5 Ways AI is Transforming the Retail Industry

Artificial intelligence is moving out of the research space and into the consumer market.

Once a topic reserved for scientists and engineers, AI technology has evolved into a powerful marketing tool that streamlines nearly every step of the buying process. With the invention of Google Home and Amazon Echo, a growing number of people are making AI a part of their daily life – and that includes shopping. From customer service management to innovative payment services, AI is reshaping retail, transforming it into a highly personalized and easily accessible experience.

This year’s PwC Global Consumer Insights Survey focused on AI and the future of retail, demonstrating the prevalence and popularity of AI in the global marketplace. According to data collected from over 22,000 consumers, nearly one in three said they were planning on purchasing a smart speaker, automated personal assistant or other AI device. Anand Rao, PwC’s Global Leader of Artificial Intelligence, believes this percentage will only grow as home devices become more technologically advanced, predicting an expanded number of capabilities “in the next three-to-five years.”

PwC notes that the majority of AI consumers qualify as early adopters. Most likely males between the ages of 18 and 34, the early AI adopter displays a few distinct characteristics:

• More likely to shop and pay for items on mobile devices
• More comfortable shopping online than in-person; less concerned with online security issues
• Majority (70 percent) purchase everyday items in bulk
• Less likely to search for price comparisons
• Majority (58 percent) feels positive about the economy and personal spending

One of the most intriguing insights about this demographic of buyers is their high standards when it comes to purchases. These young, tech-savvy individuals expect the entire buying cycle to be as fast and efficient as possible, with 25 percent assuming same-day delivery with every buy.

Now that we’ve provided a snapshot of the typical early AI adopter, let’s explore how AI is directly influencing the world of retail.

1. Faster Shipping and Delivery

We discussed how early adopters favor the quickest path to purchase possible and this character trait is directly impacting a key aspect of online retail: delivery. You may have already heard of Prime Air, Amazon’s fully autonomous drone delivery service that can drop off packages in 30 minutes or less. While the program has yet to officially launch, it highlights AI’s ability to satiate the public’s desire for speedier, more convenient delivery options. With 40 percent of consumers saying they would consider a drone as a plausible delivery method, buyers are clearly ready for a more high-tech alternative to standard shipping.

2. Convenient In-Store Assistance

AI has also started to find its way into stores with the introduction of retail service robots like LoweBot. Developed in 2016, LoweBot can be found in Lowe’s Stores across the San Francisco Bay Area. Using state-of-the-art technology, LoweBot is able to answer basic customer questions in multiple languages, which allows employees to give more attention to customers with more specialized inquiries. In addition to assisting with customer service, LoweBot can also monitor inventory in real-time, giving the retail brand important insight into purchase patterns. In early 2018, apparel retailer Zara activated in-store robots that assist customers who order items for in-store delivery. If an order is delivered to the store, the robot receives a notification, picks up the package and gives it to the customer. This new service is intended to streamline the in-store pickup process for faster, more effective customer service.

3. Inventory Management

Retail brands have incorporated AI to manage retail operations behind-the-scenes with solutions like Blue Yonder. Developed by data scientists specializing in retail and supply chain, Blue Yonder is a machine learning service that facilitates automated store replenishment. Through a feature called Demand Forecasting, Blue Yonder compiles a variety of information, including point of sale data, current promotions, upcoming holidays and even the weather, to forecast customer demand for millions of in-store items. The service then uses this forecast to provide recommended order quantities based on cost-benefit analysis. Demonstrating AI’s ability to automatically evolve and optimize based on customer purchase behavior, Blue Yonder is a great example of using machine learning to make smarter retail decisions for maximum profitability.

4. Personalized Shopping

In this day and age, shoppers demand highly personalized shopping experiences. Recent reports from Infosys show that 59 percent of customers are influenced by personalization. In addition, research compiled by Marketo indicates that 78 percent of consumers will only engage offers that have been customized based on previous purchases. In light of this information, more and more retail brands are turning to AI to provide customers with personalized shopping. North Face, for example, has partnered with Watson, IBM’s question-answering computer system, to help customers find the perfect jacket. Asking a series of specific questions like “Where and when will you be using this jacket?” and “What activity will you use this jacket for?” Watson is able to pinpoint exactly what the customer is looking for based on his or her specific needs. With personal shopping AI services, like Watson, brands are able to give customers what they want: a more relevant, convenient, and gratifying shopping experience.

5. Better CRM

One space that has been heavily influenced by AI capability is customer relationship management. Today, machine learning is fast becoming the norm for CRM service providers, as it brings a new level of efficiency to customer monitoring and communication. Conversica is a virtual customer service representative that engages customers with human-like interactions. Boasting a 35 percent engagement rate, Conversica automatically responds to every online lead and continues the conversation through personalized emails. Once a customer expresses interest in making a purchase, Conversica will seamlessly hand off the lead to a human employee who can close the sale. To make CRM even easier, Conversica instantly ranks leads based on likelihood of conversion, compiles new leads and lists at-risk leads on a user-friendly online dashboard.

From internal operations, like inventory management, to marketing and customer service, AI has the ability to enhance every aspect of the retail buying cycle. With so much to offer retailer, it’s no surprise that a growing number of big-name brands are looking to AI to maximize ROI. Find more insight on the latest retail marketing trends or read our marketing blog here.