Updated:
December 10, 2024
Take the guesswork out of when to rebill a customer after a declined transaction. Recovery by Sticky.io — a smart dunning solution — leverages AI to determine the optimal date and time to rebill.
A ubiquitous problem plagues subscription commerce: transaction declines. Say a customer signs up and pays $25 for a monthly subscription box on February 15. The transaction is approved, the customer receives the box a few days later, and all is well. Then on March 15, when it’s time to rebill the customer for the next box, the payment fails even though the customer’s payment information is unchanged from February.
Trying to charge the customer’s credit card again is the obvious move, but the provider incurs a fee for every rebill attempt. So subscription merchants should rebill when there’s the greatest possibility of transaction approval. But how can merchants pinpoint the ideal time to rebill a customer?
Rebilling each declined transaction manually may have a high success rate, but it’s too much work for any business that processes more than a few transactions each day. Creating broad rebill rules may get a decent chunk of transactions approved, but some customers will always slip through the cracks.
Smart dunning tools like Sticky.io's Recovery combines the best traits of manual and automated rebilling to provide custom, data-backed rebill strategies for each declined transaction — and it does so with less effort on your part. Subscription companies that want to thrive need tools like Recovery to reduce customer churn and protect monthly revenue.
Multiple factors affect whether a payment retry succeeds or fails, and Sticky.io's smart dunning software tracks each one.
The Sticky.io Team developed machine learning algorithms to predict the best time for a rebill attempt. These algorithms look at over 500 individual predictors of rebill success. For example, one algorithm reveals the probability of rebill success by day for every single transaction that’s declined in our platform. Another shows the best hour to retry a transaction.
We feed this data into numerous different models to uncover patterns in the data. The vast amount of information we process is far beyond what any individual or even dedicated team would be able to interpret over the same period. Our models can also examine all possible connections between various data points, including those that human methods of data analysis likely wouldn’t be able to isolate.
All of this happens behind the scenes to return the answer to the question: When will a rebill request have the best chance of getting approved?
Smart dunning tools like Recovery automatically attempt to rebill declined transactions at optimal times. These times are based on customers’ historical behavior and other factors — increasing the chance of a successful rebill.
Most dunning strategies go no further than retrying all transactions on the day that gets the most approvals overall. Some “complex” strategies may categorize transactions using one or two data points, then choose a day or time to rebill based on that. Recovery looks at every data point in context to build a strategy.
Considering all of the data is extremely beneficial because certain banks and geolocations have a higher probability of declining a transaction during specific times, like between midnight and 6 a.m. These factors are likely to get overlooked in traditional dunning. Individuals and dunning tools that aren’t driven by AI don’t have the bandwidth to consider these smaller details alongside other important information like payment method and decline code. Recovery can improve rebill rates simply by having the capacity (and capability) to take every data point into consideration.
This is why Recovery is up to 51% more successful on first recovery attempts than traditional dunning strategies.
Recovery has one more benefit: The payment recovery process becomes more successful over time because the system is constantly analyzing and optimizing new data. Machine learning tools like ours can run tests to learn what makes certain retries unsuccessful and react to what they find without needing any guidance from you.
Recovery isn’t just good for your business; it’s also good for your customers. At a high level, smart dunning software like Recovery help brands reduce involuntary churn.
With smart retries, merchants have a smaller chance of losing a customer because of...
Recovery also improves the following areas:
Payment failures inevitably lead to customer disappointment. Even when they’re not your fault, late or skipped transactions decrease customers’ brand satisfaction. It’s in your best interest to fix declined transactions quickly, so the subscription cadence is not interrupted.
Visa and Mastercard allow 15 attempts to process a charge within 30 days of the initial transaction. Exceeding these limits could break compliance regulations and jeopardize a merchant’s standing with the credit card company.
Recovery helps you get more approvals with fewer attempts. This means more transactions are approved overall, and transactions are successfully processed within fewer days of the original attempt. Consumers don’t get bothered by dunning emails or have to spend time thinking about subscription management. And you don’t have to worry about losing them because of one failed payment.
Recovery removes uncertainty from the rebilling process, helping you avoid fees and potential disruptions. Recovery can help you:
Recovery is a practice that pays for itself over and over again. Right away, merchants increase revenue by converting denied transactions into approvals. Over time, subscription continuity improves and, with it, customer satisfaction and retention. There’s a third benefit, too: The time and capital you save can be reinvested into your company.
Subscription businesses live or die on customer relationships. The more resources you can put toward maintaining your customers’ goodwill, the lower your churn rate will be.