rankingCoach is an online marketing solution for local small business owners like restaurants, plumbers, and hairdressers. Their all-in-one solution, rankingCoach 360, helps businesses maximize their online visibility so they can attract more customers in their local area. Localized in 14 languages and 32 countries worldwide, rankingCoach covers already 70% of the global market (countries using Google & social networks). The award-winning software solutions are also integrated with numerous well known webhosters and CMSs, as well as telecommunication and marketing companies.

After adopting a software-as-a-service (SaaS) subscription model in 2016, rankingCoach grew quickly, expanding to 20 new countries in just 12 months. They were an early adopter of Zuora Billing, which allowed them maximal flexibility in payment types, including international payments, and supported invoicing in as many different languages as they needed. Yet despite the expansion, they unexpectedly weren’t hitting their expected revenue numbers.

The reason? They weren’t receiving all of their customers’ payments.

“When you’re growing more than 50% per year, collections are usually the least of your concerns,” explains Daniel Wette, CEO and Co-Founder of rankingCoach. “But we serve small business owners who tend to have more issues with payments—credit cards over the limit, accounts with insufficient funds, things like that.”

rankingCoach was losing a significant portion of their credit card payments, resulting in a considerable amount of revenue leakage. To make matters worse, when a customer’s payment didn’t go through, their service was simply cancelled and the customer had to register a second time using a different payment method in order to continue with the service. Needless to say, this didn’t make for an optimal subscriber experience and increased passive churn. To tackle this problem, rankingCoach again looked to Zuora.

To increase their collection of outstanding invoices, rankingCoach implemented Zuora Collect. Zuora Collect uses automated machine learning algorithms to glean and analyze data on customer collections for important questions like: Is there a difference in success based on what time or day a payment is attempted? Does payment success time vary by region? How are the reasons for payment failure involved? Do the gateway and currency of a failed payment make an impact on timing?

Zuora Collect answered these questions without the need for rankingCoach to do a deep data dive. And, instead of having to set up their own retry logic for missed payments, Zuora Collect created optimal retry schedules for them that continually improved over time, saving the company a huge time investment.

“At first, we implemented rule-based retry schedules based on our years of learning. But when we compared these extensively researched retry strategies vs machine learning with Zuora, Zuora ended up winning,” says Wette. There was a friendly bet that Zuora’s machine learning couldn’t outperform rankingCoach’s retry rules based on years of testing. “And I’m happy we lost, because that meant more revenue for us!”

Using Zuora Collect, rankingCoach automatically gained a more effective retry process and saw their payment success rate increase an additional 18% in just two months.

But increased revenue wasn’t the only benefit. Their customers had fewer service interruptions. And in combination with Zuora WorkFlow, they added additional communication that made payments more transparent for the customer. Better communication has led to a better experience and improved customer relationships.

With their collection system in place, rankingCoach can focus their resources on other initiatives, like new product offerings. They recently rolled out a freemium model in the US and the rest of Americas.