Step one to addressing first call resolution

If you don’t know why a customer is calling, how can you expect to solve their problem the first time? In the second installment of a new blog series devoted to enhancing first call resolution, Chris Caile explains how capturing caller intent with natural language understanding can help companies improve call routing and containment.
With natural language understanding, companies can better capture caller intent and solve customer issues faster.

Despite rising customer expectations and shrinking budgets, companies are increasingly expected to deliver great customer experience in the call center. My last post introduced us to first call resolution (FCR), an increasingly popular call center metric, and outlined the cost implications of not getting it right. The rest of this series will outline four proven initiatives to help improve your company’s first call resolution rate. Today we’re kicking it off with advice on how to improve routing and containment.

But let’s take a step back. Do you know your company’s FCR rate? The formula to compute FCR is straightforward – divide all the calls that come into the IVR by the number of calls resolved the first time. Having this internal-focused view of FCR will help you start the process for improvement. But remember that is only one view into the situation. And while these internal stats and graphs may suggest everything is fine, it is also essential to consider the customer’s perspective on whether their issue has been resolved, because they might have a different impression. And ultimately, your organization’s bottom line depends on their satisfaction and willingness to do more business with you.

Additionally, failure to take the customer’s viewpoint into account could artificially inflate your FCR, resulting in hidden sources of customer churn. After all, you can’t solve problems if you don’t know they exist. You must therefore use a combination of internal and external sources of information to build an accurate picture of FCR success rate. The table below shares the most common sources of both internal and external data that you can use when calculating FCR.

8.15 FCR image

But there’s one secret many companies miss when reviewing the data. They don’t consider the caller’s timing and their reason for calling (caller intent). We’ve seen many companies mis-calculate their FCR by simply measuring it based on subsequent calls by the same phone within a pre-determined period of time – typically 24 hours. But this creates inaccuracies. I once called my cable company on Friday to address a service issue (successful!) and then called again on Saturday to add additional channels (revenue generation!). These were two very different things.  Attributing the second call to the first and putting them together as “not resolved” creates a false impression and could lead you to fixing the wrong problem. There’s no question that understanding caller intent provides a clearer window into resolution rates. Which leads us to our first initiative…


Fix-it Initiative #1 – Improve routing and containment 

Imagine the following scenario: A customer calls your company with a problem but there’s no menu option that fits the reason for their call. In that moment, they have two choices – select one of the many IVR menu options and cross their fingers that they get where they need to go, or press “zero” for the operator, who often has no context for the call and ends up misrouting the caller again anyway. Both options result in frustration and wasted time.

To avoid this dilemma, one of the best places to start is to improve intent capture. Correctly capturing intent sets the stage for a successful resolution. Think about it: if you don’t know why a customer is calling, how can you expect to accurately solve their problem the first time?

To capture intent, companies have three basic options. You can use touch-tone, which gathers intent using keys on the telephone. But that’s the classic “Push 1 for Billing” approach that frustrates so many people. Second, you can use speech, which captures caller intent by recognizing specific words (i.e. “Say 1 for Billing”). Or finally, intent can be captured through conversational IVRs with Natural Language Understanding (NLU), which recognizes strings of words, allowing callers to speak naturally.

Of the technologies available, natural language makes the greatest impact on FCR and is the most effective in capturing intent. Look at it this way – customers are calling your company countless times a day, for thousands of different reasons. Assigning all those calls to a restricted set of menu options means making assumptions about why they call, which is an infeasible task. So how are you supposed to ensure customers get to the right place the first time?

That’s where NLU comes in. Modern IVRs today are starting to use advanced technology that let your callers say anything they’d like and your IVR will be smart enough to understand it. It recognizes both what they are saying and their intent.

8.15 FCR image 2

With NLU you turn your IVR from a maze into an asset as customers are more likely to be directed to the right resource – quickly and without error. And you’d be surprised how callers may even enjoy the experience when your IVR goes from “Listen carefully as our menus have changed” to “Hello Cindy, how can I help you today?”  The ability to resolve their call on the first attempt goes up along with their satisfaction with your company.

NLU is just one way to improve your first call resolution success. Tune in here for additional steps as we continue our series to explore strategies to ensure customers get their problem solved the first time around.

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Mastering call routing

Every single second wasted by a misroute, each frustrating dead end your customers experience, comes at a very real cost. So here are 5 strategies to reduce misroutes, improve customer satisfaction & reduce costs.

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Chris Caile

About Chris Caile

Chris Caile joined Nuance in September 2015 as senior solutions marketing manager for Nuance Conversational IVR (Interactive Voice Response). Before joining Nuance, Caile worked in various marketing and sales support positions at Microsoft and Motorola and has over 20 years of experience in the high tech industry. Caile holds a bachelor’s degree in business administration from Illinois State University with minors in mathematics and economics.