Do we still need humans to power customer experiences? Yes, according to Forrester.
In its Digital CX Trends 2018 report (fee charged) released today, Forrester researchers found that "while AI, intelligent agents, and chatbots were central to the business conversation in 2017, most companies discovered they lack the design acumen and technical chops to seize the opportunities." This, researchers found, has led to widespread struggles with the basics and few leaders "innovating the way forward." It's fair to say not everyone is excited about artificial intelligence's invasion into customer experience, even those who profit from it.
AI Helps CX, With Some Caveats
Yet many organizations are still turning to AI to power customer experiences. Machine learning helps companies do a better job of making recommendations for customers, according to Peter Norvig, director of research at Google and former head of computational sciences at NASA. Norvig said this during a 2017 interview with Nick Johnson, corporate marketing director at Salesforce. “The customer doesn’t really notice that AI plays a role,” Norvig said. “They simply see their results getting incrementally better. This behind-the-scenes use of AI as an optimization tool for existing processes is an area where we’ve already made a lot of progress, and where the technology is pretty mature.”
At the same time, Norvig cautioned it’s difficult to prepare for unforeseen problems that arise from deploying AI and to “guard against big mistakes.” “It's easy to say,” he added, “‘We increased click-through rate by 10 percent by using AI to power our recommendations.’ It's hard to answer with certainty, ‘Is there going be a one-in-a-million mistake that gets us on the front page of The New York Times?’ Those types of things are hard to predict because they just don't happen very often.”
Organizations are certainly experimenting with where AI fits best in the customer experiences. We’ve discovered some ways companies in different industries are implementing AI into their customer experience programs.
Related Article: The Future of Customer Experience Is AI: Are You Ready?
Chatbots Power Automotive Experiences
Ever pencil in “chat with a car salesman” on your bucket list? Neither have we. Chatbots, however, are beginning to enter the equation when shopping for a new car, to provide consumers with more definitive goals and desires before their arrival to dealerships. No need for the slick pitches from the car salesmen.
Detroit-based Feldman Automotive Group deployed one such chatbot. Powered by chatbot provider Valassis, the chatbot combines AI and natural language processing (NLP) to help create leads, increase consumer engagement, dealership traffic and sales. It targets prospects in a geographic radius of several Feldman brick-and-mortar dealership locations with an advertisement integration through Facebook’s Newsfeed. The chatbot can then strike up direct-message conversations with prospects in Facebook Messenger. Online assistance for customers is also available through the chatbot.
MetLife Targets Better Claim Experience
MetLife has infused AI into its analysis of the health insurance claims process. The goal is to train agents to have better, more informed conversations with customers — and get things done for callers faster. MetLife uses its AI engines to analyze calls in real-time while delivering messages to associates about the way they can improve the call. Supervisors also gain insight into live calls to help manage outcomes.
MetLife started with a pilot at a claims center that handles short-term disability and total absence management professionals. It analyzed 60,000 claims from 250 agents. The AI assistant (powered by Cogito) showed through a popup the associate had “extended overlap,” which meant he too often talked over the customer. It interrupted the agent shorty after that with a message that said, “Continuous speaking. Finish your thought. Ask an open-ended question.” And then later, “Extended silence. Check in. Let the customer know you are still there.”
Delta: Facial Recognition for Bag Claims
In 2017, Delta Airlines introduced four self-service bag drop machines at Minneapolis-St. Paul International Airport. One of those machines uses facial recognition technology to match customers with their passport photos through identification verification. Delta officials said the move was to help speed up the process of bag check-in. Travelers use kiosks to print bag tags, then use the self-service bag drop machines to scan their boarding pass and weigh their bags, which the kiosk registers in the system.
Delta's not immune to the risk of AI, though. The airline announced last month its online chat service provider, 7.ai, had been involved in a cyber incident. Certain customer payment information for 7.ai clients, including Delta, may have been accessed as a result of the event, the airline reported.
Related Article: 3 Tips to Avoid the Embarassment of AI's Unintended Consequences
Domino's Messenger Bot Changes Ordering Experience
Ask a good question and you'll get a good answer. According to Domino’s Pizza officials, one of the most common questions customers used to ask on Facebook is “What deal can I get on my pizza today?” That's how the Messenger bot was born.
Domino's Pizza allows customers to order pies through Facebook Messenger using only one word — 'pizza' — or the pizza emoji. Domino's updated the bot after its initial roll out to allow customers to place an entire order. And Dominos isn’t the only one in the food industry introducing bots into the ordering experience.
Finding the Perfect Gift with GWYN
GWYN (Gifts When You Need), IBM Watson's "gift concierge," integrates with 1-800-Flowers to help customers find the right gift. The AI engine learns how customers interact online and adjusts to know what best to serve them, according to IBM officials. Shoppers can chat with GWYN during their shopping experience to share information about who they are shopping for and for what occasion and in return, get personalized recommendations. GWYN uses natural language to help clarify questions and share tailored recommendations.