Empathy in Marketing: The One Thing Synthetic Audiences Can’t Fake
Empathy in marketing means understanding what your buyer fears, hopes and needs to believe before they’ll move, and building your message from there. AI made that skill worth more. Synthetic audiences can now stand in for customers in early research, and they’re useful. But they fail in a specific direction: they’re too positive and too alike. Real buyers are anxious, divided and stubborn. Empathetic marketing starts with the real ones.
Originally published March 4, 2024. Rewritten for the AI era on October 26, 2026.
What is empathy in marketing?
It’s starting where your buyer lives, not where your product sits.
Everyone you sell to is on a personal and a professional journey. If you don’t start where they live, breathe, fear and celebrate, your message is noise to them. Show them you understand the outcomes they want, personally and for their business, and they’ll begin to trust you, engage more openly and, in time, buy.
That was the heart of this article when I first wrote it, and of the talks I’ve given on empathy-based strategy. What’s new is the shortcut that now tempts every marketing team.
Can AI stand in for real customers?
For some early questions, yes. For the ones that decide a budget, not yet.
“Synthetic respondents” are AI models asked to answer survey questions as if they were a person with a given profile. Researchers at NIM (Nürnberg Institut für Marktentscheidungen) tested them in a realistic brand-funnel study. The synthetic answers matched real participants’ brand choices about 79% of the time and captured broad trends. But they consistently overestimated positive attitudes, especially toward well-known brands. On a 7-point scale, they were off by 1.2 points on average. And they showed significantly less variation than real people (NIM Marketing Intelligence Review).
The researchers’ own conclusion: synthetic data “may currently be most suitable for early-stage concept testing or lower-stakes applications, rather than decisions requiring precise insights.”
Think about what “too positive and too uniform” means. The synthetic customer likes you more than the real one does, and every synthetic customer feels about the same. That erases the two things empathy exists to find: the fear that stops a deal and the difference between one buyer and the next.
| Use synthetic respondents for | Go to real buyers for |
|---|---|
| A fast first read on many concepts | The fear that actually stops the deal |
| Spotting broad patterns | How one buying group differs from another |
| Drafting questions to ask real people | Whether your proof is believable |
| Low-stakes, early decisions | Positioning, pricing and anything you’ll bet a budget on |
Why does empathy matter more when AI writes the message?
Because buyers can tell, and many don’t like what they see.
Cint surveyed about 1,000 U.S. consumers in August 2026. Seventy-four percent said brands have a duty to disclose when AI is used in advertising, and 44% said finding undisclosed AI-generated advertising would lower their trust in a brand. AI-generated people were the most disliked kind of AI creative tested: 46% said they dislike seeing them in ads (Cint).
B2B buyers show the same instinct at the moment of risk. In Gartner’s survey of 645 B2B buyers, 69% said they prefer to validate AI-generated insights with a sales rep. Gartner says buyers rely on reps when they “need reassurance, context and decision support” (Gartner). Reassurance is an emotional need. A machine can gather facts. People still want a person to tell them it’s safe.
How do you practice empathetic marketing in the AI era?
Use AI for speed, and spend the time you save with real buyers.
- Listen before you write. Sit in on sales calls, read win/loss notes and talk to customers who almost didn’t buy. That’s where the fears are.
- Name the fear in the buyer’s words. “We can’t afford another failed rollout” beats “seamless implementation.”
- Answer the fear with proof. A named example or a result a buyer can check does more than any promise.
- Test with machines, decide with people. Run synthetic panels to narrow ideas, then check the finalists with real buyers.
- Show the human. Disclose how you use AI, and keep real customers and real team members in your story.
I’ve seen what it does when a message shifts from the product to the buyer’s outcome. In 2020, during my D Custom years, our work on McKesson’s pitch reduced price pressure and increased its win rate. When buyers feel understood, they stop shopping on price alone.
Empathy also lives in stories. For why stories move people, and why true ones matter more now, see Why We Like Stories. For turning buyer understanding into a position, see chapter 1 of our guide on brand positioning.
Where do you start?
Pick your last lost deal. Call the buyer and ask what worried them. Then read your homepage and see whether it answers that worry. If you’d like a senior partner to work through it with you, talk to me about advisory support.
A synthetic customer will always like you. That’s why you can’t learn much from it.
