Posts Tagged ‘Target’

Semantic Tech Lends A Hand To Thanksgiving Holiday Sales

Photo courtesy: https://www.flickr.com/photos/119886413@N05/

Photo courtesy: https://www.flickr.com/photos/119886413@N05/

Retailers are pushing holiday shopping deals earlier and earlier each year, but for many consumers the Thanksgiving weekend still signals the official start of the gift-buying season. With that in mind, we present some thoughts on how the use of semantic technology may impact your holiday shopping this year.

  • Pinterest has gained a reputation as the go-to social network for online retailers that want to drive traffic and sales. Shoppers get an advantage, too, as more e-tailers deploy Rich Pins, a feature made available for general use late last year, for their products, using either schema.org or Open Graph. Daily updated Product Rich Pins now include extra information such as real-time pricing, availability and where to buy metatags right on the Pin itself. And, anyone who’s pinned a product of interest will get a notification when the price has dropped. OverstockTarget, and Shopify shops are just some of the sites that take advantage of the feature. Given that 75 percent of its traffic comes from mobile devices, it’s nice that a recent update to Pinterest’s iPhone mobile app – and on the way for Andoid and iPads – also makes Pins information and images bigger on small screens.

 

  • Best Buy was one of the earliest retailers to look to semantic web technologies to help out shoppers (and its business), adding meaning to product data via RDFa and leveraging ontologies such as GoodRelations, FOAF and GEO. Today, the company’s web site properties use microdata and schema.org, continually adding to shopper engagement with added data elements, such as in-stock data and store location information for products in search results, as you can see in this presentation this summer by Jay Myers, Best Buy’s Emerging Digital Platforms Product Manager, given at Search Marketing Expo.

 

  • Retailers such as Urban Decay, Crate&Barrel, Golfsmith and Kate Somerville are using Edgecase’s Adaptive Experience platform, generating user-friendly taxonomies from the data they already have to drive a better customer navigation and discovery experience. The system relies on both machine learning and human curation to let online buyers shop on their terms, using the natural language they want to employ (see our story here for more details).

 

  • Walmart at its Walmart Labs has been steadily driving semantic technology further into its customer shopping experience. Last year, for example, Walmart Labs senior director Abhishek Gattani discussed at the Semantic Technology and Business conference capabilities it’s developed such as semantic algorithms for color detection so that it can rank apparel, for instance, by the color a shopper is looking for and show him items in colors close to read when red itself is not available, as well as categorizing queries to direct people to the department that’s really most interesting to them. This year, WalMart Labs added talent from Adchemy when it acquired the company to bring further expertise in semantic search and data analytics to its team, as well as Luvocracy, an online community that enables the social shopping experience—from discovery of products recommended by people a users trusts to commerce itself. Search and product discovery is at the heart of new features its rolling out to drive the in-store experience too, via mobile apps such as Search My Store to find exactly where items on their list are located at any retail site.

What’s your favorite semantically-enhanced shopping experience? Share it with our readers below to streamline their holiday shopping!

 

Semantic Technology Jobs: Target

targetTarget is looking for a Principal Data Scientist – Business Intelligence in Minneapolis, MN. According to the post, “The Principal Data Scientist anticipates future business needs and identifies opportunities for complex analysis. Gathers and analyzes data to solve and address highly complex business problems and evaluate scenarios to make predictions on future outcomes and support decision making. Designs and drives the creation of new standards and best practices in the use of statistical data modeling, big data and optimization tools for Target.com and Mobile.” Read more

Machine Learning Predictive Analytics Take On Hacks, APM And More

rsz_prelertpixLast week the world learned that the hacks at Target hit more customers than originally thought – somewhere in the 100 million vicinity – and that Neiman Marcus also saw customer credit card information spirited away by data thieves. They’re not the first big-name outfits to suffer a security setback, could they be the last?

No one can ever say never, of course. But it’s possible that new tools that leverage machine learning predictive analytics could put a serious dent in the black hats’ handiwork, while also improving IT’s hand at application performance management.

A big problem in both the APM and security space today is that there’s just a ton of data coming at IT pros dealing with those issues, much of it just describing the normal state of affairs, and no one’s got time to spend reviewing that. What IT staffers want to know about are problems, which leads to a lot of rules-writing to identify thresholds that could point to issues, and to a lot of rewriting of those rules to account for the fact that things change fast in today’s world of system complexity – and to a lot of misses because of the impossibility of keeping up. Sixty percent of problems are still reported by users, not the tools IT is using, says Kevin Conklin, marketing vp at Prelert, whose machine learning predictive analytics technology is used in CA’s Application Behavior Analytics and available as Anomaly Detective for the Splunk IT apps ecosystem.

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Semantic Tech Checks In As The Holiday Shopping Begins

 

Photo credit: FlickR/crd!

 

With Thanksgiving Day, Black Friday and Small Business Saturday behind us, and Cyber-Monday right in front of us, it is clear the holiday season is in full force. Apparently, retailers – both online and real-world – are doing pretty well as a group when it comes to sales racked up.

Reports have it that e-commerce topped the $1 billion mark for Black Friday in the U.S. for the first time this year, with Amazon, Walmart, Best Buy, Target and Apple taking honors as the most visited online stores, according to ComScore. Consumers spent $11.2 billion at stores across the U.S. on Black Friday, said ShopperTrak, down from last year but probably impacted by more people heading out to more stores for deals that began on Thursday night. The National Retail Federation put total spending over the four-day weekend at a record $59.1 billion, up 13 percent from $52.4 billion last year.

Not surprisingly, semantic technology wants in on the shopping action. Social intelligence vendor NetBase, for instance, just launched a new online tool that analyzes the web for mentions of the 10 top retailers to show the mood of shoppers flocking to those sources. The Mood Meter, which media outlets and others can embed in their sites, ranks the 10 brands based on sentiment unearthed with the help of its natural language processing technology.  Read more