic approach to failed payments: retry as soon as possible on a repeating cadence. But this tactic doesn’t consider all the factors behind failures, limiting your chances for successful recovery. 

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Error codes don’t reveal all the reasons payments fail

The error codes returned by PSPs only give you part of the picture, and a one-size-fits-all retry strategy only addresses top-level failures, like “Do Not Honor” (common error 05 or 2000). For a higher chance of success, businesses need an optimized process that treats each payment differently.

But that demands a real-time view of failed payments and understanding all the factors that make each transaction unique. Not every organization has the capacity to manage data analysis on top of standard business processes, and payment service providers (PSPs) aren’t equipped to do it for you.

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Global regulations complicate payment recovery

Payment regulations also cause failures. Recently, the 3DS 2.0 upgrade aimed to make online transactions more secure with an extra verification step before completing a purchase. But during the rollout merchants encountered problems because some issuing banks hadn’t implemented the feature. That led to an increase in failed payments with no immediate fix.

Not only is the regulatory environment changing quickly, but there’s a sizable gap between what regulatory agencies say and what is happening to merchants. Staying up to date and managing these regulations can be a significant challenge for a small team.

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In-house payments solutions can cost millions

Even if you're determined to solve your payment problem, you're on the hook for hundreds of thousands or even millions of dollars. The costs to hire and onboard a full team to manage payment recoveries quickly add up. Let’s look at the roles you’ll need to fill. 

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Head of Payments ($150,000 - $200,000 annual salary)

The highest priority role to fill is the Head of Payments, someone with an expert-level understanding of failed payments. They are your organization’s point person for financial health. Given the ever-changing nature of failed payments, this position will likely be the most difficult to fill.

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Data Scientists ($125,000 to $175,000 annual salary)

Hiring a pair of data scientists is pivotal to understanding your payment data. Why not just one? Because this problem is often too complicated for a junior data scientist to solve. To find people who can develop an effective solution from the ground up, you need a blend of skill sets and experience, which can take years to find. 

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Data Analyst ($85,000 to $100,000 annual salary)

A data analyst uses payment data to translate findings to the company in layman’s terms. Their analysis helps executive teams identify trends and make adjustments to the recovery strategy.

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Data Engineers ($100,000 to $125,000 annual salary)

Data engineers ensure intelligent design, maintenance, and infrastructure optimization for data collection, management, transformation, and access.

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ML engineers ($200,000 to $250,000 annual salary)

You’ll also need machine learning (ML) engineers to build an efficient model for your business and to continue to expand your analysis and data collection. Because ML uses the data you feed it, staffing your team with a pair of qualified engineers ensures that your model uses good data to build your payment recovery strategy

With a team of 6-8 people, you’re looking at $1.35 million annually in salary alone:

But it’s not just salaries. Finding the right fit takes time, which means more money. It can take 6 months to fill specific positions, and then you still need to collect enough data to understand why payments are failing. That’s another 12-18 months, and you’re still losing 10-25% of your ARR to payment failures.

Most businesses can’t afford to invest millions of dollars and 18-24 months before seeing any meaningful impact.

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Existing in-house teams benefit from a targeted payment recovery strategy

If you’ve already built an in-house team to improve payment recovery, you’re ahead of the curve. But you improve your recovery rate even more if you can solve the optimization problems within your payment system.

Rather than getting into the weeds with retries, focus on:

• Implementing multi-PSP with backup processors to route failed payments elsewhere
• Investing in the checkout flow to understand why specific customers are unable to make a purchase
• Rolling out local payment methods for international transactions

Even with a dedicated team at your disposal, your investment is still limited, especially if you can’t dive deep enough into your payment data due to PSP limitations. So what’s the alternative? Payment recovery with Butter.

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Save time, resources, and mental bandwidth with Butter’s ML framework

At Butter, we not only address your current failure issues, but we can actually prevent future payment failures. Our machine learning models assess every data point — from soft error codes to industry-specific challenges and even your own transaction data — to design the most effective retry strategy for your business. 

Our data engineers, data scientists, and ML engineers look at hundreds of millions of transactions worldwide across different merchants, processors, and tech stacks. All that data builds more robust models that deliver better recovery performance – without investing the significant overhead in salary, onboarding, and in-house development.

Don’t waste resources trying to solve your failed payments problem. With Butter, you can improve payment health, nurture customer retention, and grow ARR by an average of more than 5%.

Curious to see how our team of 40+ delivers outsized performances for our customers? Contact us to get started with your free payment health assessment!