By John Rampton
It seems hard to imagine that a machine could provide a better experience than a human could for another human. This is especially the case when one of the biggest customer complaints is the lack of personal interaction and care. However, there are other issues that impact a customer experience as well, including response time.
While it’s easy to jump to the conclusion that robots are going to take over every human job, that’s not the case and it’s not how they could be used in the most effective manner. Instead, it’s better to view bots or any other type of artificial intelligence solution as a partner in the overall customer experience, taking on certain aspects of it so us humans can do a better job where we are most needed.
Not every customer out there wants to talk to another human being in order to be satisfied. In fact, some view a great customer experience as one where they can just take care of what they wanted with little or no interaction. This is especially the case if they are on a website and just want to find an answer to a quick question they had rather than calling someone.
Enter AI that could make that customer satisfied by answering their basic question for them so they can complete what they were looking to do. While still limited tools such as Amazon’s Alexis are proving that AI is rapidly improving. Machine learning is accelerating and bots are becoming better at natural language and decision making that emulates human communication and thinking.
This has made artificial intelligence a useful addition to certain social and digital platforms where they are filling in for human beings to handle some of the most basic customer service needs where the main criteria of a good customer experience is based on response time.
Personalized Interaction and Pattern Identification
With every interaction a bot has, the more it understands the type of interaction and responses that are positive for the customer, helping them improve over time without the need for actual training. Additionally, while handling these aspects of the customer experience for a company, it also continues to gather data that can be culled later on for insights that help to achieve further personalization and customization in the future.
Another interesting offshoot of using AI that could improve the customer experience is to take customer attributes, including their demographics, product preference, and purchase history, and customer service agent attributes to determine who could serve the customer in the most effective way, essentially matching up agents or reps with customer types. This ability to “match-make” customers and customer service representatives could also enhance the overall experience due to the “chemistry” produced.
Other patterns could be identified through the use of AI that tracks customer satisfaction rates, up-sales, cross-sales, payments, and more. It could also be used to generate feedback on a representative’s performance in real-time to quickly correct any behavior that adversely impacts the customer experience.
These patterns could also be tracked by the AI mechanism to understand customer patterns in terms of when and why they contact a company so that they can provide an answer for this customer even before they initiate contact via email or text message, delighting the customer with the depth of personalized service.
That frees up humans to focus more intently on every other customer experience where they are expected to be included and respond to their audience. Plus, the information that the bot gathers helps every human do a better job at meeting customer expectations. With all the other devices like Siri already in use, most people are already becoming accustomed to working with AI to some degree. This sets the stage for an increased use of AI in more customer experience applications.
Accelerating AI Integration Into the Customer Experience
The more data an AI-enabled device collects, the more it can learn – and at a faster rate. This process can be sped along by providing historical chat logs and email messages to the bot. The existing data can help the bot understand the typical issues and concerns of customers that contact the company.
Over time, more interaction with customers can help the bot sense the tone of customers and pick up on what is most important to each customer in order to reference that and enhance that experience. This can help ensure that the AI you employ exhibits the human emotions and emotional intelligence quotient that makes each customer feel the personal interaction that is so important to them.
Lastly, don’t always think that the customer experience is just when the customer comes into the mix. If anything, the customer experience includes everything that came before that moment and actually involves every department in your company.
Think about where AI could be inserted elsewhere in your organization to incrementally enhance that experience from the very beginning so that some issues that might have come later never have to happen at all. That includes sending data collected back through the chain of events all the way back to product development to create better products that later on deliver that improved customer experience.
Jay Baer once said: “The delivery of great customer experience is rooted in one easy to understand (but difficult to execute) formula: Great customer experience happens when you exceed customer expectations.”
Sounds simple, right? Well it can be. Download Customer Experience Simplified to learn more.