Retrying Failures: Finding the ROI Sweet Spot

When you run a subscription business, you’re bound to experience payment failures. What you do after each failure, however, determines whether that lost payment is the end of the line. Because here’s the thing: while failed payments are inevitable, lost revenue doesn't have to be.

Retries have a clear potential upside: recovered revenue and retained customers. Every successful retry represents more than just a single flipped transaction; data collected across a wide range of subscription merchants shows a recovered subscriber sticks around for an average of seven additional pay cycles. That’s a strong incentive for chasing down those failed transactions.

But retries come with costs: processing fees, network penalties, and the long-term risk of damaging your approval rates or even your processor relationship. If you retry too little, you leave money on the table. If you retry too aggressively, you could cost yourself even more.

Our goal is to find the sweet spot: the optimal number of retry attempts that maximizes recovery without tipping the balance.

Step 1: Gather and Clean Your Data

Before you can assess your retry strategy, you need to track your transaction retries and identify a baseline for both expected success and associated costs. One way to do this is by tagging retry attempts with metadata—custom labels added to transactions for the purpose of segmenting data into identifiable groups. Some processors will do this for you, but more often it’s on you to design a metadata strategy for tagging retries.

With Pagos Insights, you can harmonize all your payments data from each of your processors together into a single dataset for analysis via our no-code data connections. Using identifiers like customer ID, subscription ID, and your custom metadata, you can track a single subscription across all retry attempts and even segment metrics like approval and decline rates by each retry attempt. With data export capabilities, you can also download this clean data for external analysis.

Step 2: Measure Success Rates Per Attempt

Next, calculate how effective each retry is by plotting the success rate for each retry attempt. For example, say your strategy involves retrying a failure every day with a maximum of 15 retries. The first retry may succeed 30% of the time; of the remaining failed transactions, only 15% succeed on the second retry. Continuing on, you can chart both the success per retry and the cumulative retry success rate. You’ll quickly see where returns start to diminish.:

Step 3: Assign Costs

Each retry has a cost, typically $0.05 to $0.15 per attempt. While small at a micro level, these costs can add up over thousands of failed attempts. Past a certain point, those costs inevitably outweigh the potential revenue recovered from additional retries. 

You also need to consider the penalty fees you’ll incur on top of these base retry costs, both because they can get out of hand fast and excessive retries hurt your approval rates long-term. Visa and Mastercard have strict rules to prevent merchants from endlessly retrying declined card-not-present transactions. Understanding these penalties is crucial to avoiding them. For example:

• Visa

  • Allows up to 15 retry attempts in 30 days for the same transaction (same card and amount); every attempt past that incurs approximately $0.10 in penalties per retry domestically and $0.15 per retry cross-border

  • Forbids retries of Do Not Retry hard declines (e.g. stolen card, closed account, invalid number); each retry attempt triggers a fee (~$0.10–$0.15 per attempt) and can harm your standing with Visa

• Mastercard: 

  • Caps retries at 10 in 24 hours, and 35 in 30 days; after that, each extra attempt can cost around $0.30 in the US or €0.50 in Europe

  • Enforces penalties for retrying against Do Not Retry decline codes

Step 4: Calculate Expected ROI

For each retry attempt, multiply the success rate by the average transaction value and subtract the cost of the attempt. Stop retrying a failure when the expected costs outweigh the potential benefits. To be safe, you might stop retrying one attempt before that to account for margin, or maybe the small, incremental return is worth the operational complexity from your perspective! At this stage, how you decide to act based on the data comes down to business judgments. The math informs you, but your unique business sense and customer relationships drive the decision.

Step 5: Segment Your Strategy

So far, we’ve walked you through a calculation pretending every declined transaction is equal, but that’s clearly not the case. You’ll need to repeat this ROI calculation for each individual segment of your payments volume. Example segments include:

• Decline type: Expected retry success differs for soft, hard, and technical declines. For example, many soft declines (e.g. insufficient_funds or do_not_honor) have high success rates, while some hard declines won’t ever succeed and could trigger penalty fees.

• Payment method: The type of card a customer uses (e.g. credit, debit, or prepaid) often correlates with potential retry success. Prepaid cards typically aren’t worth the effort because customers may never reload them, while debit cards have higher retry success rates after payday

• Customer tenure: Loyal customers might be worth more effort to retain than new customers who just signed up last month

Finding a good retry strategy for each segment starts with understanding your payments data in general. Pagos Insights can help you do just that.

Step 6: Monitor and Adjust

At this point, you’ve calculated your retry ROI and designed a retry strategy for each segment of your business. Moving forward, you need to track how that strategy plays out. Key data points to monitor include (but aren’t limited to) the following:

• Retry success rate - Out of all your payments that failed initially, determine how many were actually approved via retry.

• Deduped approval rate vs. raw approval rate - Retry deduplication removes duplicate failed retries from your approval calculations. A large gap between these rates means retries are doing the heavy lifting.

• Average number of retry attempts for all transactions and average number of retry attempts for successfully recovered transactions - If these numbers differ by a lot, this means you might be retrying too many times past the optimal number of attempts, and the incremental benefits of additional retries have long past.

• Net ROI (revenue recovered − total retry costs) - This is perhaps the most vital metric, as it confirms if the strategy you designed is working.

Use this data to fine-tune your retry window and segment-specific strategies. You can even set KPIs and re-evaluate your overall retry strategy quarterly. 

Prevent, Don’t Just Recover

One final thought before we wrap up: some of the most effective strategies happen before a transaction fails. To prevent involuntary churn caused by outdated card details in your vault, consider implementing an account updater or network tokenization strategy. Pagos’ global Account Updater tools keep stored card credentials up to date via direct connections to the four major card brands. Meanwhile, our Network Tokenization API replaces all customer PANs with secure network tokens that remain consistent even when the underlying card details change over time.

You should also explore opportunities to improve customer communications. An email or push notification letting the customer know their payment has failed and prompting them to update payment details or retry the transaction manually can go a long way. With better communication, you can help customers help themselves (and you)!

Lastly, check out our previous blog post on designing a BIN-based routing strategy. With optimized routing, you can increase approval rates across the board with minimal effort!

Final Takeaway

A smart retry strategy recovers revenue, protects your bottom line, and keeps more customers on subscription. Getting there requires effort and access to clean payments data. With Pagos on your side, you’ll have the harmonized data, visualizations, and segmenting capabilities necessary to turn a blunt-force retry approach into a fine-tuned engine for retention. Whether you're tagging retries with metadata, calculating ROI, or assessing costs over time, our tools help you make decisions rooted in data.

The bottom line: Don’t just retry. Retry smarter.