Inc said on Tuesday it shipped over 5 billion items worldwide via its subscription based Prime service in 2017 while adding more new members than ever before. The e-commerce giant, which revealed its Prime shipment numbers for the first time, did not give comparable full-year shipment number for 2016. Amazon claimed that its Fire TV Stick and voice controlled smart device Echo Dot were the best-selling products among U.S. Prime members from any manufacturer in any category across all of its product offerings. The e-commerce giant, which revealed its Prime shipment numbers for the first time, did not give comparable full-year shipment number for 2016. Customers can receive free two-day shipping on most items by paying for a $99 annual'Prime' membership.

Loup Venture co-founder Gene Munster made the claim in a report highlighting eight predictions for the technology industry in 2018. 'Target is the ideal offline partner for Amazon for two reasons, shared demographic and manageable but comprehensive store count,' Munster wrote. Loup Venture co-founder Gene Munster made the claim in a report highlighting eight predictions for the technology industry in 2018. The analyst, best known for his incorrect prediction Apple would make its own TV set, claims the timing of the deal is hard to know. 'Getting the timing on this is difficult, but seeing the value of the combination is easy.' 'Amazon believe's the future of retail is a mix of mostly online and some offline,' Munster wrote.

Artificial Intelligence has unleashed the power for e-commerce businesses to explore countless opportunities to dramatically improve customer experiences, generate new leads and better understand their customers. Businesses are continuing to evolve and are steadily incorporating Artificial Intelligence into their strategies – a prediction from Business Insider has suggested as much as 85% of customer interactions will be managed without a human by as soon as 2020. There are many innovative ways businesses are exploring the potential of AI – I've spent a little time researching the best uses so far. With the advancement in Natural Language Processing, and a huge improvement in a machines ability to understand human language including words and text, the technology is there for retailers to explore Virtual Agents/Assistants. The two most well-known and obvious examples would be the Amazon Alexa Echo – they have already begun to integrate and partner with SkyScanner for flights, Dominos for pizza delivery, JustEat for takeaway delivery and Uber to ask Alexa to request a taxi ride.

Google is a good example. As nearly every other flagship phone released this year used two camera lenses to create a blurry background in photos. Google used a single lens on its Pixel 2 phones and relied on its AI software to blur the backgrounds of photos. Even though AI enabled a core feature of one of the company's flagship products, it's hard to attribute what direct impact the AI systems had on sales of the phone.

As time-pinched Millennials and Generation Z grow spending power, the need for efficient shopping platforms continues to rise. According to research conducted by SAP Hybris, 64 percent of consumers trust in-home assistants to purchase electronics due to the convenience the devices offer."As These technologies will not be successful on their own, however -- they will need a rich set of customer data in order to make relevant recommendations and be truly helpful."To The findings are relevant for more than holiday spending habits. The survey findings signal a large shift by consumers to rely on AI -- from chatbots to voice-activated assistants -- to complete shopping tasks.

The apparel market is one of the largest in existence, accounting for 2 percent of the world's GDP, and valued at roughly $3 trillion. Every year, American households spend close to $2,000 on apparel alone, and over 211 million of these shoppers make their purchases digitally. In an industry this large, and this competitive, it's hard to keep customers engaged and active with your lines. With the increase of digitalization, retail markets are growing at an unprecedented pace. Newer markets are already beginning to dominate sales.

Predicting the future is hardly a precise science, but it's possible to identify macro trends by paying close attention to what's happening in an industry. Here's what a handful of entrepreneurs, founders and executives see coming in 2018. "It's been three years since Alexa first showed up in our living rooms. When Amazon launched the first Echo, it seemed like a curious product to many. But the sales growth of Amazon's Alexa-powered product family has been meteoric in the past year. Not to mention that Google Home joined the party, and soon to be followed by the Apple HomePod. Amazon is now licensing Alexa and new devices--including thermostats, home lighting systems, remote controls, automobiles and more--which now have the super smart assistant built in. As consumers, we're becoming increasingly more comfortable and reliant upon using voice to talk with our phones, cars and smart home accessories. While I'm not about to say that the graphical user interface of the touchscreen is dying, there's little question that in 2018 voice will become a primary interface to the digital world. And with it, professionals and firms will develop specialized expertise for voice interface design and voice app development, as the VUI coexists with the GUI." "Major retailers have long ignored the importance of their supply chain and consumers are no longer willing to accept an inefficient buying process. Fewer locations to service is the only the first step for retailers needing to gain a competitive edge. The second is better control over the supply chain and less outsourcing. Large retailers will recognize this deficiency in 2018 and bring logistics in-house as a key differentiator."

This approach to predictive analytics applications can be illustrated by an example. Let's consider an e-commerce company that wants to boost its profits by growing sales to existing customers. The objectives might be to increase both the number of items bought by individual customers and the average amount they spend overall in purchase transactions. A typical strategy to accomplish those goals involves using a recommendation engine to try to influence customers to add items to their online cart as they shop. There are a variety of different analytics methods that the online retailer can incorporate into its recommendation engine to assign similar customers to groups so the engine can suggest products that they might be inclined to buy.

In many cases, the acquisition of well-labelled training data is a huge hurdle for developing accurate prediction systems with supervised learning. At Love the Sales, we aggregate sales products from over 700 multinational retailers, which results in over 2 million products a day that need classification. It could take a traditional merchandising team four years to complete this task manually. QCon.ai - Applied AI conference for Developers Apr 9 - 11, 2018. Connect with AI and Machine Learning practitioners who are driving the change in software.

Online retail has been around for more than 20 years -- artificial intelligence, even longer. The combination of the two, coupled with current computing power and data growth, can offer today's retailers a personalization punch that lifts sales. According to "The State of Retailing Online 2017," a survey of 74 retailers conducted by the National Retail Federation and Forrester Research, the median conversion rate for retailers in 2016 was 3%. It's easy to see how AI in retail can lead to a small change in conversion rates. Recommendations, not personalization: Many online sites feature static, quasi-personalized recommendations, such as people who looked at this product actually purchased that product listings, or results that link to similar products or the top products in a given category.