In 2020, “growth-at-all-costs” was the mantra. Stimulus checks and a tech boom combined to form a whirlwind of unprecedented valuations with subscription and ecommerce businesses at its center. Subscribing wasn’t just for streaming or your phone plan anymore; you could subscribe to clothes, coffee, and even dinner.

Fast forward five years, and the conversation has shifted. Today, many subscription businesses care less about sign-ups and more about stability. In fact, 86% of subscription industry leaders now rank retaining existing customers as more important than acquiring new ones.¹

At the heart of retention? Payments. More specifically: what happens when a payment fails.

The Retry Dilemma

For subscription merchants, one month’s bill holds the key to a customer’s lifetime value. But those payments have an even harder time getting approved than regular ‘customer-initiated’ transactions when between each billing cycle:

• Cards expire
• Balances run low
• Customers forget to update their details

That’s why retention strategies often include retries – attempts to process a failed payment again. If a merchant is focused only on revenue maximization, in theory any non-zero chance of approval means they’ll retry indefinitely.

And that’s what creates the dilemma. Flooding issuers with bad retries doesn’t just waste money on fees; it can erode trust and make it harder to get legitimate future transactions approved if MID (Merchant ID) credit scores decline.

So the question becomes: how do you avoid a downward spiral?

Understanding Declines: The Data Maze

The CMSPI Platform ingests trillions of data points across merchants, providers, and geographies. We know merchants often have access to a patchwork of data when asking why a payment failed:

• Acquirer decline reason codes — signals that can be passed through a chain of remapping steps before reaching the merchant
• Network decline reason codes which may be consolidated into categories that combine multiple criteria²
• Merchant Advice Codes (Mastercard) or Recurring Payment Cancellation Codes (Visa) which contain suggestions about whether and when a retry makes sense³

Discrepancies come about because each party a payment passes through has its own way of interpreting and classifying declines. Here’s what that mapping process can look like.

For one merchant, we saw this process result in generic ‘Do Not Honor’ declines making up 50% of their acquirer response codes.

The challenge for merchants is firstly knowing what data to request. Once that’s covered, it’s time to stitch the signals into something actionable.

Identifying Bad Traffic

1 – Transaction Level

Firstly, we need to isolate the relevant population. Treating each decline as a single observation won’t work because probabilities shift with first, second, and 20th tries. For one merchant, we saw ‘insufficient fund’ declines were 10% higher for second-attempt transactions.

That’s why any good decline analysis starts with deduplicating transactions to identify patterns at a payment level.

2 – Product Level

Next, we look for product patterns. Decline codes alone are often not enough to know why certain transactions are ‘low quality’, and we need to start connecting other information from our data lake to work out which payments are worth retrying:

• A gift card or prepaid card tied to a subscription? It will almost certainly fail again, and unnecessarily inflate costs.
• A one-time-use virtual card? Retrying it just pollutes your traffic, and may even be evidence of subscription abuse.

Merchants who can identify these patterns early — often through BIN data (Bank Identification Numbers) — can cut retries that were doomed from the start.

3 – Merchant Level

Now we’ve isolated ‘bad traffic’, we can design strategies unique to the merchant’s user flows. Some recent fixes include:

• Prompting for a fallback payment method
• Working with issuer call centers
• Enforcing stricter upfront rules on which cards are accepted

These remove redundant retries and user flows – helping to reduce issuer risk perception while maximizing profitability.

Phase 2: Incremental Gains

Once retries are “clean,” merchants can get more sophisticated.

They can start looking for incremental revenue opportunities in their subscription payments, including strategies like:

• Retry timing: Trying again at different hours or days of the week, especially across customer time zones.
• Cadence by decline type: Adjusting how many times and how quickly to retry based on the reason code.
• BIN-based strategy: Treating cards from different issuers and card products differently, depending on approval rate trends.
• Introducing third parties: Conducting tender processes for services that address a merchant’s specific use case.

The key is that these strategies only work when there’s already a strong baseline of issuer trust. Without that, you risk burning goodwill no matter how clever the retry pattern is.

The Case for Continuous Tuning

Retries aren’t “set and forget.” Economic shifts, changing network rules, or even an issuer updating their fraud models can quickly make last month’s winning strategy obsolete.

That’s why the most resilient subscription businesses treat retry optimization as an ongoing process:

• audit decline traffic regularly,
• adjust retry logic dynamically,
• and measure success not just by recovery, but by long-term issuer trust.

Takeaway

In 2020, subscriptions grew because of aggressive acquisition. In 2025, they survive because of smart retention. Retrying payments is one of the most powerful levers merchants have — but only if done selectively, with clean traffic and issuer trust in mind.

With the right data, merchants can continually assess their decline estate and avoid applying the perfect strategy to an imperfect relationship.

Looking to establish an optimal retry strategy? Connect with our digital experts today.