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Learn to Speak Your Customers’ Language—With AI

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

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In the first part of Chris Silvestri’s series on empathy engineering, his framework for simulating customers using AI, he wrote about the process of gathering and analyzing data. In the second part of this four-part series, he actually breathes life into his new AI personas, creating the virtual sounding boards to write and test marketing messages.—Kate Lee

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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.

Source: The User Illusion by Tor Nørretranders, 1991.

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:

  1. Identity: Who are they?
  2. Motivation: What do they care about?
  3. Evaluation: How do they evaluate products?
  4. Resistance: What is holding them back?
  5. Vision: What does success look like for them?

Let’s work through each using our case study about TeamFlow—our made-up company from part one—as an example.

1. Identity

As we define our personas' identities, we'll be laying the groundwork for how they'll interpret our marketing messages later on. Based on our initial customer research, I prompted Google's Gemini 1.5 Pro to generate three distinct ideal customer profiles (ICPs), each representing a different segment of TeamFlow's target audience.

You can see the prompt I used and the AI's response in the screenshots below. Here it is for you to use and adjust if needed:

Now, based on [types of research materials you’ve shared e.g. customer interview transcripts etc.], let’s extract data for our Ideal Customer Profiles (ICPs) using the following format:

#Example format:

  • Name: [Customer’s name or pseudonym]
  • Role: [Customer’s job title, e.g., Sales Manager]
  • Company: [Description of company size, industry, and location, e.g., A mid-sized tech company (50-200 employees) based in Minneapolis, Minnesota]
  • Demographics: [Customer’s age, gender, identity attributes, education background, e.g., 35 years old, female, identifies as Latina, has a bachelor’s degree in Marketing]
  • Values: [Key values that drive the customer, e.g., Efficiency, collaboration, work-life balance, personal growth, and building strong relationships with their team]
  • Goals: [Customer’s main goals, e.g., Increase sales revenue, hit quarterly targets, build a high-performing sales team, and advance in sales leadership]
  • Personality: [Key personality traits that describe the customer, e.g., Outgoing, driven, organized, empathetic, and a strong communicator]

Write me a set of these per each of our [number] of ICPs.

Notice how each persona has a unique set of demographics, values, goals, and personality traits, all informed by the research data we gathered in part one.

Source: Screenshots from Google Gemini 1.5 Pro.

Our prompt returned the most important factors we need to consider when it comes to our customers making a buying decision for our product—their name, role, company, demographics, values, goals, and personality.

2. Motivation

When defining a customer’s motivation, they are translating your promises into emotional experiences. They could feel pride, relief, or reduced stress. If you're selling project management software, the idea of “hitting deadlines” might evoke a feeling of accomplishment and control for one person, while for another, it might trigger anxiety and a fear of failure based on past experiences.

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