Companies around the world are striving to deliver exceptional customer experiences and elicit positive and exciting emotions that prompt the customer to return time after time.  Being able to measure our emotional response to things is not always easy, but a team from the Rotterdam School of Management at Erasmus University (RSM) believe they’ve developed a system that does just that.

In a newly published paper, the team describe how their electroencephalography (EEG) based technology tracks how we feel from moment to moment.

They tested their system on 40 volunteers who were asked to watch a series of videos, each designed to trigger certain emotions, including happiness, sadness, fear and disgust.  The data that was generated by the EEG signal was then used to train a machine learning algorithm so that it could be deciphered.

“The results showed that the algorithm we used can successfully predict which emotions were experienced during the viewing of the video clips,” the authors explain.  “The ultimate validation that the classification algorithm worked came when we showed the participants a clip from the animated Pixar movie ‘Up’. The clip tells the story of the lives of a man and woman who get married, and grow old together.”

Tracking emotions

The researchers were able to accurately predict the happy and sad responses on a second-by-second basis during various movie clips.  Indeed, the predictions accurately tracked the emotional ups and downs of the story.

The team believe that it helps product designers and marketers better understand the emotions we feel, especially in circumstances where we’re not as honest about them as we might otherwise be.

They hope that by providing a more accurate measure of emotional experiences, businesses can have a better handle on the emotional impact their product, advert or customer service has on the customer.

Whilst the product is still a little way from being ready for market, the team are confident that it will eventually make it and provide companies with a valuable method of tracking customer experience.