Amazon.com pioneered the you-bought-this, you-might-like-that and the people-who-bought-X-also-bought-Y online sales approach. Now the key people behind Amazon’s technology, who founded software-as-a-service personalization engine RichRelevance five years ago, are driving more than a billion product recommendations each and every day for six of the top ten U.S online retailers.
“We’re driving multiple billions in value on an annual basis,” RichRelevance CEO David Selinger told me on the phone yesterday between flights. “Generally we provide a 3-15 percent increase in revenue for our customers, and one recent client — a top-five internet retailer property, saw over 11 percent revenue lift.”
Selinger, who led Amazon’s product personalization engine team, calls RichRelevance’s secret sauce “ensemble learning.” It’s a machine learning engine that observes what people buy over time, as well as what they shop, but don’t buy. By seeing trends both within individual shopper’s buying experiences and across multiple shoppers, RichRelevance makes smart recommendations that are likely to appeal to buyers, thereby boosting its clients’ revenue. Other companies in the space include companies like PredictiveIntent and Barilliance,
A billion product recommendations a day is a significant milestone, and with 73 percent revenue growth and 43 percent customer growth in the past year to go with it, the company is hiring a new president to help increase growth.
“We started the year with about 150 people, and have already grown 20 percent in head count,” Selinger says. “We’re growing quickly, but the amount of opportunity in front of us is growing even quicker.”
Eduardo Sanchez, formerly EVP of Microstrategy, EVP of Lawson Software, and COO of Cartesis, was about to start his own data-based recommendation engine, but realized the space was growing too fast. So he decided to join them rather than beat them, according to Selinger.
Image credit: Shutterstock/Buying online
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