Detecting Customers’ Moods: Is it Good or Bad?

I started learning about mood detection in my childhood days; but it was just all about people and rings – definitely with no advanced technology involved. I was fascinated with how mood rings, when worn, change its color according to one’s body temperature and can easily tell you your mood based on it. I’ve had a few and tried them once, but I was never satisfied with the results – I was just probably awed by the rings’ beauty and designs and nothing more. Maybe I didn’t also like the fact that people could easily tell my mood and analyze my emotions based on the colors my rings show. It’s a little sour for my privacy, I guess. But isn’t it nice to at least know what your emotions are if you’re not really sure of it?

So why am I pointing these things out? It’s because I recently read an article from The New York Times that discusses how call center agents can now identify their callers’ moods and emotions based on their intonations. As quoted on the article, “It’s not what you say. It’s how you say it.” It’s probably another innovation that we should be looking forward to, but the article pointed out things that could make it “good” or “bad.”

Infinit-O’s VP for Data and Research, Al Pangan, also published an article on Outsourcing Insider about this topic recently. He left readers with questions at the end of the article that could either be easy or difficult to be answered by anyone from this industry. It’s really an interesting read! But moving on, here’s my take:

First, let’s talk about transparency. If you are going to analyze every data of your customers, which will now include not just their recorded voice messages, but also their feelings, it’s your responsibility to let them know. Doing it might be a good start, but the customers might feel a little awkward, too. However, the sole purpose of doing it is for their sake as well. As what we often hear, “This call may be recorded for quality assurance purposes.” Quality – that’s what customers always want to have and to offer it, this kind of analysis could truly help.

Moving forward, the second thing that could be at stake here is the credibility of the analysis itself. As written on The New York Times’ article,

“It seems to me that the biggest risk of this technology is not that it violates people’s privacy, but that companies might believe in it and use it to make judgments about customers or potential employees,” says George Loewenstein, a professor of economics and psychology at Carnegie Mellon University. “That could end up being used to make arbitrary and potentially discriminatory decisions.”

Professor Loewenstein completely has a point. What if the analysis concluded something wrong and completely changes your perspective about your customers’ feedback on you? After all, the only person who can tell how he really feels about a certain company is himself. This kind of technology seems to bypass that – so you tell whether that’s a good habit or not.

The third thing to be considered here is how call center agents can use the data from the mood detection algorithm. As quoted on the article, “It helps agents decide how to respond.” I think it’s an excellent way of applying this kind of technology on your contact centers. It can show how sincere you are on solving your customers’ problems, frustrations, and dissatisfactions by knowing exactly how to respond. The same goes for the good things – customers’ happiness, satisfaction, and gratefulness.

There’s no solid conclusion on this because obviously, this is the kind of innovation that most companies would truly need to improve and satisfy customers. It’s not that I’m questioning it, but people might need some more proof on how everything’s done and how it has already become successful in many ways.

Have you been applying this kind of technology on your contact centers? If not, are you considering doing it? Let me know about your thoughts on the comments section below!

via Business 2 Community http://www.business2community.com/customer-experience/detecting-customers-moods-good-bad-0697854?utm_source=rss&utm_medium=rss&utm_campaign=detecting-customers-moods-good-bad