Knowing your customers has always been the holy grail of marketing. But until recently, the best tools we had were surveys, interviews, and guesswork. Generative AI changes that by offering a faster, cheaper, and potentially more accurate way to simulate how customers think and behave.

At the core of this approach is what Chris Silvestri calls empathy engineering: training AI to reflect your customers’ needs, emotions, and decision-making patterns. Instead of replacing human research, it amplifies it—combining internal team knowledge, direct customer feedback, and competitive analysis to create a full picture of what drives buying behavior.

The framework starts with your team. Customer support logs, sales conversations, and analytics contain invaluable clues about pain points and desires. Layer on user interviews, surveys, and behavioral testing, and you get real voices and data that AI can then synthesize into patterns. Finally, studying competitors reveals gaps and opportunities where your message can stand out.

What makes AI powerful here isn’t just speed, but perspective. Properly prompted, it can roleplay as your ideal customer, challenge assumptions, and generate new hypotheses. It becomes less of a tool for output and more of a partner in strategy—one that helps refine messaging, test positioning, and spot hidden opportunities.

The result: sharper marketing, faster iteration, and a deeper connection with your audience. Teaching AI to understand your customers doesn’t eliminate the human touch—it magnifies it, ensuring that every message feels personal, relevant, and aligned with what people truly need.