Emotional Analytics is Next. Are You Ready?


In the near future, more organizations will use emotional analytics to fine-tune their offerings, whether they're designing games or building CRM systems. Already, there are platforms and software development tools that allow software developers to build emotional analytics into desktop, mobile, and web apps. In a business context, that can translate to mood indicators built into dashboards that show whether the customer on the phone or in a chat discussion is happy, whether the customer service rep is effective, or both -- in real time.

Such information could be used to improve the efficiency of escalation procedures or to adapt call scripts in the moment. It could also be used to refine customer service training programs after the fact. In many cases, emotional analytics will be used in real time to determine how a bot, app, IoT device, or human should react.

Although the design approaches to emotional analytics differ, each involves some combination of AI, machine learning, deep learning, neural nets, natural language processing, and specialized algorithms to better understand the temperament and motivations of humans. The real-time analytical capabilities will likely affect the presentation of content, the design of products and services, and how companies interact with their customers. Not surprisingly, emotional analytics requires massive amounts of data to be effective.

Emotion isn't an entirely new data point, and at the same time, it is. In a customer service or sales scenario, a customer's emotion may have been captured "for training purposes" in a call or in a rep's notes. In the modern sense, emotions will be detected and analyzed in real time by software that is able to distinguish the nuances of particular emotions better than humans. Because the information is digital, it can be used for analytical purposes like any other kind of data, without transformation.

Voice Inflection

What people say is one thing. How they say it provides context. Voice inflection is important because in the not-too-distant future, more IoT devices, computing devices, and apps will use voice interfaces instead of keyboards, keypads, or gestures designed for mobile devices.

Because humans and their communication styles are so diverse, contextual information is extremely important. Demographics, personas, account histories, geolocation, and what a person is doing in the moment are just a few things that need to be considered. Analyzing all that information, making a decision about it, and acting upon it requires considerable automation for real time relevance. The automation occurs inside an app, an enterprise application, or a service that acts autonomously, notifies humans, or both.

Body Language

Body language adds even more context. Facial expressions, micro expressions, posture, gait, and gestures all provide clues to a person's state of mind.

Media agency MediaCom is using emotional analytics to more accurately gauge reactions to advertisements or campaigns so the creative can be tested with greater accuracy and adjusted.

Behavioral health is another interesting application. Using emotional analytics, healthcare providers can gain insight into conditions such as depression, anxiety, and schizophenia.

The potential applications go on, including law enforcement interrogations, retail, and business negotiations, to name a few.

A Tough Problem

Natural language processing, which is necessary for speech and text analysis, is hard enough to get right. Apple Siri, Microsoft Cortana, and even spellcheckers are proof that there's a lot of room for improvement. Aside from getting the nuances of individual languages and their dialects right, there are also cultural nuances that need to be understood not only in the context of words but the way in which words are spoken.

The same thing goes for gestures. Large gestures are fine in Italy, but inappropriate in Japan, for example. The meaning of gestures can change with culture, which intelligent systems must understand.

As a result, emotional analytics will crawl before it walks or runs, like most technologies.

What's Your Take?

How might emotional analytics help you do your job better? How might it benefit your company? We'd love to continue the discussion with you in the comments section below.

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Lisa Morgan, Freelance Writer

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.

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Re: Good old-fashioned empathy
  • 12/29/2016 11:39:42 PM
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..

Jim writes


Empathy and customer service reps? Rare, oh, so rare.


 

How oh, so 20th century...

 

Re: New Aged Emotional Rescue ?
  • 12/28/2016 11:19:15 PM
NO RATINGS

This is roughly similar to the move in customer service to offshore centers. Customers caught on that the people on the other line could barely speak their language, let alone catch cultural emotional cues. Sure, customer service is still offshore to a surprising degree, but I think many companies did learn a lesson and pulled their operations back to America. Probably the same cycle will happen when they go to terminators to answer the phone.

Re: New Aged Emotional Rescue ?
  • 12/28/2016 9:28:25 AM
NO RATINGS

As we all are on a spectrum of empathy and compassion it may be that even our "normal" customer representatives and other who must deal with emotions and reading others are not quiet as up to speed as we might think in that department. I'd guess that until most of us can accurately read emotions of others and know how to be compassionate and actually be so, it's going to be difficult to have machines learn and behave in such ways that may be useful anytime soon.

Re: New Aged Emotional Rescue ?
  • 11/1/2016 4:55:25 PM
NO RATINGS

Emotion is key to how people act. Since business is about predicting, understanding and influencing how people act, the efforts on Emotional Analytics will not stop anytime soon.

I do agree that we have a lot of work to do before human customer service reps have to worry about the bots being more capable of empathy. 

PC

Re: Good old-fashioned empathy
  • 11/1/2016 11:02:56 AM
NO RATINGS

Yep!  Neo and enhanced Neo!  

Re: Good old-fashioned empathy
  • 11/1/2016 11:02:56 AM
NO RATINGS

Yep!  Neo and enhanced Neo!  

Re: New Aged Emotional Rescue ?
  • 11/1/2016 10:22:36 AM
NO RATINGS

I agree with you, Louis. A question that needs to be asked other than 'Can we?' is 'Why?'.  Emotional Analytics and the implication of using them is more than a 'business problem'.

New Aged Emotional Rescue ?
  • 10/31/2016 9:51:00 PM
NO RATINGS

Isn't Emotional Analytics an Oxymoron ?  Aren't we having enough issues with non-emotional analytics ?

While this might be a interesting endeavor, if companies want to understand their customers better then just provide the services paid for.

Far more work needs to be done in this direction for sure.

Re: Good old-fashioned empathy
  • 10/31/2016 8:53:39 PM
NO RATINGS

@BatGirl Sort of like an alter ego? Interesting. I'd have loved to have one drill me for college exams.

Re: Good old-fashioned empathy
  • 10/31/2016 8:45:16 PM
NO RATINGS

@ Magneticnorth.  Good point, people differ greatly with emotionally intelligence and empathy.  I wonder if this technology might be also used to read the customer service agents stress levels and insights on how to keep both the agent and caller happy.

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