Lessons Learned from Deploying Natural Language Call Routing

The key issue for decision makers in call centers is whether it makes business sense. The following are some of the conditions which will make a positive business case:

1. Multiple, distinct routing destinations - “Distinct” in this context means that not getting a caller to the correct destination leads either to a transfer (if the caller was routed to the wrong specialized agent pool) or a lost opportunity to self-serve the call in the IVR.
2. Size of the call center - The total yearly call volume should be in the millions of calls.
3. Above-average value of correct routing - Even if the above conditions don’t apply to your call center, the business case may still be positive if your agent costs are very high, or for other reasons, such as premium value of customer retention.

It doesn’t take dozens of destinations for natural language to provide benefits.  The Comparative Study of Speech in the Call Center3 compares call routing via menus versus an open-ended prompt proving a benefit with just eight routing destinations. While the above rules of thumb may suggest you should consider natural language call routing, building a solid business case that’s based on data from your call center is crucial to minimize risk and maximize your return (ROI). This leads you to the lessons learned.

Lesson #1: Drive the business case from analyses of end-to-end call data
Quantifying the business benefit of IVR routing is difficult because the typical ROI model for deploying speech, which focuses on fully self-served calls, cannot be applied directly. Even without fully self-serving a call, there is benefit to getting callers to the right specialized agent, assuming that your call center employs multiple distinct agent queues. Each misrouted call wastes both agent and caller time. The first agent has to diagnose the problem enough to realize that the call has to be transferred, and then decide where to transfer it. Following the transfer, the caller has to wait on hold and explain the problem a second time. Typically, anywhere between one to three minutes are wasted per misrouted call. That quickly adds up to a large savings potential. But routing is equally important to get callers to use self-service applications. Many self-service applications do not reach their potential because callers are getting lost in menus or frustrated before reaching them.

But how do you build a solid business case for natural language call routing? When our parent company deployed BBN Technology’s natural language call routing technology seven years ago, they did not buy into the standard business case based on estimates of increasing self-service, rather they based it on BBN’s methodology for evaluating and optimizing IVR business benefit based on end-to-end calls5. The key ideas of this methodology are:

• Measure routing by following calls from the IVR interaction through to the agent-caller dialog, to determine whether or not the IVR routed the caller to the correct place.
• Quantify IVR benefit as average agent seconds saved per call, instead of as number of calls “deflected” from call center agents.
• Credit the IVR for “partial” automation benefit.

Partial automation saves time by offloading routine tasks, such as capturing account numbers, routing, and delivery of information, regardless whether the call is or is not ultimately handled by an agent. Quantifying routing benefit based on end-to-end calls is necessary because only the agent-caller dialog provides the evidence of whether a call was or was not routed correctly. Misrouting rates are often measured based on statistics collected from each agent pool. These statistics are not based on total inbound traffic and missed pre-agent routing problems that still can have an effect on a substantial percentage of all callers.

An analysis of end-to-end calls yields a second key to the puzzle of building the business case and maximizing ROI of speech: the distribution of why customers are calling, or simply call-reason distribution. In measuring call-reason frequencies it is important to do so relative to all calls handled by the IVR, not just calls handled by agents. The call-reason distribution is valuable because it:

• Provides estimates of the upper bounds on IVR benefit
• Allows you to focus on the high-value areas
• Enables designers to consider the true frequencies throughout the design

Lesson #2: Focus on the high-value call reasons
Many call centers face new challenges as business requirements force them to make more and more distinctions in handling a call. For example, additional agent pools are introduced to handle specific caller populations or new products, or the push to save costs by increasing self-service automation leads to incorporating growing portfolios of self-service applications in the IVR. Designers may look to open-ended prompts as a remedy to bushy menu trees. While flattening menu trees is indeed one of the benefits of employing an open-ended prompt, this benefit should not be misinterpreted as a blank cheque to arbitrary complexity. Rather, even when employing natural language call routing it is recommended that you never lose sight of the time-tested KISS principle (“Keep It Simple, Stupid!”). Working hard to control complexity and focusing on the high-value call reasons throughout the application design leads to a simpler system, lower development and maintenance costs, higher utilization of self-service applications, and thus higher ROI.

Figure 1: Call-reason distribution example

In 2001 Our client developed a speech-enabled application to allow callers to order telephone directories. BBN’s analyses of end-to-end calls revealed that less than one percent of all calls were about ordering directories, not to mention that only a trickle of 0.1 percent of calls reached this new self-service application due to the rather complex menu tree. Hence, the new application provided little or no benefit. What’s the answer to this problem in the spirit of focusing on high-value and ROI? Employ natural language call routing to get more callers to the directory ordering application? No! High-value issues are typically associated with call reasons that represent a large percentage of all calls, and can be self-served or have to be handled by specialized agents. Figure 1 suggests that account balance inquiries in payments are high frequency and self-serviceable, while ordering directories is not even among the top 10 call reasons. In deploying natural language call routing, the recommendation was to focus on making it easy to get to the balance and payment applications.