I recently read an article about an endeavor that is currently being undertaken to develop a “Speech Analysis Algorithm Crafted to Detect and Help Dissatisfied Customers”. In short, a team of engineers are hoping to create software that will recognize when a caller is becoming stressed and immediately phone a manager to alert them of a developing situation. Wow! It is rare that you would see math and science applied to something that is so subjective. After all, math is used to quantify and measure things all based on a known or a baseline. In this particular effort, I would surmise that the team of engineer’s most difficult task will be to determine how to establish a unique baseline for each unique call and caller. Once upon a time as a student of Electrical Engineering, I took on my share of convolution integrals and that’s a path that I do not care to venture down again. I’ve also taken on my share of convoluted customer calls in a past life and witnessed our frontline assisting customers in complex situations here at SoftLayer.
Until there is such an application that can detect and address a conversation that may be heading in the wrong direction, we have to rely on good ole’ training and experience. With each call and query, the baseline is reset. I’d even go further to say that with each exchange; the baseline is reset as our Customer Service Agents seek information to get to the root of the issue. It’s not hard to imagine the frustration that can build in a back-and-forth conversation as two people look to come to a solution or an amiable conclusion just as it is understandable that sometimes, a customer may simply need to vent. How do you calculate and anticipate those scenarios?
I wish much success to the team involved in the customer service speech analysis program. And programmatically speaking, I see many CASE, SWITCH, FOR, WHILE, BREAK, CONTINUE, IF, ELSE, ELSE IF, NEXT statements in your future. Good Luck!