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AI in Focus: Retail

AI’s influence on retail extends beyond online shopping and, more recently, is disrupting the brick-and-mortar stalwarts of the industry.

Transforming any industry through AI may seem daunting, but the results speak for themselves: 75% of organizations that implement AI technologies see an increase of sales by more than 10%. For retail, an industry that had more than $3.5 trillion in sales in 2017, a 10% increase is a wildly significant number.

As the retail industry has continued to adjust to online shopping, the majority of retail sales still happen in person: 85% of consumers still prefer to purchase items from brick-and-mortar locations. From better product suggestions to faster checkouts, AI isn’t just helping make smarter purchases online — it’s bringing physical retailing into the 21st century.

Here are three of the current AI trends taking place in the retail industry:

Personalized Recommendations

AI is helping retailers offer a more personalized shopping experience both over the internet and in-person. For product recommendations, Amazon has long been the leader in integrating AI and machine learning to suggest items that customers may want to buy based on their browsing and purchasing history. Similarly, 1-800-Flowers.com combined live customer service support with AI chatbots to help users choose products and streamline transactions. These brief AI chatbot conversations resulted in 70% of all online orders being placed directly through the AI software.

Offline, AI is mining customer data to make in-person shopping more convenient. By analyzing a user’s shopping habits, AI helps retailers anticipate recurring or common purchases like groceries and monetize those insights using highly specialized promotions.

Better In-Store Customer Experiences

AI isn’t just offering better recommendations; it’s creating better shopping experiences at brick-and-mortar retailers. Lowe’s, the big-box hardware retailer with cavernous stores filled with thousands of products in every shape and size imaginable, is taking advantage of AI by employing an autonomous robot to help shoppers navigate and shop. Dubbed LoweBot, the AI-enabled device uses natural language voice commands and a touchscreen interface to assist customers in locating products throughout the store.

At clothing retailers, machine vision is also enabling virtual mirrors that allows customers to preview what an outfit might look like without ever trying it on. Once users are ready to check out, companies like SmartCart offer shopping carts equipped with AI cameras that can automatically tally up a user’s purchases and make a payment through their mobile device.

Inventory Management

Combining insights gained from personalized recommendations and better customer experiences, AI-enhanced inventory management is transforming the way retailers keep their shelves stocked. Using predictive analytics, retailers can accurately forecast demand to help determine items users may want to purchase in the future. Like SmartCart, companies like FocalSystems are able to monitor brick-and-mortar in real time by attaching deep learning and computer vision cameras to shopping carts. Greater insights into supply and demand help retailers determine what items to keep in stock, leading to faster fulfillment and leaner inventory.

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Even though traditional brick-and-mortar retail has been undergoing massive changes, the reports of its death have been greatly exaggerated. AI is enabling physical retail to work more like online retail, offering better customer experiences that will only improve with time. As more retailers begin to adopt AI, the lines will continue to blur between physical and digital shopping as highly personalized shopping experiences offer accurate product suggestions that can be fulfilled at the tap of a button, whether the customer is physically present or not.

Dr. Nik Spirin
Director of AI for Gigster, managing projects in Machine Learning, Computer Vision, and Natural Language Processing. He holds a PhD in Computer Science from the University of Illinois at Urbana-Champaign and has over 10 years of experience doing AI / Machine Learning as a technology adviser, consultant or founder.

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