Emotional AI in practice, a new trend for brands

If you are still talking about image recognition or facial recognition, you might sound not that trendy in AI gossip. Because some are flirting with the idea of emotional recognition, that is basically trying to give EQ to the machine. A handful of companies, regardless big or small, are already wading into this arena. In particular, Affectiva, a Boston based startup, seems like a “wonder boy” now by applying emotional AI into diverse business scenarios. Early adopters of Affectiva’s emotional intelligence systems have included independent video game studios, brands or advertising teams within large corporations like Unilever, Kellogg’s, Mars and CBS. In 2017, more applications are in fact underway. 

 

 

In January, Cloverleaf, a San Diego retail technology company debut Shelfpoint, an LCD display shelf with optical sensors that track customers’ emotional response in real-time when they walk into your store. It recognizes joy, sadness, happiness or disgust according to customers’ facial expressions. See demo below. It is said companies like Dell will soon implement the solution.

 

 

 

So to integrate the technology that can determine different emotional responses into Shelfpoint, Cloverleaf has to partner with Affectiva.

 

In April, Unruly Media, a video advertising technology company, launched a new tool to analyze the emotional responses of audiences to the video content. It aims to give advertisers insights to maximise emotional, social and business impact of their video ads.It is said Unruly signed premium skincare brand SK-II to monitor the emotional trace of the brand video ads in HongKong and Taiwan. Again the facial coding and emotional analytics technology behind have been powered by Affectiva.

 

The two examples above simply show great potentials in emotion AI in practice. In China, the similar startup received the media attention is a Shanghai-based company called Emotibot.

 

 

Interestingly, Emotibot even claimed it performs better than Google solution in terms of recognizing the type of emotional state, finding face rate and accuracy.

 

 

Unlike Affectiva, at this stage, Emotibot more focuses on commercializing its chatbot offer which can understand the context and emotion of the user conversation to enhance customer services for many big enterprises in China; less about facial emotion analysis. But we believe China should and will catch the trend to put emotional AI into wider actions.

 

Author: Cecilia Wu