Emotional AI – Why Is Your Marketing Department Missing Out on This Tech?

Facial recognition technology has come a long way in recent years, and the latest development in this field is the ability to analyze human emotion. This technology uses advanced algorithms to interpret facial expressions and identify emotions such as happiness, sadness, anger, fear, and surprise.

One fun fact about facial expressions is that they don’t just express emotions but they evoke them as well. For instance, raising your cheeks can make you happy, while furrowing your brow can make you angry. This is known as the "facial feedback hypothesis," which suggests that our facial muscles play a role in how we experience emotions.

Recent research has shown that emotional AI can be used in the marketing industry to improve customer engagement and increase sales. Here are some examples from around the world.

Suning: boosting the retail experience

China's retail industry has leaped forward with the strategic partnership between Chinese retailer Suning and Chinese AI technology firm Emotibot, introducing an innovative AI Shopping Assistant that uses emotion recognition technology to improve customer experience. 

Suning's finance app is integrated with the AI Shopping Assistant, giving customers a personal and in-depth shopping experience. The AI Shopping Assistant has proven its worth, enhancing a variety of business metrics such as customer service, customer satisfaction, and customer loyalty.

Not only that, but the AI Shopping Assistant has also enabled Suning to monitor customer flow and analyze customer behavior, leading to more organized merchandise management and improved product placement. In addition, Suning's AI Shopping Assistant has made shopping more convenient for customers by providing a fast checkout experience, as well as product recommendations tailored to their age, gender, and emotional reactions.

Sao Paulo Subway: optimizing ads with emotion recognition software

The Sao Paulo Metro recently made a huge step forward in the world of Artificial Intelligence by deploying AdMobilize's emotion AI analytics. With this incredible system, the Sao Paulo Metro can measure the emotions of passengers as they watch the interactive advertising on the subway doors. In other words, it delivers detailed data on the number of people who watch the displayed advertising as well as their emotional responses while doing so.

The system can also measure gender, age, and dwell time, which in turn allows the metro to optimize store traffic flow and adjust content to target the right audience demographic and emotions. This new system is sure to revolutionize the way cities around the world measure and interact with their passengers.

Think about using this tech in other contexts like airports. Airports could measure the emotions of passengers in real time. By analyzing facial expressions and eye movements, the system could detect if a passenger is feeling stressed, happy, or neutral. 

This data could then be used to create a world-class passenger experience by providing personalized assistance and services tailored to each individual. For instance, airport security staff could use the data to understand how passengers are feeling if they are in distress, and how best to approach them. 

Disney: targeted marketing campaigns

Disney has come up with a groundbreaking new campaign that uses facial recognition technology to track the facial expressions of moviegoers

This data is then used to create personalized advertising experiences for viewers and to maximize their enjoyment of the movie. To develop this system, Disney Research and Caltech joined forces to create a facial recognition system that monitored the emotions of viewers while they watched the movies. 

This system was able to capture the viewers' faces using infrared high-definition cameras and to detect how many were laughing, how wide their eyes were, and the various expressions they were making. The experiment showcased 16 million facial landmarks from 3,179 viewers, proving its predictive power.

The deep-learning software was able to accurately predict how a member of the audience will react to the rest of a film after analyzing their facial expressions for just 10 minutes. In addition, the system was able to recognize a series of facial expressions from the audience, such as smiles and laughter. The results also showed categorical boundaries of face identification at 30% and 70%, making it possible to create personalized experiences for viewers.

Overall, emotional AI is a promising technology that has the potential to revolutionize the way we interact with customers and improve the customer experience. 

With the increasing use of emotional AI in the marketing industry, companies need to stay informed about the latest developments and best practices in this field and be part of the AI revolution.

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