AI In The Real World: How Does It Drive Retail Success?

Key Takeaways:

1. AI is already transforming operations for retailers worldwide
2. Innovations are making impacts across customer experience, inventory, logistics and in-store 
3. Retailers are saving money, cutting delivery times and boosting customer satisfaction
4. Expertise is vital for strong implementation and adaptability for new technology

There’s a lot said about the benefits of AI in retail and how transformative it can be. But away from the headlines and bold claims, how does artificial intelligence benefit retail technology in practise?

The answers are many, from enhancing operational efficiency, inventory management and marketing, to revolutionizing customer service and personalized shopping experiences. All of these are vital at a time when nearly 60% of consumers expect higher-quality shopping experiences, and a majority are becoming interested in AI features.

This blog takes a look at some of the standout case studies on AI in retail, and how potential has translated into results.

How Did Retail Work Before AI?

It wasn’t so long ago that retail operations from stock-taking to marketing campaigns were still highly manual in nature. Technology would help make things happen, of course, but it relied on much more user input and oversight.

All too often, this led to a range of pain points and bottlenecks that could hold retailers back, including (and by no means limited to):

AI in Action: How It’s Changing Retail Today

All of those pinch points listed above are already being actively addressed by AI in retail. That includes improving customer service, making physical shopping smarter, rationalizing inventory and supply chain management, automating manual tasks for increased productivity, and providing data analysis and insights for faster, more informed decision-making.

This is thanks to a range of retail technology innovations such as:

• Conversational AI: AI-powered tools that work 24/7 and can deal with routine customer service inquiries and provide personalized product recommendations, streamlining the service process.
  
• Computer Vision Systems: detecting misplaced items, and monitoring shelf inventory levels in real-time to optimize inventory, cutting the need for time-consuming manual checks.
  
• Machine Learning Algorithms: analyzing customer data at vast scale and pace, to make accurate predictions on purchasing trends and preferences, so that inventory and marketing campaigns alike can be perfected.
  
• Natural Language Processing (NLP) Tools: scanning of customer reviews and social media sentiment to gain the latest information on consumer trends, helping to inform the development of future products.
  

Why Retailers Love AI

Given the range of retail technology that AI is powering, it’s easy to understand why the benefits of AI have become so compelling to retailers big and small.

Better Shopping Experiences

Every customer can get the VIP experience they want, with AI-powered personalization engines delivering tailored product suggestions and promotions, based on their previous shopping history and browsing behavior.

Smarter Inventory Management

The ability to accurately predict demand patterns through machine learning algorithms takes the guesswork out of optimizing stock and inventory, and minimizes both waste and unused shelf space.

Seamless Logistics

AI is used to optimize delivery routes and warehouse processes in real-time, speeding up delivery times for customers while cutting out unnecessary operational costs and delays.

Better In-Store Experiences

A combination of computer vision, and sensors connected to the Internet of Things (IoT), can make traditional stores smarter, more intuitive spaces. Shelves stay perfectly stocked, foot traffic patterns are monitored, and customers get fast, checkout-free experiences.

Leading Case Studies on AI in Retail

To demonstrate the full potential of AI in retail that has already been realized, we’ve picked out six of the best success stories from across the sector.

1. Levi Strauss: the fashion giant has applied AI in merchandise planning and inventory management at a global scale, integrated with its supply chain and enabling informed, coordinated decision-making.
   
2. Sport Clips: the US-based hairdressing franchise has transformed its talent acquisition process, with intelligent automation handling interview scheduling to free up valuable staff time.
   
3. Amazon: advanced algorithms and machine learning supports Amazon’s dynamic pricing mechanisms, analyzing huge amounts of data so that it can respond to market changes and adjust prices as often as every ten minutes.
   
4. Zara: the international fashion brand uses IT tools to automatically allocate certain levels of inventory to different stores, depending on predicted levels of demand and/or specific local trends.
   
5. Walmart: the grocery and retail giant has introduced AI-enabled voice shopping using the Siri Shortcuts tool, meaning users can add items to their cart, arrange deliveries and other functions by talking to their Walmart app.
   
6. Starbucks: the coffee brand added four million occasional users to its loyalty scheme in three months, by using AI to develop personalized offers that would appeal to them and make them more likely to join.
   

In Summary: What’s Next for AI in Retail?

AI and retail technology are both continuing to progress and develop at speed, and so it’s almost inevitable that there will be new innovations and possibilities coming on stream in the months and years ahead.

Robotics and sustainability are likely to be two key areas of focus. For example, in the case of the former, almost 60% of shoppers are now open to the idea of robots approaching them in-store to recommend products and take their measurements. As for sustainability, IoT devices and smart sensors are increasingly being used to monitor and optimize a huge range of parameters, including lighting, heating, cooling, footfall, store layout and more.

However, ensuring that the benefits of AI in retail can be maximized isn’t necessarily that simple. Some organizations have concerns around the cost of the technology (even though it’s estimated to unlock up to $390 billion in economic value for retailers), keeping customer data safe, and integrating AI with traditional systems.

The best way to avoid those headwinds is to work with a partner with proven expertise around AI in retail, such as Ciklum. We’re already working with brands like yours to develop and implement AI solutions that serve their needs, and we can do the same for you. 

Read one of our own retail success stories here, then take a look at our AI solutions in more detail.