How edge computing is reshaping retail
From the rise of e-commerce to Amazon Go, retail has experienced a drastic transformation in the past decade, and advancements in edge computing are expected to drive further change: Experts project that 85 percent of customer interactions in retail will be managed by artificial intelligence (AI) by 2020. Amid this disruption, brick-and-mortar retailers are feeling the pressure to adopt emerging edge technologies such as AI, Internet of Things (IoT), and object and image recognition, in order to compete.
More personalized, efficient retail
In today’s high-stakes global retail market, edge computing increases personalization capabilities that elevate the customer experience while uncovering opportunities to improve operational output. The restaurant CaliBurger, for example, recently began testing self-ordering kiosks that use AI-powered facial recognition to look up customers’ loyalty accounts and show personalized ordering options based on past purchases. Customers no longer have to enter their loyalty program information and can order their desired meal faster, and employees can serve more customers with the time saved by eliminating the ordering process. By leveraging edge technology to gather and analyze information on customer behaviors and trends, CaliBurger and other retailers can better serve customers and work more efficiently.
Faster checkout, fully stocked shelves
Edge technology is changing more than just retail POS systems – in some instances, it’s changing how customers shop entirely. The most well-known example of this can be seen in Amazon Go’s IoT shopping experience, which utilizes sensors, image-processing technology and machine learning to automate the shopping experience. With this model, checkout times are eliminated, and shoppers are instantly billed through their Amazon accounts. Tracking and recording the items a customer picks up (and puts back down) enables Amazon to compile a personal profile, generate insights on the customer’s purchasing decisions and suggest new purchases.
Smart shelves are also gaining ground in efforts to create better in-person retail experiences. Wiseshelf, a pioneer in IoT smart shelving, gives retailers the ability to detect and manage shelf inventory using machine learning and image and object recognition technology. Its smart shelves can track and quickly alert retailers when items need to be restocked, preventing a missed sales opportunity and a disappointed customer.
As retail continues to evolve, we can expect to see a widening gap between early adopters of edge computing and those who fail to implement. Companies must have adequate talent, resources and data to support edge technology and convert their data into an organized, actionable data platform. For brick-and-mortar retailers that are determined to remain at the head of their markets, now is the time to put AI, IoT and machine learning at the forefront of technology investments.
Learn more about Concentrix Catalyst’s innovative edge service offerings.Tags: Artificial Intelligence, e-commerce, Edge, Retail