Posts Tagged ‘Thanksgiving’

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!

 

Moviegoer Social Sentiment: Big Data Analysis For Big Business

Like lots of other families over the recent Thanksgiving weekend, we made our way to the movies. Our choice: Life of Pi. We’d highly recommend it, and according to the IBM Social Sentiment Index, as applied to Moviegoer Social Sentiment over the holiday weekend, so too would a lot of other folks. It earned a 90 percent positive rating.

IBM has engaged in the social sentiment index pursuit in some other endeavors – using its advanced analytics and natural language processing technologies to analyze large volumes of social media data, it had another recent take on Black Friday, for example. It tallied up that shoppers expressed positive consumer sentiment on promotions, shipping and convenience as well as the retailers themselves at a three to one ratio (see our story here for other takes on semantic tech weighing in on the holiday shopping season).

It’s also applied its social media analysis smarts to studying births of trends (cycle chic is on the rise), and which tennis player was on the hearts and minds of the crowd at the U.S. Open (Novak Djokovic and Laura Robson winning the love, with positive sentiment scores at 90 percent or better).

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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

Gobbling Up With The Semantic Web

It’s time to get semantic with your Thanksgiving meal – or what’s left of it. To that end, we toured some semantically-powered foodie services to get some ideas about what to serve up for the big day. Maybe you’ll even find some things you just may never have considered without some semantic web services making it easy to pinpoint to your tastes (literally) or nutritional concerns, or that let you bring to the table the latest delicacies getting high-fives on the social web sentiment scene.

Here we go:

  • Google. For some Thanksgiving-ers, it’s simply off “to the Google,” as the dear family member in charge of our celebration says, to suss out recipes that have been marked up with rich snippets or schema.org microdata. Tired of the same old green bean casserole and plain mashed potatoes each year? Narrow the search engine to its recipes focus and you’ll find a few choice nuggets of Thanksgiving’s best vegetable side dishes – the traditional ones are there, like Martha Stewart’s garlic mashed potatoes (for a bit of a twist) and, yup, the tried-and-true green bean casserole. But you’re not likely to have thought of a pickled root vegetable salad before, courtesy of Cooking Channel TV, are you? Be prepared to set aside an hour and thirty minutes, though, to make it happen.   Read more

Serve Up Thanksgiving Dinner With the Semantic Web’s Help

Photo courtesy: Flickr/Florian

How’s your Thanksgiving meal planning and prep going? Hopefully well, but some day, semantic web technologies might help it go even better.

A couple years back, K. Krasnow Waterman – visiting fellow at MIT who co-chaired its Linked Data Product Development Lab that has evolved into a course – organized a lecture on the topic of the business value of the semantic web. For her presentation, she focused on catering to a consumer application — that is, how the technology could add up to improving prepping a holiday dinner.

It was fun to do it then, Waterman says, and new developments like the integration of Siri into the iPhone could push the envelope even further, adding a voice-activated intelligent personal assistant to the mix.

She describes the vision of streamlining T-Day operations via the semantic web with the initial finding of recipes online. From there, apps could take the recipes a user has selected and extract as structured data various entities – i.e., the ingredients for a shopping list. After the app pulls the ingredient list, the cook-to-be could indicate what’s already in the house (e.g., flour, salt, pepper), so it’s only searching for what’s needed. 

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