Few things can make or break a company’s reputation like customer experience. Companies build lasting loyalty if they can anticipate their customers’ needs and make interactions friction-free. And if consumers can’t get their questions answered or their problems solved, they’re all too ready to walk away.
Pace-setting companies increasingly are turning to advanced technologies like artificial intelligence (AI) to deliver top-notch customer experiences. Starbucks uses AI to learn the preferences of its customers and recommend food and beverages. Australia’s Qantas Airways personalizes the flight experience by recommending the most efficient way to check in, when to leave for the airport, and the best route to take.
AI helps businesses do a better job at something they’ve tried to do for decades: know their customers. “When you have a good experience with someone, why is it good?” says Seth Earley, author of The AI-Powered Enterprise. “Because they know who you are, they know what you need, they know something about your preferences, they know your situation, they know how to solve your problem.”
RelatedThe age of experience
Today’s consumers want sites and apps to recognize them and deliver what they need—and to do it quickly. A Deloitte survey last year bears this out: The majority of 11,500 global consumers said “timely offers” and “knowledgeable customer service” are among the most important considerations when it comes to making a purchase decision.
Here are three ways that companies can capture the value of improved customer experiences with AI.
Build a strong foundation of data
Data is at the heart of AI customer experience, but for machine learning to be effective, that information must be organized in a consistent way. This “information architecture” (IA) is the foundation on which all AI applications are built.
It’s really about understanding the consumer beyond a demographic.
“Agreed-upon terminology, agreed-upon concepts—that’s really the foundation of all of this,” says Earley, whose mantra is: There’s no AI without IA.
For example, an insurance company will have multiple products, a variety of coverage types, different geographical regions, and groups of customers with similar needs. Before AI can make sense of all this, the information must be based on coherent concepts and described the same way everywhere it’s stored. If the quality of the data is poor—if auto coverage is described as a “policy” in some places and as a “product” in others, for example—an insurer won’t realize the full potential of its AI tools and the customer likely won’t benefit, either.
To ensure that AI works well, companies need to improve their data management, keep information up to date, and make sure definitions are consistent. “You can’t automate a mess,” says Earley. “You can’t automate what you don’t understand.”
Make personalization a central feature
From travel to entertainment, home improvement to banking, companies are realizing how crucial it is to personalize the online experience.
Starbucks, for instance, is able to draw an increasingly detailed picture of its customers with every order placed through its mobile app. Then, with AI, it can deliver offers unique to every customer. It’s a strategy that helped Starbucks generate 52% of its total sales in 2021 from its app.
“It’s really about understanding the consumer beyond a demographic,” says Leala Crawford, who heads Deloitte’s data science analytics and personalization team.
Early data analytics generally provided a one-dimensional view of the consumer, such as age or gender, Crawford says. AI, in contrast, can capture and analyze a wider range of data, and use it to recommend actions based on a fuller picture of the customer. One Deloitte client, a global travel and hospitality company, uses AI to assist service agents helping customers complete their bookings. The data gathered during that interaction—such as travel itinerary or planned outings—is then passed on to the service agents who can then recommend alternative vacation packages.
The payoff for companies is quantifiable, Crawford says. Deloitte research shows that companies who accurately anticipate customer needs generally see 40% improvement in loyalty, retention, and revenue.
In the insurance industry, processing claims can be a drawn-out and maddening process. AI chatbots and conversational tools can improve the claims experience for both policyholders and adjusters. Not surprisingly, insurance companies have been at the forefront of chatbot adoption.
With AI, a chatbot can cross-reference claims, check for possible fraud, and process a payment within minutes. It also makes it easier to purchase insurance. For instance, someone pricing life insurance online can enter the relevant data—their birthday, whether they smoke or have a family history of health problems—and the AI system instantly evaluates risk and provides a quote, satisfying customers’ need for speed.
“For customers, knowing the ballpark of how much insurance is going to cost is going to help you think concretely about how much coverage you can afford,” says Laura McKiernan Boylan, head of underwriting solutions at Haven Technologies, a subsidiary of MassMutual.
Other industries also are successfully using AI-chatbots to streamline customer workflows. Banks are reducing case volumes and response times, while large telecom companies are cutting down on “status requests” by using conversational AI to let customers know about interruptions in service.
AI-powered conversational tools let customer-service representatives focus more on what they do best. “That customer service representative is able to do relationship-building,” says Nicole Chiala, senior manager at ServiceNow’s Workflow Design Studio. “That’s what people do really well, and machines can help us with the other pieces.”