Learn to Speak Your Customers' Language—With AI

DALL-E/Every illustration.

Learn to Speak Your Customers' Language—With AI

A five-step framework for decoding what people actually hear when we talk to them

Words are not static. They don't have fixed meanings that everyone universally understands.

Nowhere is that more true than in marketing. What you say isn’t always what your customers hear.

In his 1999 book The User Illusion, cognitive scientist Tor Nørretranders introduced a framework called the "tree of talking." He argues that communication is a process of compressing vast amounts of information into a few words. When we speak or write, we're creating a condensed version of our thoughts and experiences.

But the person receiving that message then has to unpack those words, interpreting and personalizing them based on their own experiences, associations, and memories. The same phrase can evoke completely different reactions in different people. The words "team productivity" might trigger positive emotions in someone who thrives on collaboration and efficiency, but negative emotions in someone who associates it with overbearing micromanagement and chronic burnout.

For our empathy engineering framework, we're not just building AI personas that understand words—we're creating personas that unpack meaning. We want to use AI to simulate how real people would react to marketing messages, taking into account their unique backgrounds.

We can use the tree of talking to create emotionally nuanced and human-like AI personas. This is not your typical customer persona. Think of it like the difference between a flat, two-dimensional character in a 1980s video game and one you meet in a modern VR experience.

Five steps to building AI personas that react like humans

In order to simulate how our ideal customers unpack the meaning and emotional weight behind the words we use in our marketing, we need to deconstruct their personality and decision-making process. The following are the building blocks of our virtual customer: