When the AI buzz settles, we’ll all realize that yes, the robots are not only coming but are actually already here, and here to stay. They may not be ubiquitous yet but they will be. And they’re not our enemies. While that doesn’t make all AI “good,” there’s no denying that AI helps us do things at scale, and can do it well.

Doing it well includes the aspect we usually associate as the downside of AI: it’s, well, robotic. AI-generated content still has a long way to go. But in time it will be less and less “robotic” helping brands generate good (maybe even great) content while employing the advantages of automation and personalization.  

Artificial intelligence on emotional language and cues

AI helps us collect, build, and act on, a huge bank of emotion-related data. And personalization — if it’s going to be effective — must invoke human emotion. 

AI will continue to understand human emotion better, building better, longer brand relationships with customers through its learning and analyzing capability for human emotions and motivations. 

While human teams are still the best balance against AI’s biases, AI scores better than humans when it comes to detecting and deploying emotional language and cues.  

According to Deloitte research, 60% of consumers use emotional language to describe their favorite brand connections and 70% expect feedback as part of a brand relationship. 

Brand relationships mean real connections that come from emotionally relevant and memorable content rather than just purchase or search histories. Cookies used to be the sales and marketing cues, but they’re on the way out. Now all the big data businesses collect can be sifted to create portraits of customers so that they can give personalized experiences in real-time, according to behavior patterns and emotional language and cues.  

AI can collect and make intelligent assumptions based on these patterns and cues to deliver content or experiences that match a customer’s emotional state:

• Browsing too fast: interested but probably looking for something or bored. Can be captured by a lead magnet of an infographic rather than an ebook 

• Deeply immersed in the article or the catalogue: will want more information — or perhaps ready for a buying decision. Might be receptive to a discount.  

  
  

Back in 2017, way before their biggest scandal, Facebook had a controversial leaked memo, telling advertisers they can detect — and target — emotions such as insecurity and feelings of worthlessness. 

While that can make you fear Big Brother scenarios of AI taking over and knowing too much, the advantages for more effective communication are there. 

We can prompt responses with the right nudges according to the right emotions. 

That’s where AI comes in. It’s the stuff of science fiction, now in our current reality. 

Emotional insights for empathetic communication

Emotional and psychological principles in marketing aren’t new. Brands have always applied psychological associations to their strategies and their very structure, from their logos to their slogans. 

Famous examples are: 

• Colors for logos and websites. Black for sophistication and reliability. Blue for friendliness and sociability. That explains all the social media platforms and financial institutions in black and blue. 

• Powerful conversion phrases. The psychology of headlines and using evocative words everywhere, from subject lines to CTAs and social media captions. 

  
  

Colors and words can be considered cosmetic. They’re what your target audience sees. 

Emotional understanding through your target audience’s actions, that’s new. It’s what your audience does. 

Colors and words invoke emotions. AI tech can recognize, and help us respond to, customer emotions. 

Voice 

Licenses for Israel-based Beyond Verbal are already out. Their emotions analytics software’s patented technology helps call centers to personalize and refine their interactions with customers according to the emotional content of an individual’s voice and intonation. 

Vocal biomarkers recognize how we say something, not just what we say. 

Written content

Ixy, a messaging app marketed as a “personal AI mediator,” tells a user how he/she comes across to others based on her text. This aims to remove our email and chat anxiety. Grammarly recently already added “tone” to their app, telling you if you sound neutral, optimistic, admiring, and so on. 

You can see the possibilities of emotion-tracking not just for customer insights but for better delivery of our own messaging. 

I certainly wouldn’t want to send a neutral-sounding email when I aim to uplift or inspire my customers, would I? 

How good are these emotion-tracking AI getting?

The prevalence of the entire gamut of human emotion online gives AI plenty of data to be intelligent enough. With voice recognition joining the fray, the possibilities and opportunities for more insight just ballooned. Microsoft’s Xiaolce in China, Apple’s Siri, Google Assistant, and Amazon’s Alexa all use social and emotional cues. 

You don’t bond with a robotic-sounding AI. You bond with AI that can understand you, talk to you and make you happy. 

This intelligence of emotional AI has helped develop conversational UI already being used to alleviate loneliness in the elderly and as confidential therapists for soldiers with PTSD and others with mental health concerns.

If you think that’s unbelievable, you have to remember that AI trounces us in pattern recognition. This is an already well-known advantage of using AI in sales and marketing, predictive analytics from all the data patterns AI collates. 

Emotions manifest in patterns: facial expressions, visual and audio cues– all these are patterns AI can track and recognize, and they do. 

Gartner VP of Research Annette Zimmerman says, “By 2022, your personal device will know more about your emotional state than your own family.” This was in 2018. And we’re still on this trajectory. 

AI helps human leaders and teams connect the dots

Humans — (maybe not all of us!) — are really good at being empathetic, nuanced, and cutting through bias (among other things), but we’re limited with what we can hold in our heads, and while the super creative among us can connect seemingly disparate dots and come up with interesting ideas to pursue, it’s really tough to connect 1,000 or 10,000,000 dots! 

Business decisions 

AI gives CEOs and team leaders greater visibility; you need to know where this or that project is. Access your project management dashboard. You need to know the buzzword on this or that niche, your most visited pages, or your customer’s top-selling product? AI will have an answer, even if it takes some dialing in to get to the right one. 

This helps leaders apply their own human empathy and expertise to make critical decisions.  

Project or campaign agility

With use and constant iteration and supervision, human teams can help AI become truly intelligent. In time, every AI tools will have a valuable data bank for the logic needed to match its capabilities in speed and scale. 

Human teams need that intelligence, speed, and scale. AI needs human intuition, empathy, and creativity. When combined, AI + human team is much more effective for all marketing and sales campaigns, with the ability to adapt and truly respond to human emotion. 

Defining every brand’s value proposition

Emotional inputs give brands the ability to make deeper, more personal connections with customers. 

We recently discussed the need to adjust your value proposition, and emotional factors can help with that, giving sales and marketing teams prompts toward emotional cues that can help communicate value and great user experience in all strategies and campaigns.  

Are you screening and strategizing for emotional states? 

It’s another facet of buyer intent: emotional state. What do your customers usually feel when they interact with your brand? And how do you want them to feel? I agree with Richard van Hooijdonk: “If a marketer can get you to cry, he can get you to buy.”

That’s enough to trigger a whole slew of ideas. 

As with any ambitious initiative, start small with a pilot, and build out a program when you know what works; incorporating emotion can be tricky so it’s best to test usage. 

And don’t neglect to be transparent with your customers on how you use their information, including emotions. 

You need human teams. Emotional AI is effective aid for human teams when it’s built by emotionally intelligent humans.