So, just how is AI improving the retail experience?

Like most men in the world, shopping (especially shopping for clothes) is an unpleasant experience for me, as I really feel like my time could be much better utilized. I make it a personal mission to get in and out in minimal time. So, I wonder to myself, “Could AI make my experience better?” OK, maybe it won’t turn me into a shopaholic.

But I think there’s a lot of potential for retailers to use AI to improve my shopping experience and make sure that I find what I need as quickly as possible, ensuring that I shop more frequently.

Pleasant shopping experiences

Amazon recently opened Amazon Go in Seattle, which takes shopping to a whole new level. It provides a checkout-free experience for its customers. There are no cashiers at all. Customers simply walk in, take what they like off the shelves and walk out; it’s as simple as that.

Many retailers are looking to replicate this concept, which will have massive benefits such as removing customer friction points (long queuing times, lack of cashiers) and minimising labour costs.

Consider the evolution of how customers started making payments at retailers. It’s gone from cash to credit card to mobile payment, and now totally automated.

Amazon uses cameras and machine learning algorithms to identify customers that walk into the store and items they pick. It can even detect if a customer has picked an item and decided to put it back on the shelf.

All that is required is for customers is to have an Amazon account and the Amazon Go app on their mobile phones. When customers walk in, they scan the app at the electronic readers at the turnstile and start shopping. Machine learning algorithms know exactly what they have picked and the customer is charged appropriately.

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We are at the tip of the iceberg

Thanks to major improvements in computing power and new algorithms, computer vision and natural language processing are making massive strides. In my view, though, this is just the tip of the iceberg: a tiny fraction of what can actually be done. Facial recognition is certainly not new, but retailers are using it in new ways, such as identifying age and other characteristics.

Cameras are also being used in new ways. Retail stores are using cameras to track when customers enter their stores and how they behave when they are there. By understanding how customers behave in the stores, insights from this data are used to improve store layout, encourage customers to stay longer and visit more often.

Consider the type of behaviour that can be captured and analyzed using video cameras. For example, a customer is window browsing and eventually goes into the shop. He then goes to an aisle/certain section and spends a considerable amount of time there. Retailers are using this rich data and optimise the store layout to make customers spend more time and also visit more frequently.

Smart inventory management

Recently I had the laborious task of home renovation and had to go shopping around for items such as tiles, fittings, etc. A painful experience indeed since almost all the things I wanted to buy were out of stock. Yet they were still on display, which made it more frustrating.

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