In Minority Report, Tom Cruise, is on the run. He enters a shopping center, where every virtual assistant calls him out by name, offering tailored suggestions for the latest luxury car, perfume, or outfits.

This future is here now. Artificial intelligence, robotics and computer vision are increasingly taking root within the retail industry, and not just for personal recommendations. In fact, the technologies are set to disrupt every area of the retail industry, from warehouse management to store security. Here is where these transformations will be the most impactful.

Artificial Intelligence for Retail Inventory and Supply Chain Management

Inventory planning is by no means unique to the retail world, but it’s certainly where factors are some of the most unpredictable. How do you anticipate seasonal trends with economic forecasting and consumer shopping habits? How do managers ensure they’re not overstocking or unable to fulfill orders? One solution: using machine learning algorithms to increase the precision of demand forecasts.

While SKUs and transaction data already help the matter, the real advantage of ML is its ability to combine historical and real-time data. This means AI can identify patterns that might have been missed by traditional tools - and even offer suggestions about reducing errors in inventory management. In short, the future of ordering and stocking could be performed with much higher accuracy, reducing waste and increasing a company’s bottom line.

While SKUs and transaction data already help with demand forecasts, the real advantage of ML is its ability to combine historical and real-time data.

Supply chain management also has a lot to gain from machine learning. Root cause analysis exists to find lapses in communication or movement of fata, but human guesswork often clouds judgement in these matters. Feeding data to the right algorithms can uncover patterns to detect which step failed along the supply chain, whether it comes from warehouse processing or vendor management.

Robot Workers: Transforming Warehouses and Delivery Vehicles

Another sci-fi vision come to life: the fully automated warehouse run by British supermarket Ocado. Robots lift, sort and rearrange a vast inventory of online food orders, 24 hours a day. While individual machines don’t have much decision power, they are run by a central “AI brain”. It calculates how to optimize movement and product placement, speeding up the deliveries in ways human workers could not compete with.

Similarly, the days of delivery drivers’ jobs could be numbered. From drone delivery to new cargo systems, the technology and systems are already in place to automate how retail items get from A to B. Amazon Air is already on its way, and unmanned flying vehicles (drones) will also benefit from a Artificial Intelligence brain that can improve logistics thanks to route optimization algorithms.

Personalization and Shopping Assistants (and Upselling)

This is the image that immediately springs to mind: friendly robots and virtual assistants accompanying you as you shop. We already have the LoweBots to answer questions and guide you in Lowe’s giant US home stores. SoftBank’s robot Pepper is also increasingly popular, set to appear in more than 1000 Nescafe shops across Japan. As computer vision and natural language processing technologies continue to improve, it’s surely something we’ll see more of in the very near future.

But aside from a neat gimmick, what are the benefits of using artificial intelligence to power customer service? Quite simply, it’s about leveraging the power of big data. While ecommerces already benefit from a tremendous amount of user information (enabling Amazon to drive 35% of its sales through algorithm recommendation), brick and mortar shops can struggle with acquiring data and making it actionable. Following the model of online analytics, AI-powered shop assistants have the potential to increase sales and offer better tailored product recommendations.

Bringing Computer Vision Into Brick and Mortar Shops

Video analytics and image recognition are coming to a shop near you. First, it’s for managers to get a digital record of what’s happening in store. The company Trax, for instance, raised $125 M based on its ability to digitize products on shelves. Staff can scan shelves on their mobile devices and instantly let managers what’s happening in real-time. The potential for improving product visibility and consumer engagement is tremendous.Then, there’s also the issue of theft. While machine-learning is making leaps and bounds in online fraud prevention, physical retailers still rely on the good old security camera. This is all set to change as computer vision and machine learning become better at object and image recognition and behaviour tracking.

Better Consumer Tech for Fashion Lovers and Creatives

Finally, the way in which we create and buy clothes will be turned on its head by new technologies. The Reimagine Retail project, for instance, already combines natural language understanding technology and deep learning algorithms to produce key data on fashion trends. Its goal? To better anticipate demand and accelerate the workflow for fashion designers.

Consumers will also benefit from AI-powered tech for their fashion needs. Shoppers can already use Cisco’s Style Me Virtual mirror to try on virtual outfits and capture the digital images. And UK startup MeTail is well on its way to distribute a tech that lets you virtually try clothes from online store. Using computer vision, you can create a life-like avatar of yourself and see how clothes look and move in a realistic way.

Conclusion and Key Points

As machine learning and AI continue to improve, the lines between online and physical retail strategies will continue to blur. We will buy online and get deliveries powered by deep-learning. We’ll pop in the store, and try on clothes in virtual mirrors that use powerful object recognition software. One thing is for certain, machine learning is going to permeate every area of the retail world. And only retailers with the best data science strategies in place will remain competitive by reducing waste, increasing sales, and improving business decisions.

Originally published on August 06, 2018 Topics: Machine Learning Deep Learning Retail Computer vision


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