Decoding Your Recommendations Performance

Product recommendations, also known as “recs,” are a cornerstone to an effective ecommerce merchandising strategy. When fully optimized, recs typically increase retailer revenues by up to 5%.

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First Look at the New Relevance Cloud™

Today, we’re happy to announce that the Relevance Cloud is out of beta and available to all with the 15.02 release. This release introduces Build (API-based personalization building blocks) and delivers enhancements to our Recommend and Discover products, helping you to personalize every step of your customers’ purchase journey and setting you up for an exciting 2015!

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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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Building and Innovating the Customer Experience with the Relevance Cloud

Today, I’m super excited to announce the launch of the Relevance Cloud™– what we at RichRelevance believe to be the most comprehensive personalization solution for retail today. The Relevance Cloud is a re-imagining of all RichRelevance products with new features and more simple ways to access, use and implement each of RichRelevance’s products.

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Introducing the new RichRelevance Dashboard

Personalization is what empowers retailers to create a 1-1 relationship with customers online. By tracking engagement and other KPIs, you can quickly take stock of how are you doing with those relationships.

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Journal du Net – Le point critique des valeurs aberrantes dans le test A/B

Malcolm Gladwell a récemment vulgarisé le terme « outlier » (valeur aberrante) en l’utilisant pour désigner des personnes performantes. Toutefois, dans le contexte des données, les valeurs aberrantes sont des points de données très éloignés d’autres points de données, c’est-à-dire atypiques… Read more

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