TechTarget – Big data challenges include what info to use—and what not to

RichRelevance Inc. faces one of the prototypical big data challenges: lots of data, and not a lot of time to analyze it. For example, the marketing analytics services provider runs an online recommendation engine for Target, Sears, Neiman Marcus, Kohl’s and other retailers. Its predictive models, running on a Hadoop cluster, must be able to deliver product recommendations to shoppers in 40 to 60 milliseconds — not a simple task for a company that has two petabytes of customer and product data in its systems, a total that grows as retailers update and expand their online product catalogs.

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This post was written by RichRelevance

ABOUT RichRelevance
RichRelevance is the global leader in experience personalization, driving digital growth and brand loyalty for more than 200 of the world’s largest B2C and B2B brands and retailers. The company leverages advanced AI technologies to bridge the experience gap between marketing and commerce to help digital marketing leaders stage memorable experiences that speak to individuals – at scale, in real time, and across the customer lifecycle. Headquartered in San Francisco, RichRelevance serves clients in 42 countries from 9 offices around the globe.
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