Retail



Research: Retailers to spend $37.3bn on AI software between 2019 and 2025

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The retail industry is suffering from the decline of physical stores, and is turning to artificial intelligence in order to breathe new life into the shopping experience, suggests latest research from Omdia. The analyst firm predicts that spending on AI software by retail organizations will reach $9.8 billion per year by 2025, up from just $1.3 billion in 2019. Omdia has identified a total of 24 use cases for AI software in retail, and analyzed the 11 that are expected to account for 91 percent of spending in the next five years; it predicts that this particular niche of the AI market will be led by supply chain and inventory management software, with a 15 percent market share. This will be followed by AI-based applications in image recognition and visual search (13 percent), virtual digital assistants fine-tuned for the needs of eCommerce (12 percent), video surveillance analytics (12 percent), and tools that enable personalized customer journeys (10 percent). "AI technologies have begun to move from research lab projects to the engines that drive genuine business solutions. These technologies are disrupting a variety of industries, from healthcare and telecommunications to financial services and retail, primarily by bringing scale and efficiency to bear in solving business problems," said Mark Beccue, principal analyst at Omdia.


Home :: New Arrivals :: Building Machine Learning Powered Applications: Going from Idea to Product

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All Indian Reprints of O'Reilly are printed in Grayscale Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers-including experienced practitioners and novices alike will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success.


COVID-Consumers: Pessimistic, but spending more online - Search Engine Land

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Consumer sentiment has turned sharply negative as the virus has disrupted every aspect of daily American life. According to a consumer survey from Engine, 88% of consumers in the U.S. are now concerned about the pandemic. And according to another survey of roughly 2,600 U.S. adults from L.E.K. Consulting and Civis (.pdf), between 80% and 90% of adults expect a recession next year. In addition to measuring consumer sentiment, the survey explored how the coronavirus has shifted buying patterns across industries. Generally, the survey finds "significant increases in at-home activities, particularly cooking at home, watching television, browsing social media and exercising at home."


Analyzing and optimizing Amazon Lex conversations using Dashbot Amazon Web Services

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This post is co-written by Arte Merritt, co-founder and CEO of Dashbot. In their own words, "Dashbot is an analytics platform for chatbots and voice skills that enables enterprises to increase engagement, satisfaction, and conversions through actionable insights and tools." After you have deployed a bot, it is critical to analyze bot interactions, learn from this analysis, and use these learnings to improve the end-user experience. Conversational interfaces are easier to analyze than websites and mobile applications. You can infer user behavior directly from conversations instead of guessing what your users want by stitching together page views and choosing events.


NRF 2020: Retail technology trends and deals InfotechLead

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National Retail Federation's annual Big Show and Expo in New York – have announced several retail technology deals, indicating that innovation is the key to improve customer experience. Total e-commerce revenue in 2020 will reach $3.52 trillion, an explosion that will force retailers to find faster and more convenient modes to reach the final mile and yard, according to tech market advisory firm, ABI Research. There is increasing convergence of online and in-store businesses, with brick and mortar positioned as hubs closer to the customer, as well as e-commerce sites directing package delivery to retail outlets. Additive investment will grow in Buy Online Pay in Store (BOPIS) options. Alibaba and JD.com have focus on growth through lower-tier cities, chasing fast growing, third place Pinduoduo's rural playbook to reach the next 600 million people.


Reflections on NRF's 2020 Vision: Finding Experience in the Data - EVRYTHNG

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We're officially a month into 2020 and the new decade is well underway. So much so, it is worth reflecting back as it jolted our eyes open and set the stage for what's to come. To sum it up in a word, data. Data, data everywhere – how to get it, how to use it, how to see it. Everywhere you looked there were analytics dashboards.


Robots in Aisle Two: Supermarket Survival Means Matching Amazon

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At a Stop & Shop supermarket near Hartford, Connecticut, one of the nation's first micro-fulfillment centers (MFCs for short) opened at the end of last year. Ahold Delhaize, Stop & Shop's Dutch-Belgian parent, carved out 12,000 square feet from the store during a recent remodel to make room for the MFC, which is operated by the retailer and with support from Takeoff Technologies. Through a glass window in a corner of the store, curious shoppers can get a glimpse at the automated mini-warehouse, where robots whoosh around grabbing cereal and soup. The system can handle up to 3,500 orders a week, although it's nowhere near that level yet. Stop & Shop's not alone: Walmart, Albertsons and others are also testing MFCs.


Why every online store needs a customer service chatbot

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In recent times, organizations have been competing with one another to implement chatbots for various reasons, including enhancing customer experience, streamlining processes, and fueling the demand for digital and innovative technologies. Cognitive technologies such as chatbots have become an apt candidate for end-use application as they have high automation feasibility, high potential of accuracy, low complexity and low execution time. Raising the bar through intelligence, virtual assistants have been propelled by advancements of mobile technology. Technology giants are putting their weight on a platform designed to answer ad-hoc queries in real-time and fuel sales as chatbots can remember customer preference and use order history to learn from customer responses to the product advertisements, suggest products, and cross-sell aptly. For instance, if a customer asks for a pizza recommendation with a chatbot, it can remember which pizza the customer ordered and follow up with it when offering a recommendation for another pizza or a restaurant.


Why Safeway grocery clerks worry about artificial intelligence

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Consider the grocery clerks at two Safeway stores in the San Francisco Bay Area. A few weeks ago, over 200 workers who are members of the United Food and Commercial Workers Local 5 (UFCW5) union picketed a Safeway store in San Jose, Calif. to voice concerns about a push by parent company Albertsons to add more A.I to its operations. Albertsons recently partnered with the startup Takeoff Technologies to create mini warehouses where computer vision technology automatically sorts items that shoppers order online. Using A.I. reduces the need for Safeway staff to manually locate and grab items for delivery--workers now just retrieve the finalized orders from a conveyor belt and sign off on them for eventual delivery. Several grocery store chains are investing heavily in micro-fulfillment centers after Amazon helped to popularize as-fast-as-you-can deliveries, said Andrew Lipsman, a principal analyst at research firm eMarketer.