WINTER 2019 RELEASE

MAKING THE LEAP TO HYPER-PERSONALIZATION

One trend continually on the rise is shopper dissatisfaction with what once passed for personalization. More so than ever before, your customers want and even demand that you know them better, understand their individual needs, and inspire them to continue shopping. The time has come to rethink personalization by making the leap to Hyper-Personalization. With Hyper-Personalization, and the new features launched in support, we allow you to take the next evolutionary step and do what the marketing clouds and rest of the personalization industry can’t: deliver real-time personalized and shoppable experiences at the individual level.

read more
EMEA personalisation summit review

2019 EMEA PERSONALIZATION SUMMIT RECAP

RETHINKING PERSONALIZATION AND DELIVERING ON SIGNATURE MOMENTS

This time last week we were wrapping up our 8th annual RichRelevance Personalization Summit in EMEA. As always, we sought out a unique venue removed from the hustle and bustle of the busy streets of London where we could bring together international brands and retailers for an evening of networking and dinner, followed by a day of thought leadership, personalization success stories, and announcements of innovation on what’s to come for RichRelevance in 2019 and beyond.

read more

Diginomica – RichRelevance crafts recipe for ingesting big data

Analytics has always been the sexy bit of data management. That’s where the nuggets of insight are teased to the surfaced and millions made by understanding why diapers sell beer or who is newly pregnant or how to route a jet so it burns 25% less fuel. But, behind that, there has always been the grunt work of extracting data from multiple, disparate sources, cleansing it of partial or bogus records, transforming it into a consistent and usable format, and loading it into the target analytics engine.

Read more

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.

Read more

Scaling the peaks of Black Friday 2014: Shopping Insights and Metrics

We’ve finally slowed down enough to reflect on how we did in 2014 and the final holiday push: pretty darn great if I may say so myself. We ended another year at 100% uptime all year with record loads and HUGE growth.

read more

RichRelevance Expands Global Data Footprint with New Data Centers in Singapore and Stockholm

Eleven data centers enable the company to maintain uptime and performance at global scale, while increasing speed to delivery, for the world’s largest retailers 

read more
More posts