Category: Featured

Data Scientist, Data Engineer and Data Analyst

By Vinay Verma in Featured, Technology and Science on June 27, 2013

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The role of data scientist grew alongside the internet as did a few other related engineering jobs. Data engineers and data analysts work with data scientists to complete the whole “big-data” picture. They work together to determine the data platform requirement, basic and advanced algorithms, and to deliver the visual tools needed to analyze and present the data and value creation back ... Read More »

Trending Now: Products, Content and Community

By Marti Tedesco in Events, Featured on June 19, 2013

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In addition to being ahead of the curve on social marketing, JackThreads and its parent company Thrillist, have figured out how to create a virtuous cycle of content, engagement and conversion.  When Jason Ross sold his company in 2010 to Ben Lerer and the Thrillist organization, it’s doubtful that they realized the scale of the alliance they had made ... Read More »

Best Practices in Social Commerce

By Jen Burns in Events, Featured on June 14, 2013

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PetFlow, a 3yr old company set to hit $65MM in online sales in 2013, covered “how social marketing became the rocket fuel for a small startup.” The co-founder and IRCE speaker, Alex Zhardanovsky, claimed he was nervous, but the results he shared on his company’s success were both humorous and engaging. Customers engage with Facebook’s rich demographic focusing capabilities PetFlow shared their frustrations with ... Read More »

The Pulse of Online Shopping at IRCE 2013

By Jen Burns in Events, Featured on June 12, 2013

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At IRCE last week, Gian Fulgoni, Chairman of ComScore covered the results of their recent report: The UPS Pulse of the Online Shopper.  The report which surveyed over 3,000 participants, gave great insight in to the pre- and post-purchase expectations of online shopping. Here are the report’s major insights: Tablets and Mobile devices Today, stores are displaying more and more “tablet” ... Read More »

A Personalization Manifesto – Why Bother? Part III of III

By Dan Darnell in Featured, Personalization on May 23, 2013

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Personalization means delivering relevant content to a shopper based on what is known about them. Relevance is defined as that content that is most appropriate to the user’s needs. We know the goal of personalization is to deliver content which best meets the user’s needs. But what about the business needs?  Ecommerce companies must also focus on maximizing key ... Read More »

A Personalization Manifesto – Personalize Based On User Type Part II of III

By Dan Darnell in Featured, Personalization on May 21, 2013

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Before any real personalization can happen, a retailer needs to first ask, how well do I know this shopper?  In most cases, the shopper will be an unknown or anonymous visitor.  These are users that you have never seen before or that you do not recognize. Using in the moment context and intent is the best ... Read More »

A Personalization Manifesto – Personalize for the “Now” Part I of III

By Dan Darnell in Featured, Personalization on May 16, 2013

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It is a common fallacy that ecommerce personalization must and should treat everyone as completely unique individuals.  Yes, I know we all think that we are completely unique people.  But the reality of it is that we are more alike in or choices and preferences than we think.  What is different about each of us though, are ... Read More »

Video Recommendations at Face Value

By Jen Burns in Featured, Recommendations on May 14, 2013

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Our good friends over at Invodo know that 57% of consumers rely on product videos to confidently complete a purchase. Video content exists as a medium for many things, but for retailers or other information providers, it helps consumers with a purchase, an experience or both. Video recommendations are similar to product recommendations, but are more interactive and ... Read More »

Algorithms, Merchandising and Psychology – Part 2

By Robin Morris in A Word from the Engineers, Featured on May 9, 2013

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In my last post, we discussed the recommendation algorithm, the merchandizing layer and the presentation layer as well as the fact that I am working on a KPI-optimizing algorithm that differs from a collaborative filtering algorithm. In running A/B tests on these differing approaches, we’ve found that the sites divide into two types. Type 1: ... Read More »

Algorithms, Merchandising and Psychology - Part 1

By Robin Morris in A Word from the Engineers, Featured on May 7, 2013

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I was going to write this blog about feature hashing, a massively useful trick when building classifiers and predictive models.  It saves the time and complexity of building a dictionary and allows the hashed feature vector to be smaller than the number of possible features.  It is smaller because the number of actual features in a particular data set is often much ... Read More »