With the continued dominance of artificial intelligence in business applications, we’ve started to see a dramatic shift in how people shop for and purchase products. At least 60% of the U.S. population have made mobile purchases; 82% of mobile phone users use their devices while in-store to help them make a product decision.
As mobile commerce continues to grow, retail stores will need to adopt new technologies to stay afloat. Consumer reliance on smart devices will only become greater, so brick-and-mortar stores must act quickly if they don’t want to become outdated.
This is why many stores are adding an AI solution to their business operations. With the help of AI, retailers can boost employee productivity, add value to the customer experience, and generate increased revenue over time.
Ways AI Can Help Retailers
1. Enhanced In-Store Experience
Perhaps one of the biggest reasons mobile commerce has become so popular is its sheer convenience. Customers like the ability to quickly look up an item, add it to their cart, and make a purchase with no interruptions—all within the comfort of their homes.
Now, when a shopper visits a brick-and-mortar store, they seek a more valuable experience. Consumers go in-person to explore, try out, and observe the product they’re interested in buying. This puts more pressure on retailers to find ways to reach their customers and compel them to make a purchase.
Using AI solutions can help bridge the gap between the convenience of e-commerce and the experience of physical in-store shopping. For example, customers can receive better product suggestions, immediate virtual assistance, and more convenient in-person shopping with an expedited cashier-less payment process. With repetition, this solution can increase footfalls and keep shoppers coming back for more.
2. Better Supply-Chain Management
AI solutions can help retail merchants with inventory planning. For example, Shopic, a grocery smart cart technology company, has developed an AI-powered device that can be attached to any standard shopping cart, turning it into a smart cart.
“By identifying the items that go into your cart, the system collects anonymized data that the grocer can use to improve their store,” explains Shopic CEO Raz Golan. “For example, this makes it easier for stores to track inventory levels so they can restock popular items before they run out. This type of tracking can also help them improve the store layout to make it easier to navigate. All of this can be done without giving up any personal information, allowing your preferred store to become even better with time.”
3. Refined Consumer Journey
As we’ve already said, physical storefronts serve a new purpose for modern consumers. They aren’t just places people go to buy a product, but places where people come to gather information, connect with a brand or company, touch and smell products, compare shopping experiences, and spend time. McKinsey conveniently coins this experience as the “consumer decision journey.”
The consumer decision journey isn’t a straight line—it’s a zigzag tour from research to purchase. Using AI, retailers can utilize variable data to measure engagement statistics, like how much time a customer spends on a certain page, which pages are receiving the most clicks, which products are getting the most attention, and so on.
Retailers then can use this information to implement management solutions like optimized in-store layouts and product displays that make use of foot traffic patterns and trending product categories.
4. Dynamic Pricing
Now more than ever, consumers have greater price sensitivity, and retailers are forced to be more thoughtful in their pricing decisions. Of course, covering expenses and reaching a profit are critical pricing criteria for a business to grow.
But when a product is either overpriced or underpriced, retailers risk stirring a consumer outrage. So how do they determine the right price for their products? Do they set static prices? Should they mimic those of their competitors? Or should they use a combination of both?
The answer lies in using AI solutions and data-driven tools to create dynamic price-setting strategies. Through surveys, social media, and other interactive outlets, companies can utilize the data to adjust their pricing in real-time.
By using advanced data-driven tools, businesses can analyze the success rate of various pricing models before identifying the best price for their products. Then, as seasonal trends come and go, competition arises, and market demand shifts, retailers can adjust prices accordingly while maximizing their opportunities to increase their revenue.
5. Personalization and Consumer Insights
Just as shoppers yearn for a more valuable shopping experience, they also seek personalization when they shop. As technologies like biometrics and facial recognition become the preferred method for identification, retailers can use this function to identify customers who revisit their store and to remember their liked purchases as well as their dislikes. Advanced AI algorithms can design personalized promotions and recommend products customers might enjoy.
For a more immersive personalization, retail companies can use AI to look into consumers’ demographic data, social media impressions, and digital footprints to determine their shopping preferences and interests. Not only does this create a more valuable, personalized shopping experience for the consumer, but it also provides valuable consumer insights for retailers.
AI Solutions Help a Retail Business Grow
According to a Boston Consulting Group study, companies that integrated advanced digital technologies and data to design personalized experiences for customers saw an increase in revenue by 6 to 10%—and they saw this increase two to three times faster than the companies that didn’t.
While AI is still a very new and emerging technology, businesses across all industries are making it a part of their business applications, and retailers can benefit, too. If retail companies want to truly thrive, the best way forward is to embrace AI solutions.
This article was written by Nathan Resnick for AllBusiness from Forbes and was legally licensed through the Industry Dive Content Marketplace. Please direct all licensing questions to legal@industrydive.com.
