Today Angel.com announces a break through in the IVR and Call Center world… embedded business intelligence analytics and reporting for IVR and Call Center Solutions using MicroStrategy.  Angel.com has been working for many months with the goal to not just bring stronger add-on reports to the IVR and call center world, but fully embedded business intelligence analytics built right into our on-demand Site Builder platform.  This capability came out of Beta today.

Dubbed “Caller First Analytics“, Angel.com was working to design a suite of fully customizable reports that enable businesses to deeply analyze their IVR applications with the goal of making the applications better for callers, which in turn has a positive effect on the business’ bottom line.  Participating in the Beta were Angel.com customers such as AstraZeneca, Pfizer, Barnes & Noble and Hughes Networks.  For some of these customers we’ve been able to use Caller First Analytics to address potential issues in the IVR, fix them, and incrementally increase the efficiency of the IVR to the tune of hundreds of thousands of dollars in savings for the business.

“Recently the marketplace has been expressing interest in the merits of integrating business intelligence with IVR,” said Jay Lassman, Research Director at Gartner, Inc.  “This marriage offers the possibility for large enterprises to better analyze and understand customer needs as well as voice call data, which should lead to improved customer satisfaction and business growth.”

Here’s a look at some of the key features Caller First Analytics will give Angel.com customers:

• Voice User Interface Reports. Track hang-ups, visits, time spent on a page, and other indicators of trouble spots in your voice application.
• Application Performance Reports. Measure and track task completion metrics, automation and containment rates, and transferred call statistics.
• Funnel Analysis. View the path callers take through the system and identify entry and exit points, which areas are accessed most frequently, and hang up points.
• Customizable Views. Customize reports by sorting columns, removing columns and filtering data, then save the reports in a “My Reports” folder so they can be accessed later or subscribed to.
• Export and Share. Schedule reports to be delivered via email to all major stake holders, or export reports to Excel for further analysis.
• Historical Reporting. Pull reports based on call parameter to see how your call metrics change over time.

To learn more, visit the Caller First Analytics page on the Angel.com website, and view the Caller First Analytics Overview video.

No matter how carefully you crafted your VUI design, or how diligently the design was implemented, or how thoroughly the implementation was tested, your application will need regular and careful tuning once deployed if your aim is to maintain a world-class, highly usable voice solution.

Tune up

To effectively tune your application, you should have at your disposal three sources of information: (1) Call Logs: which will enable you to identify patterns across calls (e.g., where are people hanging up), (2) Call Recordings: which will enable you to understand the nature of a problem (why are people hanging up?), and (3) Your callers: usually, you do this by assessing their level of satisfaction with the solution.

Here are the basic questions that need to be asked in order to begin tuning a voice application:

Where are people hanging up? A hang up prior to completion of a task is usually a sign of frustration. If the goal of your application is automation, your first tuning task is to identify such hang up spots in your application and understand why people are hanging up.

Where are people asking to be routed to an agent? If you have designed your application with the goal of empowering the caller, you must have provided the caller with the option to route to an agent. A caller actively asking to speak to an agent is a caller who has decided that the application is not successfully enabling them to serve themselves. This is especially true of callers who have engaged the application over several minutes of interaction and then decided to bail out.

Where are people saying the wrong thing? The aim here is to identify those spots in your application where no-match failures are significantly higher than the average or the expected. The remedy is to listen to the prompt the caller hears and then listen what people are saying in response to that prompt. In such situations, adjust your application by either re-writing the prompt or by adding to the language the system is listening to what callers are responding with.

Where are people not saying anything? These are the spots in your application where the caller goes quiet on you. This occurs usually because the prompt is confusing or the caller was asked for some information that they don’t have (or don’t have ready access to, such as a subscription ID or an account number). If the issue is with lack of clarity of ambiguity, then re-craft your prompt (see Chapter 3). If the issue is with lack of readiness, then provide the caller with the time they need to retrieve the information you need from them or suggest that they call back when they have the information handy. Another strategy is to inform the caller at the very outset of the interaction that the subscription ID or the account number will be needed.

Where are people speaking too soon? At times, callers are impatient and speak sooner than they should, often missing crucial information or instructions. To remedy, either turn the barge-in setting off, or re-craft the wording of the prompt the caller is interrupting.

What type of noise level are your callers calling from? When you listen to your recordings, pay attention to the noise level and how the noise is affecting the no-match error rates.

What options are people asking for? If you discover that 80% of your callers are checking their savings balance, then ask 100% of your callers if they are calling about checking their Savings balance. By definition, 80% of the time your will be right.

How are people feeling about the application? You can probably get a good sense of how people feel about the application by just listening to the tone of their voice in your call recordings.