Effective Data Management for Service Isn’t Easy, But it’s Worth It

September 23, 2020 | 4 minute read
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This article is adapted from the Oracle CX Cloud Virtual Summit interview with Chris McGugan, Senior VP, Oracle CX Service and Jeff Wartgow, VP, Oracle Product Management.

My “why” for working at Oracle is simple: data. The world runs on it, especially for the future of service and customer experience design.

Every day, we’re exposed to thousands of targeted ads based on the mountains of behavioral, demographic, and geolocation data companies own. Yet when we reach out to a contact center, we’re transported to the Stone Age. We have to repeat the same basic information every time we interact with someone new. Even if we’re transferred, we usually have to go back to the beginning. Many businesses have led customers to believe this is just “how it works” when the truth is they don’t have the right level of customer data management that could support the customer intelligence needed to deliver incredible service experiences.

Nothing’s impossible when you have that elusive golden record of customer data. Businesses can better anticipate market shifts, reconcile high value customers, predict customer churn, and create more authentic customer service experiences all while improving business performance. This is the future of service, and successful organizations understand it’s “do or die.”

What does providing great service look like?

When a customer—let’s call her Ashley—calls her pet products supplier’s customer support number, the agent should already know who she is, her address, her purchasing history, and that she’s most likely calling about a delay with her automatic shipment of cat food—all before the first “hello” is spoken. AI-based screen pops should appear on the agent desktop, offering relevant information such as why the delay is happening and an offer for a 20% off discount code for Ashley’s next autoship. With this information readily available, Ashley can have a real conversation with the service rep. A more authentic connection is created. This is what customers want. They’re looking for brand relationships that feel less robotic and more real regardless of what they’re purchasing or how they’re engaging. This is just the tip of the iceberg of how companies can leverage customer intelligence with effective customer data management (CDM). 

Let's take a look at another example. Imagine you’re the CIO of a large grocery chain that has an active recall of baby food. With hundreds of stores across the country, it doesn’t take long until your contact centers start getting flooded with calls. What if you could proactively engage with affected customers based on a massive pool—one consolidated source of actionable data—at your fingertips? Your customer service agents could immediately identify if an incoming caller is a recall-affected customer to anticipate their needs (i.e. “I see you bought Healthy First Baby food. Yes, we can confirm there’s been a recall and it’d be best to throw it out. Here’s a credit of $10 towards a new purchase”).

What could customer service look like in the future?

Customers have been calling your contact center about this recall, but you also need to alert every customer who's still unaware. Research shows that most major U.S. grocery chains need to do a better job of notifying customers about recalls. You can be the one who steps up and uses data to deliver a better customer experience (CX). What if you used that sample of people who contacted you about the recall to generate key insights? What if you looked at demographics? You might learn that most of those customers are females aged 25 to 32. You might see that they also live in specific neighborhoods. You could use this data to find other “like” customers and proactively notify them using their preferred communication method—text, email, or phone—that if they recently bought that brand of baby food to check into it (including a link to learn more on your website).

With the right data strategy, you can piece together accurate profiles of individual customers based on their interests and attributes, and you can use that information to your advantage. Consider the telco industry. Imagine knowing off the bat that an incoming caller is a young mother who lives in a Texas suburb and being able to route her to a customer service agent who is also a young mother living in a nearby city. Imagine a screen pop appearing on the agent desktop informing her there’s a 75% chance of that customer canceling her service within the next 30 days and that she is authorized to offer one free month of Disney+ to keep her satisfied. Would that make for a better customer service experience? This is the power of data- and AI-driven customer intelligence for the future of service.

How to build a customer service team based on data

I know what you're going to say. If it was so easy, everyone would do it. The more monolithic the technology gets and the more that’s needed to understand it, the more difficult it becomes. It feels like scheduling yourself for open heart surgery. But that’s what digital disruption is.

In today’s digital economy, data is the most important kind of capital. This new role for data has significant implications for competitive strategy and the future of service, and that’s why I chose Oracle as my next professional endeavor. Data is in the DNA of this company. It’s what we do best. No one has a bigger database nor a more effective management system for the level of integration and analysis needed to leverage customer intelligence and enable the future of service. And what a bright future it is.


During the Oracle Cloud CX Virtual Summit, Chris McGugan, Senior VP, Oracle CX Service and Jeff Wartgow, VP, Oracle Product Management talk more about the importance of real-time intelligence, their favorite streaming TV binges (Cobra Kai vs. Outlander), and what it all means for service leaders and practitioners in the Experience Economy.

Watch the full interview from the CX summit here.

Chris McGugan

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