Ecommerce businesses do everything in their power to acquire customers. Along the way, most use sophisticated targeting and optimization tools to find those consumers who will be the most valuable. Yet once those customers have been acquired, few companies employ tools of any sophistication to keep them there. As a result customer attrition, aka “churn,” is an enormously costly, and largely unnecessary problem.
Los Angeles startup Retention Science is hoping to solve this problem using big data. After launching into public beta in July 2012 with $1.3 million in backing, the company has worked to further analyze the customer data of its etailer partners and draw insights to refine its product.
Today, the company is releasing a major product update that focuses around a new summary metric: the “Retention Score.” Similar to a Klout score for ecommerce merchants, the Retention Score give an at-a-glance measurement of customer retention effectiveness and churn probability. With each score comes customized, actionable recommendations for maximizing customer lifetime value.
“The whole point is so marketing managers don’t have to think too hard about what steps to take next,” co-founder and CEO Jerry Jao says. “As a Retention Automation Platform, we let our algorithms tell businesses exactly what to do with their customers, instead of just telling them information about their customers.”
Retention Score is available as an ecommerce platform extension (Magento only, currently). The software analyzes four key metrics: customer churn, customer engagement, customer sentiment, and repeat purchase rate. The output is both a single representative score, the Retention Score, calculated relative to industry and category peers, and granular analysis of each above individual metric.
“Retention Score is computed from various metrics that measure customer retention throughout the entire lifecycle of the shopper,” Retention Science data scientist Dan Feldman says. “We simplify a lot of complex calculations and predictions into one simple score, which provides concrete means for businesses to monitor and improve their retention health.”
Recommendations take the form of targeted email, SMS, and push notification campaigns aimed at re-engaging fatigued customers. The system combines signals including demographic, social, and behavioral data, real-time Web viewing patterns, and purchase history, to dynamically create relevant and timely offers for each individual customer. For some, it may be 10 percent off their next purchase. For others it may be $20 off a purchase of $200 or more, depending on their individual preferences as determined by the software. The platform even optimizes the time of day to send the retention offers based on each user’s historical Web browsing and email opening activity.
The ineffectiveness of current customer retention efforts across the industry makes little sense, given that current customers spend 33 percent more on average than new ones, according to the company. Further, customer retention typically costs significantly less than acquisition.
For industry leading companies like Amazon, Zappos, JustFab, Gilt, and the like, repeat business is essential to success. Amazon’s $79 per year Prime membership, and JustFab’s refusal to move away from subscriptions despite the surprising decision by its largest competitor to do so, are indications of this value.
Some technology-savvy etailers have in-house data science teams and handle their own customer retention efforts, but most large brands do not. Retention Science already has several paying customers, and is in conversations with the vast majority of ecommerce companies that you’ve ever heard of.
While pricing is not advertised publicly, Retention Science operates on an annual, volume-based SaaS licensing model, under which the largest customers will likely pay six figure sums – and earn exponentially more through increased sales and reduced customer acquisition costs, if all goes according to plan.
Jao and co-founder Andrew Waage launched Retention Science as a pivot of a previous startup – a cash flow positive, but overall uninspiring social media rewards platform – and joined Santa Monica’s MuckerLab accelerator with the new idea in early 2012. The company has since grown to nearly a dozen employees, primarily data scientists.
The Retention Science team has built a compelling product. The biggest challenge ahead for the engineer-heavy team is likely that of selling its solution to customers. Jao is taking his time building early market adoption before hiring dedicated sales force. But it’s likely this step that will prove (or disprove) the long term sustainability of the company. Until then, the company is targeting slow and steady growth, and watching its burn rate closely.
Unlike other more nebulous marketing and customer analytics tools, Retention Score is the kind of technology that, if effective, can deliver a quantifiable return on investment to its customers. As the company gets its product into the hands of more and more merchants, and thus gets access to their consumer data, it should be able to further refine its algorithms and improve the overall effectiveness of the product.
The ecommerce category has been growing increasingly competitive and hostile. Only the very best, and most metrics driven operators can survive. Customer retention may be a historically overlooked science, but with the launch of Retention Score it doesn’t need to be.