One of our products, a Canadian address capture VoiceXML module, has been deployed with great success by several of our customers. One of these deployments was done in the context of a change of address application, where the module has to capture the new address, the date when the new address becomes effective, and the new telephone number. Note that all information is entirely obtained through speech recognition.
In this deployment, the contract specified that the application had to achieve a minimum success rate. In order to track performance, two success metrics were jointly defined with the customer:
- The Raw Success Rate. This is calculated simply by dividing the number of calls for which the change of address was successfully completed (with all collected information confirmed by the caller), divided by the total number of calls for which the change of address module was used.
- The Real Success Rate. This is calculated similarly, with the exception that certain calls were excluded from consideration, namely calls where the caller provided no input whatsoever and calls where the caller hung up within the first two interactions.
The customer specified that the application had to achieve a Real Success Rate of 75% or more. The rationale for the Real Success Rate is to exclude callers that either don’t want to use the application (for instance because they ended up in the application by mistake) or don’t have the requested information. As a matter of fact, after the initial deployment revealed a fairly high hang-up rate early in the change of address call flow, the customer contacted a number of those callers in order to find out why they had decided to hang up and it turns out that most of them admitted that they had no intention of changing their address; they had simply selected this option in the hope of getting connected to an agent faster.
It’s nonetheless interesting to track both metrics since a large difference between them can indicate problems that occurred earlier in the call (that is, before going into the change of address application).
For instance, at the end of 2008, the customer made some changes in the front menus, which significantly increased the number of callers that incorrectly found themselves in the change of address application. As shown in the graph below, this created a big drop in the Raw Success Rate while the Real Success Rate remained relatively constant. The customer implemented various changes to the front menu throughout 2009 (while the change of address application remained unchanged), with the result that the Raw Success Rate was finally stabilized at around 75% (and the Real Success Rate at 85%).
This shows that, when trying to evaluate the performance of an application, it’s important to focus on the correct metrics. Otherwise, we may end up not only with an incorrect assessment of its real performance, but also with wild variations that have nothing to do with the application itself.