Improve Transaction Success Rates and Reduce Churn With Recurly’s Revenue Optimization Engine

Recurly-Revenue-Optimizaton-Engine-Blog.pngEvery subscription business encounters credit card declines. These declines increase churn, reduce your revenue, and can negatively impact your subscriber relationships. But, with the right subscription management platform, you can minimize their impact.

Recurly has the advantage of working with thousands of subscription businesses which come from a wide range of industries. Many of these are ‘high-velocity’ businesses with large subscriber bases generating high transaction volumes annually. This gives us access to hundreds of millions of data points that encompass billions of attributes from many different types of companies in both B2B and B2C categories.

All of this data is an incredible resource. Add to this wealth of data Recurly’s expertise in recurring payments and our culture of learning, iteration and innovation, and you get something truly unique and powerful: the new Recurly Revenue Optimization Engine. The Revenue Optimization Engine takes a highly tailored approach to each invoice, using statistical models and machine learning to improve collections -- increasing our customers’ monthly revenue by an average of 9%.

Credit cards and recurring transactions

Credit and debit cards are the most common method of payment in the U.S., used in a wide variety of transactions. In subscription commerce, these transactions are recurring transactions where the card is charged anew each billing cycle. Recurly has found that on average, 13% of recurring transactions are declined.

Recurring transactions may be declined for a number of reasons including insufficient funds, credit/debit card restrictions, technical issues, or other reasons beyond the subscriber’s control. These declined transactions can lead to involuntary churn. When this happens, subscription businesses lose the customers they worked so hard to acquire.

How it works

Every declined transaction is different, which makes a static, one-size-fits-all retry schedule less effective. Recurly’s Revenue Optimization Engine uses the power of machine learning to craft a more intelligent retry schedule that is specifically tailored to each individual declined transaction.  

Using this technology, subscription businesses recover an average of 61% of failed subscription renewals. This increased payment success rate increases revenue and decreases involuntary subscriber churn that results from failed transactions.

By creating and utilizing a tailored retry schedule, Recurly helps resolve more credit and debit card payment issues in a shorter timeframe than a static schedule can. This means that the business gains access to cash sooner. And because subscription businesses rely on recurring revenue, improvements made each billing cycle have a compounding effect over time on subscriber retention and total recurring revenue.

Subscriber benefits

When transactions are successful, subscribers benefit from having uninterrupted access to your product or service. You don’t have to suspend their account while payment issues are resolved.

And, subscribers receive fewer communications regarding payment issues, such as asking them to update their billing information. Instead, businesses can send email that is more focused on improvements to their subscription service and the value customers gain from subscribing.

Continued innovation to maximize your revenue

Recurly continually works to add new, innovative capabilities to our platform to help our customers maximize their revenue. We’re proud to announce our new Revenue Optimization Engine, which is available in our Professional and Enterprise plans.

We believe that subscription billing can and should be a competitive advantage—and for our customers it is, because of our expertise in subscription commerce and our dedication to our customers’ success.

 

New Call-to-action

Ready to Get Started?

Request a Demo

We use cookies for analytics and to improve our site. You agree to our use of cookies by closing this message box or continuing to use our site.
To find out more, including how to change your settings, see our Cookie Policy.