Anywhere humans can look at, engage with, or react to digital assets, emotion intelligence can pinpointed actionable insights to feed innovation.
During the pandemic, you might have toured a museum, taken in a concert, enrolled in a class, visited with a friend, or purchased something new for your home. How? All were available as digital experiences to anyone with an internet connection. Even before the pandemic, experiences were evolving digitally. We are surrounded by hyper-intelligent technologies, yet we crave experiences that bind us to the digital world in an emotional way. To win on both fronts, technologically enhanced experiences can’t just be intelligent. They need to be emotionally intelligent, that is, they need to make use of emotion intelligence.
As we emerge after living a virtual existence for more than a year, one area of tech innovation pulling ahead is emotional intelligence (EI). As an offshoot of Artificial Intelligence (AI), EI uses facial mapping, eye tracking, and other experience measurement data points to gain insight into the natural reactions of online users. Just as one might read someone’s body language or facial expressions to gauge their response to a real-life conversation, EI can collect multi-modal data and immediately connect it to tell that story digitally.
Particularly within the brand-consumer relationship, where a glaring disconnect shows 85% of brand executives claiming connection with consumers and only 15% of consumers agreeing with the sentiment, EI technology is a burgeoning frontier that will be making an impact going forward.
Visualization feedback: Emotion intelligence and facial mapping
Whether designing a product, game, app, advertisement, or website, the conceptual phase is always visual. Initial concepts are presented in the form of mood boards, sketches, scripts, or online staging sites. By using EI eye-tracking technology, user response can be captured in real-time, providing valuable data on what visual elements catch a user’s attention first or longest; or where their eye travels during the interaction. The addition of EI facial mapping capabilities further enriches that data by including physical responses indicating happiness, confusion, contemplation, or any number of emotional reactions.
EI feedback is also expeditious compared to traditional user feedback mechanisms. An online survey, for example, requires that questions be formulated and distributed before any input is contributed. Time is also lost as results are collected and analyzed, even when using technology to do so. EI technology closes that time gap by tracking responses in real-time, enabling a business to act on valuable feedback more quickly within the design cycle.
Customer-centric experience design
Feedback is a critical component of the experience design process. By soliciting user input throughout a product development lifecycle, businesses can adjust prototype designs to better reach a successful final result. But waiting for a prototype means that feedback-driven changes are happening in the second stage of experience design, prototype creation. What if user engagement could be enlisted and tracked in stage one – the conceptualization phase?
The highest ROI on any feedback channel is achieved when consumer centricity is built-in at a very early stage in the design process. That is to say, before a significant financial investment has been made, creating multiple test products and executing revisions. By enlisting valuable feedback beginning at the very first decision point, a business is aligning with consumer needs from the get-go, saving on future redirects, and moving more confidently – and cost-effectively – toward final product development. By utilizing the depth of information not available through traditional methods, Emotion Intelligence facilitates a more agile approach for measuring customer experience. The result is a more streamlined implementation of unaltered feedback.
Studies have shown that there are two kinds of purchase decisions drawn from a consumer response system: the subconscious left brain, which represents 95% of decisions made, and the conscious right brain, which represents 5% of decisions made. Existing technologies endeavor to understand consumer behavior by asking questions to solicit answers, a quantitative approach that’s right brain focused. Using measurement rating scales also adds a layer of subjectivity. The reason one user might rank an interface at a 7, for example, may be completely different from the reason another user chose the same ranking.
EI technology targets left-brain subconscious responses by reading real-time reactions, representing the overwhelming majority of true indicators. Based on tracked eye movement and emotional cues, insights are pinpointed, making them keenly actionable. Issues that need to be addressed during the revision phase can be based on exact moments during the user interaction, making changes more efficiently streamlined.
Elimination of data bias
Finally, EI technology cancels out data bias on both sides of the feedback loop – creator and provider. The process of designing what is meant to be a consumer-centric experience often starts with a small group of originators who bring certain biases to the table. Those inherent influences become part of the mix as the process moves forward. When feedback is solicited from users in the test phase, traditional methods rely on surveys written by people who may or may not bring additional bias to the formulation of questions. Finally, when users contribute input based on right-brain conscious feedback, more bias can be introduced.
By eliminating conscious thought and relying on EI technology to capture, interpret and organize true reactive data, these natural biases are removed from the equation, resulting in real-time unfiltered analytics. These form the strongest framework possible for an authentically consumer-centric experience.
Emotion intelligence on the horizon
Beyond consumer products and experiences, the future is limitless for EI technology capabilities. Think online education optimized for maximum student engagement and retention, or human resources departments collecting body language data previously missing from online candidate interviews. Anywhere humans can look at, engage with or react to digital assets, EI can be there with pinpointed actionable insights to feed innovation.