MIAMI, Feb. 3, 2017 /PRNewswire/ Men spend around 65% more than women when it comes to show their love on Valentine's day and jewels are their favorite gift to give, according to the analysis of consumer behavior patterns performed by Poder.IO, the artificial intelligence company for marketing and customer behavior prediction. According to Poder.IO, jewels are the preferred gift by men during Valentine's around the globe, even over flowers or romantic dinners. They spend over 210 dollars per gift, and women, a little bit more money savvy, spend around 127 dollars to surprise their significant other. Next to the jewels, clothing is the other favorite item of men with an average spend of 112.71 dollars. Those who don't want to splurge too much, but still want to make a gift go for gift cards, spending around 106 dollars.

Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand.

With Valentine's Day just around the corner, let's consider a company that we can all learn a few customer service lessons from, 1-800-Flowers. The company is innovative and totally focused on the customer. It all started in 1976. Jim McCann was an entrepreneur who owned several flower shops in the New York City area. Ten years later, he acquired the 1-800-Flowers phone number from another company that was going out of business.

Humans develop a common sense of style compatibility between items based on their attributes. We seek to automatically answer questions like "Does this shirt go well with that pair of jeans?" In order to answer these kinds of questions, we attempt to model human sense of style compatibility in this paper. The basic assumption of our approach is that most of the important attributes for a product in an online store are included in its title description. Therefore it is feasible to learn style compatibility from these descriptions. We design a Siamese Convolutional Neural Network architecture and feed it with title pairs of items, which are either compatible or incompatible. Those pairs will be mapped from the original space of symbolic words into some embedded style space. Our approach takes only words as the input with few preprocessing and there is no laborious and expensive feature engineering.

An effort to bring Target stores into future has reportedly been nixed before it could ever see the light of day. As Recode reports, Target's aptly named "Store of the Future" project, which would have put the retailer in direct competition with Amazon's forthcoming cashier-free Go stores, was abruptly canceled after a disappointing holiday season. According to Recode's sources, the new, smaller stores were slated to debut sometime this year and an internal team had already begun building out a test version. Instead of the normal rows and aisles most Target customers are used to, the Store of the Future would look more like a showroom and employ a team of robots to pick up items and bring them to customers at checkout. The stores also had an e-commerce component and Target intended to use the spaces to encourage other, non-retail experiences and community gatherings.

Amazon's Alexa was showered with attention at last month's CES tech show in Las Vegas, as dozens of companies invited the voice assistant to live in their cars, washing machines and set-top boxes. Yet, behind all that luster is a somewhat uncomfortable question about Amazon's 2-year-old artificial intelligence platform: Does Alexa make Amazon any money? The answer, say several analysts: No, but it will. And when it does, it'll be huge. As part of Amazon's fourth-quarter earnings report on Thursday, the company mentioned that Alexa-powered devices were Amazon's top-selling products this holiday season.

At NRF, retailers saw solid ideas and use cases for the implementation of AR/VR, helping them make the case for ROI. Machine learning will help retailers use these insights to create personalized experiences, forecast demand and set prices in more sophisticated ways. Predictive Artificial Intelligence 5. Watson Customer Engagement 1/31/2017Engaging Mobile Experiences5 Engaging Mobile Experiences Mobile continues to be a high priority for retailers. Even now, when most retailers have brand new apps and mobile-optimized websites, sales on mobile are not on par with desktop traffic. Retailers are challenging themselves to deliver experiences on mobile that not only engage, but also convert.

Retail Real Estate is experiencing greater change than ever before. The impact of changes in real estate and the consumer retail world is comparable to tectonic plates shifting across the surface of the earth, producing an energy force that few know how to harness or predict the outcome. The way we conduct retail and real estate are rubbing, creating friction & forces, sometimes against, and sometimes in harmony with each other. Year-end 2016 came and went with little time to pause and reflect as Amazon Go made the headlines in the final few weeks and continues to do so. We asked some of the Movvo team to share their predictions for 2017, the trends & innovations that will have an impact on retail real estate as we know it. "2016 is going to be remembered as the year a retail platform came from nowhere to hit Apple & Google where it hurts. Alexa from Amazon is an intuitive AI interface already flexing its muscle and proving incredible popular. Alexa is already present in 4% of US households and dozens of Alexa-enabled devices launched at CES Las Vegas from fridges to cars. It's an early vision of the death of the keyboard as an interface & will have an impact on the way consumers shop".

In its last financial quarter, it sold $32bn (£25.6bn) That "other" category encompasses everything from crucifixes to sex toys, board games to plyboard, and mousemats printed with the faces of obscure TV and Radio personalities. It has also diversified beyond its simple shopping business: the company will sell you something to be delivered in less than one hour, food from restaurants, and even digital content to be watched on your TV or listened to on your phone. And, of course, it has a hardware business which many other companies would kill for, producing ebook readers and tablets, and single-handedly creating the product category of "smart speaker" with the Echo. But there's another chunk of Amazon that you're less likely to know about.

There was a media frenzy when Amazon Go was announced in December 2016. A grocery store based initially in Seattle, it enables shoppers to literally just walk out with whatever items they choose thanks to sensors recording what they pick up and charging back to their Amazon Prime accounts. Facilitated by first swiping the Amazon app on your smartphone, it nods to the automated future of retail, but more than that the growing potential ahead for the phone to control the entire commerce experience. A wake-up call to retail execs around the world, the question on many people's lips is whether that concept is equally applicable to other verticals? From a value proposition, not to mention strategic business perspective, it's something that makes a great deal of sense for grocery, where both the barrier to entry and level of associated risk, is low.