What is emotion analytics and why is it important?

SG. How do Heartbeat emotion text analytics findings complement or compare with insights discovered via neuroscience and biometrics, via facial image recognition and brain-activity measurement?

LN. I strongly believe in cooperation over competition. I think putting our best technologies together will create a better future for our businesses and for this planet. A graphic will communicate how I see the future of emotion AI integration. (See the image below.)

How Heartbeat AI sees the progress of emotion analytics.

SG. Could you please sketch out 2 or 3 use cases? What’s your target market — clients and applications?

LN. Let’s start with the customer, the consumer or shopper. What do all customers have in common? They’re human, they feel emotions all the time, and those emotions drive many (if not most) of their decisions.

Why not measure emotions on every step of your customer journey? It’s not easy to put an eye tracking and EEG device on thousands of people, but it’s easy to ask one simple question, “Please share a few words that best describe how you feel about X.” This natural human question fits nicely into any survey and customer feed-back tool, and it’s surprisingly powerful. It not only invites a wide range of un-aided and un-biased feelings on the subject, but it can also aid at predicting what people will do in the future.

We’re a start-up, but we have already published two case studies to show the predictive power of emotions measured with HEARTBEAT emotion analytics: banking and political elections. The best application of HEARTBEAT is in on-going customer experience measurement and foresight.

SG. What’s on your product roadmap?

LN. We are driving in the fast lane! We launched our first prototype last December, and won an international startup competition (Insight Innovation Competition by GreenBook) in March 2016 in Amsterdam. All Spring and Summer, we tested our tool with some of the best research companies in the world. Finally, we launched enterprise SaaS this fall, which will enable anyone — brands, market-research suppliers, consultancies, marketing agencies — to access the engine. No more manual coding: leave it to a machine, fast and accurate.

Next, we’re venturing into a long complex journey of NLP and machine learning, to crack the challenge of context and meaning.

Here’s a quote that resonates with me, especially when it comes to trying to solve one of the biggest puzzles in the Universe, the puzzle of human consciousness: “The most influential thinkers in our own era live at the nexus of the cognitive sciences, evolutionary psychology, and information technology.” That’s New York Times columnist David Brooks.

The mission of Heartbeat Ai is to design emotionally intelligent technologies and tools to help machines understand peoples’ feelings and improve our emotional wellbeing. I don’t know exactly how we’ll get there in the end, but I know that we are on the right track today.

SG. Thanks Lana!

Readers, I’ve written-up a couple of other emotion analytics interviews — an IBM Watson blog contribution, Sentiment, Emotion, Attitude, and Personality, via Natural Language Processing, based on a conversation with IBMer Rama Akkiraju and On Facial Coding, Emotion Analytics, and Emotion Aware Applications with Affectiva principal scientist Daniel McDuff — and of course you can learn more about Lana’s Heartbeat work at LT-Accelerate in November. If you can swing a trip to Brussels, see you there!

Original post. Reposted with permission.

Bio: Seth Grimes is the leading industry analyst covering natural language processing (NLP), text analytics, and sentiment analysis technologies and their business applications. He founded Washington DC based Alta Plana Corporation, an information technology strategy consultancy, in 1997. Seth created and organizes the Sentiment Analysis Symposium and LT-Accelerate conferences. He consults, writes, and speaks on business intelligence, data management and analysis systems, text mining, visualization, and related topics.

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