If you’re still using emojis to power your brand’s emotional intelligence, you shouldn’t be

June 21, 2022




In a recent piece on the rising need for more informed emotional intelligence (eQ) in customer experience (CX), Information Week nailed it by saying: “Humanizing the digital experience is much harder than it sounds because it involves much more than just putting a happy face on software.” I couldn’t agree more. Using a perfunctory smiley face to demonstrate a strong understanding of emotion, one of the most complex topics on the planet, seems obviously flawed.

And yet, many organizations today are still capturing customer emotion via emotional analytics that attempt to assess sentiment by scanning a person’s social media, facial features, or eye movements. Accurate emotional understanding of your customers can only happen by more precise means of measurement, and must occur far earlier than after someone watches a piece of content or talks to a Chatbot. If you’re only using emotion AI or waiting that long to find out how customers feel, you’re likely often wrong and definitely too late.

Imagine having an emotional GPS tell you how every part of a brand experience will make each customer feel before it’s built. My team and I work with data to create new segmentation models, uncover unmet needs, and allow for individualized CX. Our work has allowed us to see up close that the most humanized brand experiences are created when you get into the customer’s emotional headspace as early as possible. This type of data mining absolutely must happen at the strategy stage so that experiences are crafted to directly align with what matters most to the customer.

Many brands are on autopilot and believe they are winning the personalization-at-scale game simply because they have more or better data than their competitors. That thinking is quickly coming to an end, as most recent reports suggest fewer and fewer people feel that brands do a good job at creating individualized experiences that matter to them.


Emotion tracking via AI is not the same as using AI, data science, and other means (such as ML or neuroscience) to acquire data that predicts how people will feel about something before an experience is created. Invest in technologies that enable precise emotional scoring at the strategy stage vs. smiley and sad faces in the customer feedback loop. Identifying emotional white space early avoids false positives and reveals new opportunities.

For example, in a recent Gen Z study, my team and I were able to see a ton of joy around the Walmart brand from the overall sample, likely due to its strong partnership with Tik Tok. At the same time, we identified underlying tension beneath the brand. This type of precise understanding offers Walmart a cue to dial up efforts around issues that matter most emotionally to this audience segment, like mental health and food insecurity. Doing so lays the groundwork for a relationship with Gen Z based on loyalty and trust vs. a purely transactional one built upon a media platform they don’t own.


Broad brush demos no longer work based on age, gender, and income without adding a layer of emotional contextualization to your data. Sure, you’ll be able to find out that Millennial soccer moms in both Cleveland and Cambridge love the same features in their minivan in traditional demographic data, but you won’t also be able to be surprised to discover that a Baby Boomer, Asian male in Compton derives joy from the same experiential components of the car as they do. Novel cohorts built upon emotional data provide the deeper level of customer understanding today’s environment demands. Emotional phenotypes, otherwise known as observable emotional traits, are quickly debunking traditional means of segmentation.


Everyone is aware of how critical respecting gender identity is for any brand, but executing on it in an emotionally relevant and resonant way is everything. For example, our Gen Z study also showed us that while both Puma and Nintendo invested in gender-neutral experiences, the efforts by Puma were widely lauded because of the authenticity and fluidity of their AMI gender-neutral apparel line. Nintendo, on the other hand, was widely criticized for an emotionally obtuse approach toward gender neutrality in their Cyberpunk 2077 game, brought to life by uninspired, augmented anatomical features.

What Nietzsche said long ago summarizes well the golden rule of marketing today: “One ought to hold on to one’s heart; for if one lets it go, one soon loses control of the head too.” Regardless of industry or focus, emotional data must be harnessed as a critical component of any go-forward marketing strategy. This is what the most beloved brands will use to power their CX to achieve personalization at scale and improve bottom-line performance.

Post by Billee Howard

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