Synthetic Data: It Sucks, Says Designers
April 25, 2025
Some would argue taking actual customers out of market research is a bad idea. Smashing Magazine supports that reasonable perspective in, “How to Argue Against AI-First Research.” Yes, some AI enthusiasts praise synthetic user testing as a valuable new tool. The practice is exactly what it sounds like—using LLMs to build fake customers and performing market research on them. Admittedly, it is much faster and cheaper than surveying actual humans. But what good is that if the results are bad? Writer Vitaly Friedman explains:
“When ‘producing’ user insights, LLMs can’t generate unexpected things beyond what we’re already asking about. In comparison, researchers are only able to define what’s relevant as the process unfolds. In actual user testing, insights can help shift priorities or radically reimagine the problem we’re trying to solve, as well as potential business outcomes. Real insights come from unexpected behavior, from reading behavioral clues and emotions, from observing a person doing the opposite of what they said. We can’t replicate it with LLMs.”
But budgets are tight. Isn’t synthetic user data better than nothing? No. No it is not. We learn:
“Pavel Samsonov articulates that things that sound like customers might say them are worthless. But things that customers actually have said, done, or experienced carry inherent value (although they could be exaggerated). We just need to interpret them correctly. AI user research isn’t ‘better than nothing’ or ‘more effective.’ It creates an illusion of customer experiences that never happened and are at best good guesses but at worst misleading and non-applicable.”
Not only that, cutting real customers out of the equation means not catching AI errors. And there will be errors. Furthermore, emphasizes Friedman:
“Synthetic testing assumes that people fit in well-defined boxes, which is rarely true. Human behavior is shaped by our experiences, situations, habits that can’t be replicated by text generation alone. AI strengthens biases, supports hunches, and amplifies stereotypes.”
All of which could send marketing dollars down the wrong, unprofitable track. As suspicious as we are of AI hype, even we can admit the tech is good for some things. Market research perhaps is not a core competency.
Cynthia Murrell, April 25, 2025
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