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Facial Expression Recognition for Market Research

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Being able to interpret facial expressions is an important part of nonverbal communication. Think about this, in a conversation, if you only listen to what a person says and ignore what that person’s face is communicating to you, then you’re only getting half the story. The value in understanding facial expressions is to gather information about how the other person is feeling and guide your interaction accordingly. Well, what does this all mean for you as a business or researcher? Let’s dive in for some clarity.

What is Facial Expression Recognition?

Facial expression recognition is computer-based technology that uses algorithms to instantaneously detect faces, code facial expressions, and recognize emotions. It is a technology that is positively disrupting the market research industry. This is because researchers, marketers, and businesses conducting consumer research, are now able to get a better understanding of how customers feel about their products, services, or brand.

The problem with surveys

For years, brands and market research firms alike have been using surveys or focus groups to gather data on their consumers perceptions, beliefs, and feelings toward their products and marketing campaigns. These tried-and-tested methods have of course worked and have taken the market research industry far. But one has to wonder, are these methods painting the whole picture?

The problem with surveys, or focus groups for that matter, is that what people on them is not always aligned with what they really think. This could be caused by a number of reasons: peer pressure, social norms, embarrassment, or maybe a lack of understanding. Also, as much as respondents may share honest feedback, that feedback may not necessarily help you pinpoint where the gaps are. This is to say that consumers may like your product, but not necessarily love everything about it.

How does Facial Expression recognition work?

The idea of analyzing and categorizing emotional reactions in market research is far from being new. Skilled researchers have been trained to have a watchful eye when conducting research, paying careful attention to human behavioral traits such as body language, tone and so forth. However, with qualitative facial expression recognition technology, researchers are able to go a step further. The technology can capture extremely brief micro-expressions at the point-of-experience and automatically detect the six basic or universal expressions: happiness, sadness, anger, surprise, fear, and disgust.

Here’s how facial expression recognition works:

  • First, a face is detected in the scene: in an image or video.
  • Next, facial landmarks (or features) are detected.
  • Once the face has been detected and analyzed, facial expression and emotion classification takes place.


Using a webcam, respondents watch an advertisement on their computer as the webcam and program detect micro-expressions made during the advertisement. This is typically followed by a questionnaire for a true Whole Mind Approach to understand decision making processes at play during the consumer’s experience.

The importance of Facial Expression Recognition

Facial expressions convey nonverbal communication cues that play an important role in communicating how a person feels. Facial expression recognition is, therefore, important because it can further help companies understand their audiences. Because of its ability to detect and analyzes expressions from an image or video feed, it is able to deliver unfiltered, unbiased emotional responses as data.

Sightcorp Facial Expression Recognition software

At Sightcorp, we develop patented proprietary AI Software solutions. Through computer vision and deep learning, we can analyze faces in images, videos, and in real-life environments. Our software can detect and measure facial expressions like happiness, surprise, sadness, disgust, anger, and fear. The overall mood can be estimated with accuracy up to 92%.

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Melissa Roux Author
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About the Author
Hobbies: reading, hiking, football and traveling. Why I'm an expert: I have 6 years of experience in copywriting; I'm always learning new things; I started out my marketing career in the education sector, where I had the opportunity to learn about multiple fields; I started working in the tech industry last year and find it highly engaging