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Concept: Most e-commerce retailers are familiar with the science of product recommendations. richrelevance has created an addition to its SaaS platform called myrecs, which uses more data to recommend more products per page, and updates customer information to recommend those products in real time.

The Team: Two main players drive the company and make it a force to contend with. David Selinger (CEO & Founder) designed and developed the recommendations engine at Amazon.com. He is a pioneer in the field of e-commerce data analytics and personalization and takes credit for one of Amazon’s great leaps forward when it used personalization to increase annual profit by over $50 million (25% of US profit, 2003). After that he oversaw Overstock’s personalization efforts as Vice President of Software Development and Data Mining.

Darren Vengroff (Chief Scientist) is also an ex-Amazonian and a former VP at Goldman Sachs.  The company recently hired Tyler Hoffman as VP sales. He will be responsible for opening new accounts, which he most recently did for PayPal.

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Market Relevance:  Personalized recommendations have been a “secret sauce” for Amazon, and never quite duplicated by other ecommerce players. richrelevance is run by the guys who made that sauce. Selinger promises that this application is better because it is in real time and works on the cloud computing concept. He claims it will increase customer retention, increase conversion, and increase revenue. “We have pushed the limits of what is possible for this concept,” he says.

Delivery: Besides the SaaS platform from which it can be accessed and delivered, RichRecs, according to Selinger, has other advantages. Because the recommendations are updated in real-time it is more intuitive. Example: After Bruce Springsteen played the Super Bowl, consumers were interested in his back catalog as well as his new album. After the event, however, interest in his back catalog faded. The richrecs application was able to sense that interest via search and other activity, serve the back catalog recommendations and then stop serving them when the demand faded.

Purchase history affects the recommendations, but richrecs delivers a graded purchase history. Selinger says the Amazon engine may consider a purchase made three years ago in current recommendations. richrecs moves recommendations based on older purchases to the bottom of the recommendations page.

Proof Points: For Sears, myrecs has products an 80% increase in AOV and 5x increase in page views/sessions.

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