As we speak, more and more brick-and-mortar retailers around the world are faced with dropping sales that force them to close their stores or move a good chunk of their business online. What’s more, they find themselves competing with those online retailers who decide to expand their reach to physical sales.
The message is clear: traditional approaches to retail are becoming obsolete in the wake of technological progress. To stay afloat, industry players must keep pace with the ways technology changes customer habits and learn to anticipate demand. Artificial intelligence has emerged as the key technology for the task due to its ability to process unstructured data and facilitate automation at the scale required by each individual business.
According to a recent IBM report on the coming AI revolution in retail and consumer products, forward-thinking brands have already picked up on the importance of AI-driven solutions as a competitive advantage.
Source: IBM Institute for Business Value
With numbers like these it becomes obvious that in a few year’s time, artificial intelligence in retail industry will become a game-changer for businesses who don’t want to go by the wayside.
How artificial intelligence is used in retail
So what unique capabilities can AI offer to retailers who are struggling with keeping their sales up? And how does it all work?
AI systems need plenty of data to learn and improve. In retail it means analyzing anything from supply chain statistics to sales data to customer behavior data. Starting with historical data and moving on to real-time insights allows the system to create a more accurate model capable of generating reliable predictions and give actionable strategy recommendations.
Let’s examine what role AI can play at various stages of the typical retail workflow.
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Warehouse management and supply chain planning
Before any product can reach a regular shopper, it arrives at the warehouse. The bigger the business, the more complicated warehousing gets, especially if we are talking perishable goods.
This is why efficient warehouse management is so important for saving time and money. AI is well-positioned to help retailers run warehouses better by eliminating human error and automating the majority of repetitive tasks.
Large retailers are already experimenting with using AI to design the layout of warehouses and pick optimal building sites that minimize delivery times and related fuel consumption. AI is applied in combination with IoT to closely monitor warehouse conditions and protect quality where vulnerable merchandise is involved. AI inventory solutions help keep the inventory counts pristine and 100% transparent, resulting in a streamlined shipping process and simplifying accounting.
Beyond the walls of the warehouse, the entire supply chain can use the insights supplied by AI on the basis of historical data. The system sifts through previous instances of overstocking or understocking and analyzes the reasons for spikes and dips in demand to forecast future fluctuations. This information is then incorporated into supply chain adjustments. As a result, the retailer can better match supply to demand and no customer is left disappointed.
Smart product placement
People tend to buy certain products together, and recognizing these patterns can give a retailer a better idea of how to arrange goods on their shelves and the shelves in relation to each other.
This kind of analysis is especially impactful when the system gets real-time, venue-specific data. Besides improving the customer’s in-store experiences, smart product placement is a great way to stimulate sales.
The analysis of purchasing patterns can even affect manufacturing, especially for fashion retailers who rely on feedback from the stores as they start working on their next collection.
One of the world’s biggest fast fashion brands H&M is using AI in retail to tailor in-store assortments.
Even when the product is well-arranged, new problems can emerge such as items selling out or prices being mixed up. Walmart uses AI-assisted robots to scan shelves and proactively track pricing, sell-by dates, and the number of available items. By automating this tedious task, the company is able to get faster results, reduce operational costs, and give human employees more time to interact with customers face-to-face.
Bossa Nova robots working store aisles at Walmart
Competition analysis and price optimization
Multi-brand retailers invest into AI and image recognition solutions with the purpose of better understanding how competing brands perform against each other. This information drives decision-making, as any retailer would rather expand their inventory with the brands that are more likely to benefit their bottom line.
Brand performance also informs in-store pricing. When the retailer is able to predict how much customers will be willing to pay for a particular item, they can adjust pricing strategies and enrich them with loyalty points, promotional offers, and discounts.
Digital fitting rooms
The fitting room experience is the be-all and end-all of fashion retail. The less hassle customers go through while trying on new clothes, the more they are likely to buy.
To encourage customers to try on more items and facilitate decision-making, retail companies started implementing cutting-edge fitting room solutions. Equipped with computer vision, digital touch-based mirrors can recognize clothes items by code and notify shop assistants when another size or color is required. Customers also receive suggestions about items that go well together and tips on improving their style with makeup and accessories.
Smart fitting rooms powered by AI in retail
The same technology can be adjusted to serve online customers and personalize virtual fitting rooms.
Advanced store security
One of the powerful aspects of AI is the ability of a trained system to recognize anomalies in video footage and instantly flag suspicious behavior. This creates an opportunity for large retail companies to automate and scale security across multiple chain stores that run a high risk of shoplifting or robbery.
AI security solutions employ face detection, object recognition, and deep video analytics to simultaneously monitor every visitor. As soon as suspicious actions are detected, a human operator receives an alert and reviews the footage in question. With man and machine working together, action can be taken sooner and false positives are eliminated.
Customer engagement and support
Engaging customers from the moment they enter the store is a great way to ensure they won’t leave it empty-handed. More and more retailers opt for next-generation engagement solutions based on AI to approach customers with personalized offers. When you save a busy customer the hassle of looking for the exact item they want at a good price, they feel appreciated — and feel compelled to praise your service to their friends and family.
With long-term customers, historical data is the key to predicting demand. With first-timers, the task is more tricky, but experimental technology is already available that empowers retailers to collect data on them in-store and in real time. Pepper, a robotic shopping assistant, uses emotion recognition and data analytics to hold meaningful conversations with store visitors, transform customer journeys, and stimulate purchase.
“Phygital” experience enabled by machine learning in retail
How a retailer treats customers after the purchase is complete also reflects strongly on their image. Solutions like Conversica harness artificial intelligence to deliver a personalized touch to every customer who contacts support with a query, even as they process thousands of them in a day. Fast and comprehensive responses improve customer satisfaction, while reduced operational costs boost the bottomline for the business.
As the IBM report states, the use of AI in retail and consumer products industries is expected to rise from 40 percent of companies today to more than 80 percent in the next three years.
More than any other technology, artificial intelligence in retail is propelling digital transformation through relatively cheap automation of time- and labor-consuming activities. The result is improved operational agility and a purchasing experience that is more tailored and more personalized than ever before.
The question, then, is not which retail businesses will be betting on AI to increase their sales, but rather, which businesses will be able to apply it most effectively.