Forget Freud. Emotion AI Is the Key to Analyzing Consumers’ True Feelings.

Most of our decision making occurs on a subconscious, emotional level. Now facial recognition technology is being used with AI to understand how that impacts consumer behavior.
Headshot of Ranjan Kumar
Ranjan Kumar
Expert Contributor
October 5, 2021
Updated: October 6, 2021
Headshot of Ranjan Kumar
Ranjan Kumar
Expert Contributor
October 5, 2021
Updated: October 6, 2021

To remain competitive in a fast-moving digitally transformed marketplace, brands need to utilize technology to gain a deeper understanding of both existing and potential customers. Automation is vital, but traditional data analytics are mostly limited to measuring behavioral touchpoints. By employing Emotion AI, brands can gain insight into a consumer’s subconscious, instinctive responses without the behavioral filters that come with making a prompted selection or answering a survey question.

 

Emotion AI Interprets Facial Expressions to Gauge Emotional Response

If a picture is worth a thousand words, a face is worth a million. When we’re skeptical we squint, for example, and a furrowed brow is usually associated with seriousness or concern. A face registering surprise might show widened eyes, an open mouth and perhaps a hand placed on a cheek. Emotion AI is an advanced technology that can read those markers and translate them into actionable reports based on whichever feelings are happening in real-time.

What is emotion AI and how does it work?

Emotion AI uses facial recognition technology and artificial intelligence to read eye movements and other facial markers to interpret emotional response.

To track eye movement, specialized software works with infrared eye-tracking cameras or webcams that support it; eye behavior (such as pupil movement or dilation in response to a stimulus or gaze time spent on various on-screen elements) is then recorded. By capturing this cumulative data, a report or heat map can be generated to tell the story of what the viewer found interesting while they were being tracked browsing a website, watching a video, or viewing a digital ad.

Targeted facial recognition technologies also lend themselves to reading emotion. By using a machine-learning algorithm to decipher facial expressionsa furrowed brow or open mouth, per our previous exampleEmotion AI technology can track associated synapses in the brain that trigger distinct expressions, matching them to their linked feelings. In this way, a story comes into view about that person’s digital experience.

 

The Business of Emotions

While adopting a more AI-enabled, data-driven approach to delivering positive customer interactions eliminates much of the guesswork involved in creating a consumer-centric experience, there is more, deeper technology that can be utilized. Specifically, Emotion AI can go even further, helping companies connect with users at the deepest level possible.

Whether testing the look of a newly designed website, tracking response to an online ad or gauging response to potential product design prototypes, the feedback gained from Emotion AI technology can prove to be an invaluable tool. Add to that the reduction in cost from reading the tea leaves early in the design process, and the expeditious delivery of actionable feedback, and interpreting intuitive responses through technology quickly shows its worth.

Read More on the Business of AI on Built In45 Artificial Intelligence Companies to Watch in 2021

 

Feelings Are Faster

Consumer feedback can be inferred by recording their actions, as in the case of shifting purchase behavior or other surface-level data. It can also be solicited via surveys or by enlisting focus group input. Both methods require time, either to await an observable pattern or to create a full-cycle testing scenario. Real-time insights are critical to gain actionable data quickly.

Given that no response to a brand, product or ad happens more quickly than an emotional one, Emotion AI is the key to harnessing the power of that instinctive, unfiltered feedback. In doing so, companies can use deeply personal insights to run ad campaigns, deliver product experiences and share messaging that resonates with customers.

 

Less Time, Lower Cost

Back in 2007, a marketing firm did a study and estimated that an average urban consumer saw 5,000 ads per daywho can even imagine what that number has grown to in 2021? When emotion is interpreted with behavioral data, companies can learn how customers interact with their brands ads and why. By utilizing Emotion AI, brands can tap into the subconscious behavior that drives 95% of purchase decisions. A more complete picture forms quickly, humanizing the experience to show product developers which features elicit the most excitement and engagement in users, or which ones cause skepticism. This sort of detail early in the go-to-market plan is a game-changer in terms of timing and expense. It also works to avoid opportunity cost post-launch; brands that fail to communicate effectively with customers have been shown to deliver nearly 40% fewer conversions.

While there will always be a place for traditional feedback channels, including surveys, polls and focus groups, today’s digital marketplace demands better. Emotion AI is the secret weapon in the effort to streamline development, accelerate the go-to-market cycle and maximize ROI.

Read More on AI From Built In’s Expert ContributorsWhat Can’t AI Do?

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