Category: Machine Learning

Human Algorithms – Three Key Ways that People Drive Automated Personalization

By Dan Darnell in eCommerce Merchandising, Featured, Machine Learning, Personalization on October 19, 2015

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In my last post I wrote about the 5 key differences between targeting and personalization. Several comments were made about the distrust of automated systems. While I understand the concerns, I think it is important to know that automated personalization systems using machine learning are still under human control…at least for now. First of all, I find it helpful to think of a personalization system as a combination of ... Read More »

Targeting vs. Personalization – 5 Key Differences You Should Know

By Dan Darnell in Big Data, eCommerce, Engagement & Conversion, Featured, Machine Learning, Personalization on September 30, 2015

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Any system that uses rules to determine the content being displayed to a segment, persona or audience is a targeting system and not a personalization system. The goal of personalization is to surface the most relevant items to each customer based on their current needs and what you know about them as individuals. The more you know, the more you should be able to personalize the experience to drive ... Read More »

December Personalization Roundup

By Dan Darnell in Machine Learning, Personalization on December 27, 2013

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Every year, I take stock of the past year to get an idea of what the New Year will hold, so I went through the 2013 monthly round-ups to select stories that defined the state of personalization, predictive analytics and other major retail trends last year.

Technically New Technologies

By Jen Burns in Events, Featured, Machine Learning on October 10, 2013

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At the in the “Future of Technologies” session, I heard about advancements like wearable technologies and robotics with even more changes and technologies to come.

Beware the Bias

By Marti Tedesco in Machine Learning on May 31, 2013

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One of the beauties of big data and machine learning is that is it supposed to be completed agenda-less.  The system collects data of all types and the machine learning algorithms watch and establish meaningful patterns and outputs as a result of the abundant data.  Seems simple enough. Unfortunately, as with most things, it’s not that simple. First, most systems, at least in ecommerce, don’t collect ... Read More »