Over the last few years, traditional retail has stagnated with some of the world's most ubiquitous retailers shuttering their storefronts. But as total retail sales stay flat, digital retail is experiencing rapid growth with no signs of slowing in the years to come. According to a late 2016 eMarketer study, digital retail sales grew 23.7% in 2016, and sales expected to grow to a total of $4.058 trillion by 2020, making up 14.6% of total retail spending that year. As digital retail continues to grow and offer consumers new ways to shop, we worked to identify the ways retailers are planning to generate revenue and grow their business, what they are prioritizing and the challenges they expect to face. To gather these insights, we conducted a survey in January 2017 with 202 marketers, primarily representing brick-and-click retailers, ecommerce companies, and online marketplaces. We'll be unveiling this research at eTail West, where ecommerce and multi-channel leaders from all around the globe will be connecting next week.

Voice-powered artificial intelligence is not something that's easy to set up for just any business, even if it might have real benefits in terms of driving sales or improving customer experience. Voysis is a startup that wants to change that, with an AI platform that can parse natural language input, and that works effectively in specific domains including e-commerce, entertainment and more. Voysis doesn't want to be Siri or Alexa – it wants to the perfect shop assistant, or the extremely insightful video store clerk. "Voysis is a complete voice AI platform," explained Voysis founder and CEO Peter Cahill in an interview. "What I mean by that is that the platform enables companies and businesses to rapidly stand up their own artificial intelligences that can be queried by voice or text."

Retailers are pushing for more technology to enhance consumers' shopping experience, such as chatbots, virtual reality and augmented reality, but new research shows customers might not care so much about it. The report, Reality of Retail Tech shows consumers are not that psyched about new tech from retailers, especially chatbots and smart mirrors. Research for the report was conducted by mobile commerce and engagement platform, GPShopper, along with research and consulting organization YouGov. Data show there is clear disconnect between companies and shoppers over what technology people want to use. "Developments in mobile are further giving way to more advanced technology like virtual reality and chatbots, being brought into the shopping experience," said GPShopper Co-founder and CMO Maya Mikhailov in a statement.

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Lowe's Home Improvement recently announced layoffs as a part of an effort to "overhaul its staffing model." The cuts, which will constitute less than one percent of the total staff, come in the context of a reshuffling of responsibilities, which a source told the Charlotte Observer is meant to provide an increase in "face time with customers." Some of the additional changes include reassigning job responsibilities and the elimination of the department manager title, a later Observer article reported. But Lowe's is also eyeing expansion. Lowe's plans to open 15 to 20 stores annually over the next three years, which the chain said will create 4,000 new store-level jobs. And despite the cutbacks, Lowe's continues to add staff as necessary to meet seasonal demands.

Leveraging data from disparate sources to provide more personalized promotions to consumers can seem like a fool's errand. The efforts, however, can be rewarded with higher key performance indicators (e.g., click throughs, conversions, average order values, loyalty). As part of our, "4 Companies You Didn't Know Worked in Artificial Intelligence" feature, Website Magazine caught up with Rubikloud CEO Kerry Liu to learn more about how his company helps retailers gather data from consumer behaviors and use it in meaningful ways. What are some common problems of retail promotions? Retailers tend to struggle with gaining a holistic view of their customers due to outdated legacy solutions.

The primary application of artificial intelligence in retail is customer service chatbots, intelligent search tools, and personalisation. Despite knowing where to put their money, only a handful of retailers in the UK have trialled AI due to it being prohibitively expensive. Most AI investment in 2017 will be targeted towards e-commerce -- though Amazon is something of an exception. Amazon intends to use AI to replace in store cashiers in its Amazon Go stores to detect products shoppers have picked up. Over the next five years a growing number of retailers will buy into AI as it becomes more affordable. Here's where some big players are putting their money: Most retailers use algorithms to suggest similar items or items bought by other customers already, but in 2016 John Lewis was one of the first retailers in the UK to implement an artificially intelligent visual search tool for its iPad app.

Prior to that, Siri made adding an event to your calendar or quickly looking up the weather as easy as a simple push of a button on your smart phone. At what point does "Siri, tell me the weather" or "Alexa, play music" become "I'll have a cheeseburger and fries" or "What aisle can I find the peanut butter on?" or "Does this shirt come in small"? As we move away from assistants who perform simple automated tasks, 2017 has the potential to turn voice assistant technology into a virtual customer service functionality. The convergence of chatbots and virtual voice assistants has the potential to completely change the retail experience. For years, we have heard rumors about quick service retail (or QSR) replacing humans with touch screen tablets.

Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Once your models are ready, Amazon Machine Learning makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure. Amazon Machine Learning is based on the same proven, highly scalable, ML technology used for years by Amazon's internal data scientist community. The service uses powerful algorithms to create ML models by finding patterns in your existing data.

January has been a month characterized by price cuts but low prices are not the only factor eating into profits. At a time when competition is increasing, not only from the discounters, but from new players with optimized supply chains and leading distribution networks, meeting the demands of customer experience has become far harder. Limited product availability, a longstanding challenge for retailers across the globe, has led to customers across the UK becoming dissatisfied with their grocery shopping. A bad customer experience ultimately eats sales figures and margins. Worse still, the vast majority of retailers are unaware of the scale of this problem.