How AI is Revolutionizing Retail

How AI is Revolutionizing Retail

We’re living in a brave new world of retail B2C commerce. Technology has supercharged retail’s infrastructure, and no tech is more powerful for this engine than AI. While many retail giants have been investing in AI and machine-learning solutions for some time, the trend is so strong that IBM commissioned a study focusing solely on the convergence of humans and artificial intelligence in the retail space. These findings were clear and incontrovertible.

After surveying 1,900 retail reps in countries across the world, IBM found that AI will continue to revolutionize the retail industry, allowing for innovation and improving every process, from demand forecasting to supply-chain planning to store operations to customer intelligence to pricing and promotion. All of this serves two fundamental purposes: to improve the customer experience and to better equip employees with the tools needed to provide a more streamlined omni-channel customer experience.

Below we take a deeper look at the principal ways in which AI is revolutionizing retail.

Inventory demand forecasting

One of the many intricate arts to running a successful retail business is being able to accurately forecast product demand and optimize merchandise allocation for various stores. There are a number of advanced analytics platforms out there, powered by AI, that help achieve this. One effective example is Celect ML, whose data-modeling and prediction database runs on AI developed at the Massachusetts Institute of Technology’s AI lab. Lucky Brand Jeans is just one of many retailers to utilize Celect to help manage their store inventory.

This tech predicts merchandise demand by understanding customer choice. It looks at a number of factors, including how demand for a certain product in an assortment is affected by the greater product assortment around it. The platform is able to effectively discern this context between products by pulling data from retailers’ CRM programs as well as sales transactions. This results in a high accuracy of forecasting that tells retailers exactly how much merchandise to allocate for each store, thus helping them to better manage stock.

Logistics and delivery

Not only can AI help a retailer to better manage their product supply, but it can assist in predicting supply-chain disruptions as well as facilitate product delivery. Regarding the former, it does this by looking at certain data points mentioned above, like CRM programs and CRM transaction. As for the latter, AI helps save money on last-mile delivery through the advent of technology like self-driving cars, delivery trucks, drones, etc. The machine-learning element also maximizes efficiency by being able to make decisions about route planning, managing delays, and more.

Store operations

AI not only improves store operations by powering advanced CRM processes and inventory management, but it is now transforming more conventional tools already in the retail store space. Amazon Inventory Management is a crucial aspect of the company’s vast e-commerce operations. It involves efficiently tracking, storing, and replenishing the immense range of products available on the platform to ensure timely deliveries and optimal customer satisfaction. Take retail-technology vendor Caper, for example. They’ve developed an AI-engine for a “smart” shopping cart that utilizes multiple cameras, sensor fusion, and computer vision to automatically tally the items in the cart. All that’s required of the customer is to scan each product barcode once before putting it in this new self-checkout cart. Once they have, the cart will display the total cost of all the customer’s items as they shop.

It’s technology like this that showcases that AI has a place in the physical world of retail as well as the digital. So brick-and-mortar stores don’t need to go away entirely; they simply need to adapt. We’re seeing more along these lines with the thousands of cashier-less Amazon Go grocery stores that are popping up throughout the country.

Personalization and customer intelligence

Personalization is all the rage in every corner of the marketing world right now for the simple reason that modern consumers like a personalized experience. What they don’t like is to be treated like a number or percentage. Enter the Smart Shelf.

Like with Caper’s brick-and-mortar tech, this AI retail solution comes in the form of a product shelf that can work all kinds of wonders. It utilizes cameras to discern demographic (age, gender, ethnicity, etc.) and biometric information of the potential customer which it can then use to make product recommendations via LED displays. Not only that, sensors on the Smart Shelf recognize when a certain product has been removed, it adds that item to the cart, and then it authorizes a cashier-less payment via the customer’s digital wallet.

Marketing and customer relationship management

The above examples of AI-powered in-store tech are all very exciting, but just as compelling is what machine-learning can do in the marketing realm. AI-powered marketing tools using creative algorithms have the ability to discern all kinds of customer insights and boost marketing initiatives. This includes improving marketing content, promoting content engagement, more precise ad targeting, more efficient lead follow-ups, customer segmentation on a macro level, helping customers via chatbots and AI assistants, delivering tailor-made brand messages, personalizing search and browsing experiences, and in general processing mass customer data at speeds which humans are simply not capable of doing.

Conclusion

In the end, the real question isn’t whether AI is influencing retail but just how quickly and fundamentally it is re-shaping the entire retail landscape. The changes are coming so fast and furious that it’s almost impossible to keep up with them all. Those retailers who do will ensure their success in a 21st-century AI-powered world.

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