Reason codes, IVR data and customer loyalty: Do they really work?

Your customers call you with a specific need or problem they want you to solve. It is in this moment you are gaining the most unbiased voice of the customer — the moment of truth. This interaction contains answers to many of your company’s most pressing questions. Tools available today, like disposition codes and IVR data, offer flawed data. But we still often mention IVR data and customer loyalty in the same sentence. Yet to properly serve your customers and build loyalty, it’s even more critical that you understand WHY they initiated the call in the first place. How do I know this? Although I hear it often, I have always been surprised when call center and business leaders say, “We want a better understanding of why people call us!”.

The Goal — Better Data to Drive Business Decisions

Oftentimes, customers have more than one reason for their call. This reason (or reasons) — the WHY — is the true call driver. It often gets lost during the conversation, but if you really wanted to learn everything you need to know from each phone call to your contact center, you’d have to listen to all your calls and that’s just not reasonable. So companies collect and use IVR Data and Reason Codes (disposition codes) to provide call center managers an overview of why customers call. This awareness enables call center managers to make data-driven decisions to improve customer experience and call center productivity.

The issue — Do our current IVR and reason code tools give us the right WHY data?

First you must examine how the IVR data and reason codes could fall short of a robust understanding. When asked, we hear these common responses:

IVRs

• Everyone is using the same options in the IVR, simply because it is the first option on the list
• Customers prefer the option that is the quickest path to speaking with a live agent

Reason Codes

• Inaccurate use by agents who pull the code at top of the list
• Competing goals, such as AHT and reduced wrap-up vs. proper disposition
• Limiting the option set to ensure proper use, which ultimately limits insights gained

These issues result in inaccurate data and you may not understand the full spectrum of your customer call drivers.

Solution — Can we let the voice of customer be the purveyor of robust and reliable data?
Could you ditch codes altogether and still get better data? Could you reduce wrap-up time while getting better data? We think so…

The advent of the ability to turn customer interactions into structured insight holds much promise here. Today you can use machine learning to detect the reasons for calls. Here’s how:

• Almost limitless reason capture, as the machine is not taxed by depth
• Full context of the call provides instant value by uncovering the multiple reasons and outcomes typically held within most interactions
• Not only can the machine capture call drivers, but it helps you determine which combinations of events can drive deeper understanding and value

One more thought — We find that when you start to compare reasons to other factors in the call, that the system has been trained to detect (e.g., re-contact, channel switching, customer frustration, or agent uncertainty), you also learn the impact on your customers and agents.

With this data, you can determine all your unique call drivers with robust, accurate data. You can then address the issues and, in turn, save the organization money and increase customer loyalty by uncovering important facts about your customers’ needs.

We’ve done many data dives and a few eye-opening data comparisons regarding the reasons why customers call. We’d be happy to review some of the results if your interest is piqued.