The key internal capabilities needed to ensure a successful digital shopping experience are personalization, automation and the unique identification of the customer across shopping channels. In this report, we discuss how AI and IoT are impacting the retail industry. Retailers that aim to remain competitive cannot afford to ignore the potential benefits of these technologies. AI, a technology that enables computers to make autonomous decisions, is a step forward in automation that is changing the retail industry. Retailers are using AI to analyze customer data, adapt how they interact with shoppers and predict demand in order to better manage inventory. Because consumers are bombarded with an unprecedented amount of information, being able to deliver highly personalized content for each individual customer is crucial to staying ahead of the competition. Meanwhile, the use of AI to anticipate demand and estimate when items will be returned should translate into more efficient business operations. Digitalization is the key that will unlock the future of brick-and-mortar retail, and the IoT is a crucial part of it.
Augmented/Virtual Reality Tools – Startups that leverage augmented or virtual reality to aid retailers in layout of stores and the design of promotional displays. InContext Solutions, which has worked with clients like Walmart, Nestle, and Kellogg's, lets brands visualize marketing concepts and test new designs on shoppers in virtual reality to gauge their efficacy before launch. Augment aims to help brands, such as General Mills, L'Oreal, and Coca-Cola, pitch their vending machines, kiosks, or merchandise displays to retailers by showing how they would look in augmented/virtual reality. Beacon-Based Analytics and Marketing – Companies that provide hardware and software to help stores track visitors. Many focus on data collection for internal analytics, such as merchandise tracking, adjusting staffing levels, monitoring promotions, etc. Euclid Analytics, for example, tracks visitors to monitor the impact of promotions on driving store visits and to better understand when people visit stores and specific aisles.
Tomorrow's retail stores want to take a page from their online rivals by embracing advanced technology -- everything from helpful robots to interactive mirrors to shelves embedded with sensors. The goal: Use these real-world store features to lure shoppers back from the internet, and maybe even nudge them to spend more in the process. Amazon's new experimental grocery store in Seattle, opening in early 2017, will let shoppers buy goods without needing to stop at a checkout line. This photo provided by SoftBank Robotics America demonstrates a shopping experience with SoftBank Robotics' humanoid robot called Pepper, waving at right. The robot can greet shoppers and has the potential to send messages geared to people¿s age and gender through facial recognition.
In their first guest exclusive with us, Acuvate Software shares the many different ways in which predictive analytics, combined with AI, is changing our industry. Acuvate provides AI and predictive analytics solutions for consumer goods and retail businesses. Their mission is to produce intelligence applications that simplify processes. A retailer can predict the number of footfalls for a given period, but cannot predict where these footfalls are likely to pause in the shop, stop for exploration and for purchase. But, for those retailers who have incorporated predictive analytics and Artificial Intelligence, knowing these gray areas is possible.
The rapid pace of innovation in the e-commerce sector propelled by the trend'bricks to clicks' is increasingly shifting consumers to online shopping. A major disadvantage for offline retail stores is their lack of knowledge on customers entering their premises. Here, artificial intelligence (AI) opens up a big opportunity to predict the purchasing behaviour of in-store customers. AI through its sub-technologies such as machine learning and deep learning can enable offline retailers to derive actionable insights from consumer data (structured and unstructured) to offer predictive and precise decisions for better customer experience. AI practices incorporated by global offline retailers The global offline retail industry has been moving toward increased automation, cashless transactions and self-checkout stores based on consumer behaviour patterns, and demand for increased convenience.