Using AI for Outcome-Based Customer Experience

Getting from customer satisfaction to winning customers’ hearts and minds.

Garbage in… garbage out. As 2020 approaches, the old adage has resurfaced, thanks in large part to four trends that are morphing from talking point into reality:

• Higher customer expectations
• Selecting experiences over price and product
• Explosion of data
• Increased use of machine learning and AI

On their own, none of these trends are new. But when they’re combined with a customer-focused strategy, they represent a phenomenal opportunity to use data to compete more effectively and go beyond satisfaction to build customer loyalty.

Higher customer expectations

Amazon set the bar years ago on what customers expect from the companies they do business with. That hasn’t changed, as Amazon is still the experience standard. What has changed is the number of companies across almost every industry that have also created a strategy to compete on customer experience: Hyatt Hotels & Resorts, Liberty Mutual, Allianz, Lufthansa, and many more. Each company has taken an approach to compete based on the experiences they create as a result of the insights they are capturing from their data.

Selecting experiences over price and product

Survey after survey finds that customers are increasingly focused on experience as a deciding factor. Eighty-six percent of customers will spend more to have a better experience. Thirty-two percent will walk away from a beloved brand after one bad experience. Seventy-five percent are more likely to buy from service providers who recognize them by name. And while you can predict a lot about a person to help create a great experience, you can still lose someone if you’re getting their name wrong.

Explosion of data

Although it seems as though we’ve been hearing about this trend for at least the past 10 years, it now has even more impact: it’s been estimated that within 5 years, the average connected person anywhere in the world will have one interaction every 18 seconds with their connected devices. When you consider that each interaction generates data, it becomes clear that it’s not just the explosion of data, it’s also an exponential increase in the things that create data: channels, ways to interact and transact, different types of devices, and more. And all of these contribute to increased complexity, too.

Increased use of machine learning and AI

The last big trend is machine learning and AI, which applies both to how data is consumed as well as to the processes that support data management. As a consumer of data, AI leverages new types of algorithms that rely on the vast amounts of data being created to reveal insights and provide more individualized guidance for informed decision making. And the use of machine learning and AI also makes data management more effective and automated, which eases the complexity of unleashing the value of data as a critical enterprise asset.

What’s most exciting to me is that the convergence of these four market shifts allows for companies to focus on how to build customer loyalty. (To clarify, I’m thinking of the real kind of customer loyalty that’s strategic, not the airline program kind that was once strategic and is, sadly, now tactical.)

Real customer loyalty is created through a focused strategy designed to capture the hearts and minds of customers over a series of mutually beneficial interactions and transactions as they occur over time. Satisfaction places a customer in a perpetual evaluation phase, because it is based on whether the customer is ‘satisfied’ with each individual interaction or transaction. However, when you’re focusing on customer satisfaction, what’s often overlooked is a single critical element for building loyalty: the understanding that customers want to build relationships with companies they trust.

To move a customer from being satisfied to loyal may require an individualized understanding of a customer, an understanding based on the answers to five seemingly simple-yet-complex questions:

1. Are they a customer?
2. What products do they own?
3. Are they happy with our [company, product, last transaction, etc.]?
4. What’s the next best offer or interaction?
5. Who is in their circle of influence?

Where can you find the answers to all of these questions? In your data. Those answers—and more—are just waiting for you to discover them and to use them to make great customer experiences a reality, and not just a talking point. But with the proliferation and complexity of data, you really need AI-driven insights and a 360-degree customer view to unleash the full value and potential of your data to create personalized, timely, and frictionless experiences for customers. With AI-driven insights and a 360-degree customer view, you can:

• Reduce digital leakage by as much as 10%
• Increase cross-sell effectiveness by as much as 25%
• Improve overall customer satisfaction by as much as 15%, along with improved retention rates as great as 10%

As we approach the year 2020, where are you on your customer experience journey and what do you want to accomplish? Let us know in our survey.

You can also hear more about Outcome-based, AI-Driven Customer Experience during our webinar taking place at 11 am PT on October 22^nd. Join me, Jay Warren, Vice President, AI & Analytics, and Marcus Ansell, Sr. Director, at Cognizant, and Jennifer McGinn, Product Marketing Director at Informatica, as we share how intelligent data and analytics transform operational, cost, and revenue results across a variety of CX use cases.

Register today and join us to hear the value of Outcome-based, AI-Driven Customer Experience.