How Human Emotions are Useful For Your Marketing

Emotions and marketing

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Can you spot a person’s emotion at first glance? You could probably tell when someone looks sad, joyful, or enthusiast. You can do it thanks to many little details. Not only huge smiles, ugly cries, or happy jumps. A lot of micro-expressions can reveal people’s mood, too. Understanding emotions is a human ability that is innate and natural to us.

Nowadays, AI can do it, too. It sounds incredible, but Artificial intelligence can read our faces and understand our feelings and our mood with enough precision. It may seem a bit scary, but it’s an excellent opportunity for many brands in different fields, indeed.

If you want to know how AI can detect our emotions, follow us to find out!

After all, we can tell you’re dying of curiosity. You have it written all over your faces.

Emotion Recognition. What Is It And How AI Improved It

Emotion recognition is an existing technique that’s already been used all over the world. You are probably already using it every day, too. First of all, let’s have a distinction between three similar yet different concepts.

  • Facial detection: this is the ability of algorithms to identify the presence of human faces in a frame – a picture or a video.
  • Facial recognition: the next step is facial recognition. The software compares different faces to find out which ones belong to the same person. This happens, for example, when Facebook asks you if you want to tag your friend in the photo you took, or when you active Face ID on your iPhone.
  • Emotion recognition: despite its name, the idea of this function is pretty simple. The software can tell if a person’s expression is sad, happy, angry, or feared. It can “read” the emotions.

Today we are going to focus on emotion recognition. How does it work? It works by analyzing the sentiments and the feelings on a human face by using image dispensation. This technology can also catch what experts call “micro-expressions”. They are all those tiny, unconscious movements that can tell a lot about our mood.

Like a lot of fancy inventions, this one isn’t new, either. Scientists worked over image recognition a lot since the mid-1900s. But why is it so important?
First of all, it’s impossible to have two faces that are ideally the same. Even identical twins have tiny little differences that can help you distinguish them. Ask their parents, and they’ll tell you!

Nowadays, facial and emotion recognition has more credit than other biometric systems like palm print and fingerprint. This happens because facial recognition doesn’t need any human interaction to work correctly – which means that people can be even unaware of it.

This can make you think to many different dystopian scenarios, and in a certain way you would be right.

In a world like the one George Orwell depicted in 1984, Big Brother could see every single movement of your body and face, and you were forced to smile – every single moment. Or, at least, to show the expression and the emotion the regime wanted you to feel. The Big brother knew who you were, how you were feeling, and had a handy file about you and your features, just in case.

Lucky for us, we’re not talking about a dystopia. Emotion recognition is a reality, but people can use it for functional purposes, like every other technology in the world.

Emotion recognition goes to the next level by detecting single emotions.
A considerable part makes our language is nonverbal communication. The emotions can be classified into seven kinds.
They are:

  • happiness
  • sadness
  • fear
  • disgust
  • anger
  • neutral
  • surprise.

Do you remember Inside out?

via GIPHY

To achieve emotion recognition, you take advantage of two techniques.

  • Computer vision: The first one is computer vision, to identify facial expressions and features as precisely as possible.
  • Machine learning: The second one is machine learning, most of the time, with supervised learning. Its AI-based algorithms can analyze and interpret the “emotional content” of different faces and learning from it.

Machines are trained, thanks to machine learning, to detect millions of faces that have millions of different expressions. Happy babies, crying babies, angry women, sad old ladies, feared young men. More examples the AI will have – in terms of expressions, ages, ethnicity, and genre – the more accurate it will be to classify new pictures.

AI algorithms can learn to identify precise elements of someone’s face and pair them with a specific emotion. They could map some parts of the face – the tip of the nose, or corners of eyes and mouth -, classify the facial expression, combine them, and assign them to a specific emotion.

The more data, the better, because they can assure the most reliable accuracy.

The objection that someone moved was that human expressions aren’t always so blatant.
You can scowl because you’re angry, sad, or worried.

You can laugh because you’re happy, or even nervous (people often react at stress or fear by laughing).
You can cry because you lost your job or because your sister is getting married.

In all of these cases, a typical expression of an emotion doesn’t necessairly match the real person’s mood. Human beings react in so many different ways! Moreover, do you remember we introduced micro-expressions? AI can catch them, but they can sometimes mislead the machine.

This can be true, but nowadays, the accuracy of the machines is well tested to guarantee a reliable efficacy. Who knows how precise they’ll be in a few years!

fingers with human expressions
Freepik

How Emotion Recognition Affects Marketing

If you’re still not sure about emotion recognition, we can tell that different companies already use this technique all over the world. They do it to test consumers’ mood towards their brands.

Let’s explore together a couple of situations in which this technology can do magic for your brand, in many different fields.

  • Video game testing and marketing research. This is the funniest of all! Videogames have many different targets, but they all have something in common. It’s impossible to control facial expressions when you’re trying to defeat that ultimate boss or jump between flaming platforms! The scientists can analyze focus groups’ live emotions to understand what are they feeling in different moments of the game.

    This is an excellent opportunity to understand what gamers want and improve the final product. The same process applies to market researches to identify human needs and insights.
  • Voice and emotion for vocal recognition. Do you use Siri and Alexa? You are using vocal recognition. At the moment, this process is still on the embryonic stage, but it will grow. Our devices could feel emotions in our voice or our expressions and take some precautions. Think, for instance, about a driver that’s not entirely sober – or just plain tired. His car could feel these emotions when he speaks to it and decides to warn him.
  • Emotions and advertising. It’s not a mystery that advertising and emotions are strictly bonded. Advertising never spoke to your brain first but to our feelings. Two brands that know this very well and applied it to their strategies are Disney and Kellogg’s .

    Disney uses AI technology to analyze how audiences enjoy its movies. The company created an AI-powered algorithm that can “recognize complex facial expressions and even predict upcoming emotions” in a few minutes of tracking.

    Kellogg’s tests audience reaction to ads for its cereal. It does it by using Affectiva’s software, one of the most critical players in the advertising field. The software tests public reaction to multiple ads for its famous corn flakes and measures the responses in terms of laughing and engagement. After the test, the brand picks the version that generated a higher engagement level.

Other Emotion Recognition Practical Uses

How can brands take advantage of all of this technology?
Let’s discover a few examples.

  • Healthcare. Healthcare can take advantage of a lot from AI and emotion recognition. For example, it can analyze patients’ faces to see if they still need medicines or evaluate the gravity of their disease, to prioritize doctors’ examinations.
  • Automotive. Cars are more personal and secure every day that passes. This means that cars are almost “intelligent,” and it’s useful to them to understand human emotions. One of the most common problems is the driver falling asleep or driving drunk. If the machine can sense when its driver is drowsy or had too much to drink, it can alert him and potentially save his life.
  • Security. This one is possibly the most known use of AI and facial recognition, probably because of a lot of tv shows that use this technique. Thanks to emotion recognition and facial recognition, it’s easier to find out a suspected person and try to find out if there’s danger ahead.

Takeaways

  • Understanding emotions is a human ability that is innate and natural to us.
    Nowadays, AI can do it, too, and it is a great marketing tool.
  • Emotion recognition is different from facial detection and facial recognition. It makes software capable of telling if a person’s expression is sad, happy, angry, or feared. AI can “read” the emotions.
  • Machines are trained to detect millions of faces that have millions of different expressions. AI will be more accurate; it will be to understand the nex emotion you’ll put in front of it. This can be used in many ways from marketers.

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