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5 Artificial Intelligence Use Cases in Retail

Artificial Intelligence may seem pretty distant from our current retail experience, but this is simply because it’s been so seamlessly integrated into our consumer journeys. The fact is, AI is radically reinventing the retail landscape as we speak. Unlike the cyborg-ruled dystopias we’re used to seeing on film, AI isn’t running our lives, it’s changing our lives for the better, even if we don’t know it.

Artificial Intelligence in Retail

From applying machine learning and Warehouse Management Software to using computer vision to customize promotions, retailers are taking advantage of AI to connect with their customers in a personal way. Despite the massive surge in online shopping, Amazon isn’t the only player in the retail game any longer, artificial intelligence is helping more and more retailers operate extra efficiently.

The stats speak for themselves. AI is predicted to increase retail store revenues by 38% by 2022, and it’s predicted that AI will add an almost incomprehensible 16 trillion dollars to the worldwide GDP within the next decade. In order to compete in this AI-forefronting retail landscape, retailers must use this emerging technology in the right ways to keep and grow their customer base.

When used correctly, AI can help retailers respond to their customers in new and innovative ways by converting data into insight and insight into real-time change. This change drives better outcomes on business messaging and increased revenue, but it also propels amazing customer experiencesan accessible business messaging platform. But wait. How do you ensure that AI will deliver such rewards?

Let’s take a look at how AI is already being used in day-to-day retail processes, both in terms of in-store and online shopping experiences. And, while we’re at it, let’s explore five massively successful AI use cases in retail so you can fully understand just how much AI can do for your business.

How Is AI Being Used in Retail?

Artificial Intelligence in Retail

The closer you look, the more AI reveals itself in many everyday operations of an increasing number of retailers. In the aftermath of a pandemic that forever changed the way in which we shop, and moreover the way in which we think about retail as a whole, artificial intelligence has become a bridge linking physical and virtual spaces (and sales!) in real-time.

To overcome the challenges faced by an increasingly online-present customer base, retailers have introduced AI in innovative ways both in-store and through their ecommerce operations to improve customer satisfaction. This doesn’t necessarily mean that a robot’s going to help you decide between a bucket hat or a fedora. AI is rather helping with all kinds of covert operations:

  • AI is being used in Customer Relationship Management software to automate marketing activities.
  • Predictive analytics powered by AI is being used to identify which customers are likely to choose which products.
  • AI is helping to store and process huge amounts of data from many sources via the cloud to help plan things like inventory management.
  • AI is being used to monitor customers both in-store and online to provide data about the customer’s physical shopping behaviors.

It’s AI’s ability to transform huge amounts of data into quality insight and real customer intelligence, that then propels the right kind of action at the right time, that makes it so full of potential. But with so much promise, how are companies using AI in the most intelligent ways? Here are five use cases for AI in retail to give you an idea.

AI Retail Use Case: In-store Customer Experiences

Artificial intelligence hasn’t just reshaped the online shopping experience, it’s helping save the in-store customer experience too. AI customer intelligence can be unleashed in-store to pick up on trends, take physical stock counts, assist customers, and aid staff too.

Take the humble virtual fitting room. What started as a novelty turned rapidly into a necessity during the pandemic, and it’s not going anywhere. It saves customers time and matches outfits perfectly to every figure. Companies like Old Navy, Gap, and Levi’s have all seen profit increases since installing virtual fitting room scanners in their stores. 

Artificial Intelligence in Retail

AI is also revolutionizing the check-out. Many of us are justifiably concerned with picking up germs from point of sale systems, and AI is now helping customers check out without touching anything. Moreover, smart self-checkout systems can provide a range of payment options, and integrated video analytics can help identify products when the barcode is damaged or missing.

AI Retail Use Case: Trend Prediction and Personalized Shopping

Maybe the biggest and most notorious example of this is the now common knowledge that Facebook uses AI to personalize ads, but trend prediction and personalized shopping are doing so much more than this both online and in-store. Trend prediction and a totally personalized shopping experience are perhaps the main goals of AI in retail, and it’s getting more clever by the moment.

For example, AI point of sale systems can capture customer purchase data to predict new product recommendations for them. It can also collect data about personal customer shopping habits to propel more successful product promotions. Collecting this passive customer data leads to experiences tailored to each customer’s patterns and preferences. 

The innovation doesn’t end there. Take, for example, the ways in which AI is helping customers choose the perfect gift. Gifts When You Need, launched by 1-800-Flowers.com, is an AI-powered personal gift shopper. It provides tailored gift recommendations based on information provided by customers by comparing gifts purchased for similar recipients.

AI Retail Use Case: Automated Inventory and Supply Chain Management

Artificial Intelligence in Retail

AI is streamlining inventory and supply chain management through one genius idea: automation anywhere. Managing and maintaining inventory has always been a major challenge for retailers. But AI is helping retailers regain a comprehensive view of online and physical stores, shoppers and their habits, and of course products with the help of intelligent SAP automation.

A great retail use case of automated inventory management is the Smart Shelf. The Smart Shelf has been employed by retailers like the grocery chain Kroger to do all kinds of inventory checks. Smart shelves can identify out-of-stock items or pricing errors with complete accuracy. 

Innovations like these are helping retailers run more efficiently, something we can all get behind.

AI is encouraging retailers to think of a business process as a service. Processes like inventory checks can be outsourced via the cloud to keep data cleaner, accomplish tasks faster, and reduce the workload necessary to verify a process. Robotic process auto attendant is, quite simply, freeing up employees so they can get back to offering exceptional customer experiences.

AI Retail Use Case: Experiments in Retailing

Predicting what retail campaigns will hit just right with your customer base can always be a challenge, but even here AI is paving a new way forward. AI can help retailers learn and understand customer behaviors and trends - and even more impressively - AI can provide a new landscape on which to test these predictions before turning them into reality.

This is where artificial intelligence’s ability to aid with split testing, or a/b testing methods, really shows just how crucial it is to be able to test before you implement. AB testing harnesses AI to approximate the outcome of new strategies without actually putting them in place. It does this by testing different versions of things against each other, like varying formats of a landing page. 

Then, by using online marketing tools like Google Analytics, data is collected about the effectiveness of each variable. This allows businesses to find the best performing version of something before spending unnecessary resources on a doomed campaign. AI services then interpret data and make decisions about what and how to implement the best promotion.

For example, Netflix uses a stringent AB testing model to create that personalized, streamlined experience we all know so well. Each and every change that Netflix makes to its website first goes through an extensive AB testing process before showing up on our screens.

AI Retail Use Case: Customer Service and Complaints Resolution

Artificial Intelligence in Retail

We’ve already seen just how much AI can add to customer service, but what about when customers aren’t satisfied? It turns out that the reach of Artificial Intelligence extends even here. Customer support automation can be used to address different queries from different customers at the same time, and provide answers while avoiding all-to-human mistakes.

Chatbots, for example, are one such technology helping to automate the customer service experience. Chatbots are used to create predetermined rules to help amend customer issues and complete desired actions. They can easily and effectively help customers with questions about their shipments, finding account data, canceling orders, and also adjusting orders.

Another, more futuristic, application of AI rescuing the customer journey is employed by Walmart. In-store, Walmart uses AI to detect the moods of customers during their shopping experience. Cameras are installed at checkout lanes to read facial expressions as well, and if a customer appears annoyed or distressed, a store representative will be alerted to go assist them. 

AI Is Here for Good

What all retailers need to take away from this exploration is that artificial intelligence isn’t just about Amazon drones. AI can be used in many, perhaps less flashy, ways to streamline your business with Dialpad conference call, customer journeys, and all of them offer exactly what retail needs: disruptive innovation. 

AI is transforming data into insight to create highly personalized experiences and simply smarter business practices. With so many different ways to use AI in retail, it’s no longer a matter of if you should be jumping on board, it a matter of asking yourself why you haven’t yet.

Jenna Bunnell

Bio: Jenna Bunnell

Jenna Bunnell is the Senior Manager for Content Marketing at Dialpad, Dialpad contact center software that provides valuable call details for business owners and sales representatives. She is driven and passionate about communicating a brand’s design sensibility and visualizing how content can be presented in creative and comprehensive ways. Check out her LinkedIn profile.

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