Reporting on Bots – Why It’s as Bad as IVRs Ever Were

By: Rob McDougall, CEO, Upstream Works Software 

Reporting on the performance of conversational AI applications is often challenging, as they must be tailored to a specific business and its needs. As a result, it is difficult to gauge the success of a chatbot in interacting with and meeting the needs of customers.

To understand this issue, it’s helpful to look back at the history of Interactive Voice Response (IVR) systems. IVRs were generic systems that ran customized business applications – applications that were designed to meet a specific self-service need for that business. As a result, a ‘standard’ IVR report didn’t know anything about the actual application, and standard reporting was limited to port usage statistics. One of the outcomes of this became known as “IVR hell,” where businesses created applications that met their own needs but had no information on whether or not they met the customer’s needs. Without accurate reporting, it was hard to improve the IVR’s performance and customer satisfaction.

Reporting on the performance of chatbot applications can be similarly challenging, as these conversational AI applications (CAI) are tailored to a specific business and its needs. While ChatGPT has made amazing inroads into natural language processing, the underlying technology still needs to be integrated into your specific business in the same fashion that an IVR had to. The same goes for any other vendor on the market.

As a result, the same IVR reporting problem exists today with CAI.

Without solid customer-level reporting on how well a chatbot is performing, it’s hard to improve its behavior and effectively serve customers. As a result, companies may simply add more functionality to their chatbots in the hopes of improving containment rates, but this approach doesn’t address the root of the problem, which is the availability of success metrics based on your contact types.

When considering a CAI application, it’s important to pay attention to the reporting it provides.

Specifically, businesses should look for reporting on the unique operations of their business and whether or not the chatbot is solving the problems of customers. First Contact Resolution (FCR) is still the gold standard for servicing customers and should be measured with your CAI applications as well as with your agents.

By understanding the successes and frustrations of a chatbot, businesses can make improvements and better serve their valued customers.

Learn how Upstream Works AI application integration capabilities improve agent experiences (AX) here.