I was arguing with a bot recently. I was asking what I thought was a straight-forward question. Using the helpful ask us tool on my bank’s site, I typed in a simple question: “I don’t recognize what this 'service adjustment' fee is all about on my statement. Can you please tell me what that is?”
The bot wanted to tell me about their great interest rates.
I explained to my new artificial friend that I had a business checking account and needed to understand a fee on my statement.
“I can help you with that!” The bot proclaimed.
After verifying my identity and account information, I was again directed to the wonderful interest rates available for personal savings accounts.
I tried typing in what I thought might be trigger words like “agent” or “help” and after about 8 minutes of frustrating activity (OK I timed it: it was exactly 8.23 minutes) I was redirected to a service representative.
Another delay, and then Megan-The-Real-Person introduced herself in the same chat box.
And guess what I had to do all over again?
Verify everything. Repeat my question. Wait. And wait some more.
Where was Megan? Did she give up on me? What she conferring with the bot?
Megan would occasionally type “yes, I’m still here. Thanks for your patience.” This would be her reply after I would type in the frustrated, “Are you still there?” after minutes of nothing.
Megan was now making me wait well beyond the original 8 minutes and I couldn’t understand why this was so difficult. Was Megan actually a bot, too? Hard to say.
Finally, I realized I was wasting my time with both the bots and potential human, so I picked up the phone and dialed the bank's number.
After verifying, again, and asking, again, the agent explained in simple terms that this was indeed a mistake on my statement. She’d make sure the fee was refunded and thanked me for my business.
What should have been an easy answer turned into an episode of frustration. And effort. Too much effort for me as the customer to get a simple question answered.
Artificial intelligence (AI) is a promise of providing faster, more personalized experiences for customers, especially when combined with humans still serving customers. And it also offers organizations ways to scale tasks that are difficult to scale today. All while leveraging technology and machine learning (ML) to provide high-touch, human experiences via automated tools.
The story I shared is a small glimpse into how artificial intelligence (AI) and machine learning (ML) can be fantastic in theory, but maybe not as fantastic in real life.
However, what if AI and ML could deliver on the ideal of a better customer experience? What role do we, the humans, need to play to ensure our AI solutions are helpful to our customers?
What is artificial intelligence?
AI is a term used to address the ways technology, automation and machine learning will provide help, solutions and reactions to humans in more human ways.
AI is used to help your smart speaker get to know your preferences and answer your voice commands. AI is also used to help you book airline tickets, transfer money to bank accounts, and more. The last time you saw “people like you have also enjoyed these products” on an ecommerce site, or even your local library app, you have AI to thank for that.
The rush to use AI is an exciting glimpse into what we were promised for our future with smart machines who feel like friends and serve our needs in real-time. But the tools, like any other tool, cannot stand on their own. They need to fit into the overall strategy and structure of your organization.
The best way to leverage AI for your customer experience is to understand what it requires first, then plan and execute and evolve for the needs of your customers and your brand. Here are a few guidelines for those anxious to let the robots take over!
Strategize, don't execute
Know your (company) why
AI is a tool. Make it part of your business strategy.
Deploying an army of bots because the technology is there is not a strategy. Your overall business strategy should guide how AI is leveraged in your customer experience.
How does your organization measure success? Start there. Review your overall goals, your key performance indicators, your customer experience metrics, all of it.
Ask yourself what outcomes you need. If scaling service is a goal, define what that would look like in an ideal world. For example, the hospitality industry has leverage chatbots to answer questions for front-desk staff that are easy to answer and provide the humans in service to be free to address more pressing issues for guests. The bot is super capable of answering the repetitive questions like “where can I find pool towels?” and “what time is checkout?’ Defining these questions in advance means creating solutions that can start with some basic knowledge and helpful outcomes for customers.
Know their (customers) why
Customers are becoming more and more comfortable with AI. Why? Because they see what is in it for them. Define what your customers will gain from your organization’s use of AI. Then share that with them.
Customers shouldn’t have to guess at who they’re dealing with or why. Explain upfront what these new ways of working will do for your customers. Offer words of advice or suggestions on how best to deal with chatbots or virtual agents.
Customers want personalized, efficient and convenient communications. They are typically happy to interact with virtual agents or others to gain the outcomes they’re looking for.
Artificial intelligence requires customer buy-in, too. Data integration is key to driving the right outcomes, so keeping customers aware of how their data is used to provide more personalized and meaningful experiences for them must be part of the overall strategy.
What else can AI offer your customers? What happens when it can’t deliver?
Faster service is certainly a successful outcome for many customers. But AI has the potential to provide more convenient hours of service and real-time responses, regardless of time zones or those pesky sleep schedules of human beings.
But there are times AI can’t deliver, just like how the bot from my bank couldn’t quite get to the answer I was seeking. So it’s important to offer transparency about what is possible when the AI experience can’t deliver for customers. If there are specific customer service hours for human agents, address that even when delivering service via bots.
Customers want you to know them and serve up the experience best suited for them. AI allows this type of personalization. But sometimes there are recommendations that are all wrong.
Music streaming services allow subscribers to reject certain songs not only one time, but with a declaration of “I don’t like this song.” This information helps refine future recommendations for the user.
What is the option of “I don’t like this” in your AI playlist? Giving customers control to reject the assumed preferences defined by AI helps the machines learn and keeps the customer in control. Providing an “out” to personalization at this detailed level is a great way for machines and humans to cooperate and learn the nuances of the relationship.
Plan to evolve
Customer experiences don’t remain stagnant over time. Don’t expect your artificial intelligence strategy to either.
Leverage what feedback mechanisms you already have with customers. Provide in-moment ways for customers to let you know if this AI-supported customer journey is working for them.
Then, be honest. There might be some hard truths from that feedback. When customers tell you the chatbot is wasting their time or the personalization feels anything but personal, listen to them. Something isn’t working and it might be your smart solution.
Challenges of AI leadership
Incorporating AI into your customer’s experience might not be seamless. The organizations achieving the most success with AI now are addressing these challenges in similar ways as overall customer experience strategy and design.
1. Data data data
Data integration and centralization are critical to well-executed AI performance. This is a huge challenge for many organizations today, so now is the time to look under the hood and make sure your customer data is where it needs to be.
Siloed experiences lead to disjointed journeys for customers and employees. It’s difficult for machine learning to get smarter if only part of the customer journey is tapped into.
Furthermore, a universal understanding of what data, how to use it, where it’s kept and how to govern its usage are absolutely imperative to the ethics of using customer data.
2. Siloed leadership
You get a bot! And you get a bot! Everybody gets a bot!
If your teams are working independently on AI initiatives, just like any customer experience strategy, your customer experience will suffer.
If one area of your organization, like ecommerce, has developed and executed great personalization strategies for shoppers, those customers will expect the same personalization when requesting help on the store app, for example. If those teams are leading separately and not communicating, the customer suffers.
Get your cross-functional team together to address the whole customer journey and how AI can support that, not the other way around.
3. Culture, training and employee engagement
Many employees today are asked to use new technology and leverage the AI tools available without the proper communication, training and ways to provide feedback. These employees are vital to the success of the adoption of AI, so create a rollout strategy along with training and communication plans.
Watch for subtle messages employees might hear differently than they were intended. These tools are not there to replace every customer service agent, for example. They are provided to make those agents jobs easier and more efficient. Don’t let the idea of "robots taking over" torpedo your service strategy before it really starts!
Another note here–be sure you celebrate your successes as you rollout these new tools and technologies. Share the wins throughout the organization and tie those back to the customer feedback and customer experience metrics reflecting those wins. Help everyone see their role in serving customers and how your overall business outcomes reflect working together.
It’s fair to say artificial intelligence (AI) is here to stay and will have an impact on customer experiences in ways both small and large. Your organization can take advantage of the unique wins provided by scalable service and more personalized experiences for both employees and customers.
But, like most things, these strategies still require a human touch. Get your organization ready to succeed by leading with strategy and delivering with and for humans. The technology is there to learn from you!
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About the guest author
Jeannie Walters, CCXP, CEO, Experience Investigators™ by 360Connext
Jeannie Walters is a Certified Customer Experience Professional (CCXP) and is CEO of Experience Investigators. She is a customer experience speaker, writer, and consultant with more than 20 years of experience in assisting all types of companies, including Fortune 500. Specialties include in-depth customer experience evaluations, customer journey mapping, user experience analysis, and leading workshops and training programs. Her mission is: To Create Fewer Ruined Days for Customers.™ Connect with her: experienceinvestigators.com | @jeanniecw