Where does your customer's emotional trail lead?

I was reading a recent article in Speech Technology Magazine, the subject matter was speech-to-text software for recorded calls, and this passage caught my attention:

Many people live and work under the false assumption that speech analytics is a form of plug-and-play technology; in reality the applications require a significant amount of work and resources to make them function properly. Users constantly have to fine-tune applications, improve definitions, realign parameters, and then work and rework facets of the applications until they get them right for their specific operating environments. Once that is achieved, everyone has to understand that if they’re going to use speech analytics effectively, then they’re going to need to dedicate resources to it.

To me, that sounds expensive and slow with many potential points of failure. But maybe it's worth it. Let's see, after committing your time, talent and treasure to this analytics approach, what is it that you finally get to unveil at the boardroom readout...


Yeah baby, nothing says, "I've got my finger on the pulse of customer experience" like transcribed customer service calls.

I know there is the whole argument that speech analytics is needed because text can be indexed, sorted, aggregated, and mined for the keys to customer bliss and angst (if only our company had more data we'd know the answers....wait a minute... what about putting the text of all those calls in a ginormous database?).

But lets peel back this argument and look at another reason companies adopt this technology, although it may not be explicitly stated: speech-to-text allows us to avoid listening to the customer's actual voice. Let's admit it, hearing a customer treated poorly, or hearing them get upset about an issue is painful. Even as a third party listener, its painful (if you are in the business of improving customer experience, it SHOULD be painful). But at risk of having the cliché-police knock on my door, I tender that customer analytics is a case of "No Pain, No Gain."

When we experience the customer's pain, we gain depth of understanding what to fix. Their emotions are a trailing indicator of what has happened to them and a leading indicator of what they will do with (or to) you. Does a customer leave for a competitor and show no emotion? Does a customer call you and show no emotion? Does a customer's emotion typically stay the same over an entire call? Of course not.

Neutral emotions may characterize a customer's "business as usual" mode, but by definition they are on the phone with you because they are not in "business as usual" mode. And as all the mis-interpreted e-mails that have caused arguments (ok, I'm guilty on both sides of those) will attest, text is and always will get mis-interpreted much more frequently than voice. Voice is the most reliable medium for understanding emotion, and correlating the events of an interaction with customer emotion is the most effective way to fix what may be broken in customer relationships.

I don't have an issue with deployment of speech to text technology, just want to make sure companies have the right expectations about what they have in the end, and more importantly, what they have lost in translation.