Unveiling the future of AI in Customer Experience

In this article, CX Thought Leader Colin Shaw discusses the transformative potential of AI in improving customer experience, emphasizing the importance of training AI correctly to understand customer behavior. It highlights common mistakes, such as ignoring the subtleties of subconscious and emotional customer experiences, and stresses the need to incorporate behavioral science into AI training. Shaw suggests that organizations should focus on understanding the emotional and subconscious aspects of customer experience to fully leverage AI for proactive and personalized interactions, ultimately enhancing satisfaction and loyalty. 

 
We all know that when implemented correctly, AI will provide a massive opportunity to improve the customer experience. However, we are always doomed to repeat the mistakes of the past, and nowhere is this more true than in the implementation of generative AI. Let me explain before I discuss the opportunities AI creates.

We all know the old adage ‘garbage in, garbage out,’ but many organizations seem to ignore it. We all know AI is a sophisticated pattern recognition system. As such, it can understand the patterns of customers' behavior and predict what they will do next. This is if, and only if, it has been trained correctly. Generative AI is only as good as the information it is trained upon. It is also only as good as the people who interpret the information it provides, and they use this to design a new customer experience based on its findings. 

The challenge is organizations don’t know what they don’t know. Too many organizations think that Customer experience is just a rational process. It is not. There are four aspects of Customer Experience and how customers make decisions.   

1. The rational: This is what the customer does: their actions, what they buy, where, when, why, and how.
2. The emotion: How their experience makes them feel. This is the specific emotion they feel. Importantly, they do not just bucket emotions into general positive or negative emotions. 
3. The subconscious: This is the subconscious message they are receiving from the company. For example, a voice system that says, ‘Your call is important to us,’ and then the company keeps people waiting for 30 minutes. The subconscious experience reveals the company's true nature; it shows that the customers are not as important; the customer receives this subconscious message by what they do not what they say.  
4. Behavioral science: This means understanding human behavior. It embraces the fact that people/customers are not logical and do not always make rational decisions. The key here is that there is a big difference between what customers say and what they do. For example, Disney knows when they ask customers what they want to eat at a theme park; customers typically say they'd like to have the option of a salad. But Disney also knows people don't buy salads at theme parks. They buy hot dogs and hamburgers. There is a big difference between what Customer say and what Customers do. You need to understand how customers make decisions.

“In my experience, most organizations only train AI on rational experience; a few include emotions if they have the data. Very few train them on the subtleties of the sub-conscious experience and behavioral science” – Colin Shaw

This is a big mistake when trying to elevate a customer's experience.   

To explain why, let me tell you about one of my favorite comedy books converted into a film: The Hitchhiker's Guide to the Galaxy. 

In the book, people on a planet were trying to answer the ultimate question: What is the answer to life, the universe, and everything? So, they built a massive computer called ‘Deep Thought’ to answer this question. Deep Thought starts addressing the problem. 7.5 million years later, the great day comes when it reveals its answer! Everyone gathers in anticipation. In a fanfare of excitement, Deep Thought informs everyone that the answer to life, the universe, and everything is 42! 

As you can imagine, there was confusion, and nobody understood what it meant. Their mistake was not understanding the context of the answer. 

The same applies to AI. AI will identify patterns of customer behavior, but the organization will not understand the answer if it doesn’t know what the subconscious experience is or how and why people behave and make decisions that are not always logical but emotional. This is the whole area of behavior science.  

On top of this, they are not certain of the experience they are trying to deliver, and they don't understand the four aspects of a customer experience. Therefore, when their AI gives the answer of 42, they don't understand!  

So, what is the solution? 

Firstly, your teams need to understand the three aspects of customer experience: what a subconscious experience is, how people behave, and how they make decisions. This means an understanding of behavioral science. 

Secondly, you need to train your AI based on these. Therefore, you need to train it using data on customer emotions and the principles of behavior science. If you do this, the opportunity is massive.  

“I firmly believe the next competitive battleground is moving from a reactive experience to a proactive experience, and generative AI will take a lead role in this.” – Colin Shaw 

AI will predict what the customer does next as it has gathered all the information from across the organization's various silos. With that knowledge of what the customer will do next, they will enable AI to provide a proactively automatic experience to the customer.

Here are four examples of how AI will be able to provide a proactive experience:  

1. Predictive Personalization: It could automatically suggest products or services a customer might like or need before they know themselves. In e-commerce, this might manifest as personalized shopping experiences where the AI suggests items that fit the customer's style or previous purchase patterns, enhancing the shopping experience and increasing satisfaction and loyalty.
2. Automated Support and Resolution: Generative AI can proactively identify issues or problems before the customer is aware of them and initiate contact to resolve them. For instance, a service provider could use AI to detect a potential service interruption and automatically inform customers about the problem and the steps to fix it. This reduces customer effort and frustration and improves trust and reliability in the brand. 
3. Dynamic Content Creation: AI can create customized content for individual users based on their interactions and engagement history. Generative AI will keep users engaged and improve their experience by making content consumption more relevant and digestible. 
4. Enhanced Customer Interactions: AI-powered virtual assistants can use generative AI to engage in more natural, context-aware customer conversations. These AI assistants can remember past interactions and preferences, anticipate needs based on the conversation, and provide assistance such as scheduling appointments, answering complex queries, or offering troubleshooting steps without the customer asking explicitly.

These examples are just basic. We are in the foothills of massive change, and those who embrace the change correctly, as I've described, will reap the benefits. Those who just Implement AI because everybody else is doing it will fall by the wayside. Which path will you take?

Interested in discovering additional insights about AI's role in customer experience? Listen to the latest episode of the CX-Wise podcast, where Howard Tiersky, the CEO and founder of FROM, an award-winning digital transformation agency, shares his approach to leveraging AI for refining and streamlining customer interactions.