SimpleRelevance Won Brands+Startups™ 2014 Challenge

Posted by on September 22, 2014 at 12:23 pm

After five months and four grueling rounds of pitching our business based on specific brand pain points, SimpleRelevance is proud to claim victory of the Brands+Startups™2014 Challenge. Back in April, 31 startups presented their business concepts and marketing plans to a panel of Fortune 500 brand marketers and early-stage investors – the brand coaches. Each

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How does SimpleRelevance Work?

Posted by on September 16, 2014 at 10:45 am

By 2017, revenue generated through eCommerce sales is expected to reach $370 billion, yet many of the nation’s leading brands can’t leverage data to offer their customers the personalized digital marketing experience they are demanding. SimpleRelevance solves this problem. How does SimpleRelevance work? Our platform is the only modular, open predictive learning platform that enables

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Translating Data Science into Marketing Language

Posted by on September 5, 2014 at 1:07 pm

Recently, I was tasked with writing the content for a new technology white paper, and as someone with little to no technical background, it seemed like an insurmountable challenge at first. So I started at the very beginning, first gathering intel about our technology from our data scientists and developers, and then talking to our

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What Marketers Can Learn from the ‘Ice Bucket Challenge’

Posted by on August 19, 2014 at 11:24 am

Every marketer dreams of creating a viral video that skyrockets their company to the next level, makes customers fall in love with their brand and leaves a lasting memory. You could combine adorable kittens, people falling, sassy celebrities, and an epic parody and you’re still not guaranteed viral video success. Unfortunately there is no magic

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5 Tips for Picking a Personalization Platform

Posted by on August 8, 2014 at 1:38 pm

“Personalization” is one of the most recently overused buzz words in marketing. The word “personalization” has been so misused and overused by now that it has taken on a range of different meanings from segmenting to randomly generated product recommendations to actual unique recommendations generated from predictive analytics. Because of the confusion in the marketplace,

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