While customer retention marketing sometimes takes a backseat to customer acquisition at many companies, retaining customers often costs significantly less than attracting new ones, and typically constitutes an area of untapped potential for many brands. That's where Retention Science, in Santa Monica, CA., comes in.
"Retention Science takes the guesswork out of retention marketing," CEO and cofounder Jerry Jao says. The company's mission, Jao explains, is to help companies maximize customer lifetime value and retention through predictive technology. "We employ the most sophisticated learning algorithms and statistical models to predict customer behaviors and optimize retention marketing campaigns at the individual level. That means less guesswork and better results for our clients," he says.
When BikeBerry, an online bicycle and bicycle accessory retailer, wanted to rethink and restructure its approach to email marketing geared toward existing clients, it turned to Retention Science. BikeBerry's main issue, owner Jack Lin explains, was that the company was losing too much money by giving discounts and coupons to customers who were willing to make purchases without them.
"We were getting tired of a one-discount-fits-all approach to email marketing," Lin says. "We wanted to maximize existing customer spending and avoid giving away offers to customers who would convert without needing additional incentives."
To address Lin's concerns, Retention Science used its customer profiling engine to automatically create tailored retention campaigns for every BikeBerry customer.
"Each customer is different, so it makes sense that a retailer should market to each individual differently," he adds. "We don't just make that possible for businesses, we make it easy and automatic, so merchants won't have to spend too much time on data analysis."
The company aggregates and analyzes numerous data points, including browsing patterns, purchase history, demographic information, behavioral data, and more in order to make the most optimal and relevant recommendations.
Once information about BikeBerry's clients was gathered, Retention Science's algorithms and tools determined which customers were likely to buy without monetary incentives and which relied on them, and targeted their retention marketing campaigns accordingly.
"Our retention marketing campaigns launch with the click of a button, and our customer profiling engine can deploy campaigns through multiple delivery channels, such as email, which worked well for BikeBerry," Jao explains.
With a more targeted email marketing campaign, BikeBerry saw an improvement almost immediately. According to Lin, the company's email campaigns saw an increase of 133 percent in sales and of 200 percent in user activity. "BikeBerry also undoubtedly saw cost savings in not giving too big of a discount to customers who converted at a lower offer threshold," Jao adds.
"With Retention Science, we're turning roughly thirty percent of our one-time customers into repeat buyers—customers that continue to purchase items from our Web site again and again," Lin says. "They help us determine when and who to send specific offers and product recommendations to, which helps us optimize margins and increase existing customer spending."
Retention Science was named a Top 10 Software Company in Southern California by SocalTech and an "Innovation Agent" by Fast Company. The company, which is working on several new algorithmic and software developments, is growing and hoping to make a name for itself. "We're excited to make big things happen in e-commerce," Jao says.
By tapping Retention Science to help it restructure its email marketing programs, BikeBerry was able to achieve:
- a 133 percent increase in sales;
- a 200 percent increase in user activity; and
- 30 percent of one-time buyers returning to shop again.