Synthetic vs Traditional vs Consumr.AI
There are three ways to do consumer research. Two of them are broken by design.
Approach 1: Synthetic / LLM-based research
Section titled “Approach 1: Synthetic / LLM-based research”Synthetic research tools let you spin up thousands of fake respondents and ask them whatever you want. They rely on the central limit theorem: flip a coin enough times and the distribution averages out into something that looks like a real population signal. Run 10,000 simulated respondents, and something will stick.
The problem is not the math; these tools tell you what you want to hear.
Think about the Tom Cruise story. Matt Damon recounted it: Tom Cruise had planned for 20 years to do the Burj Khalifa stunt himself. He went to his stunt director and said he wanted to do it. The stunt director said it was too dangerous; you cannot do this. Tom Cruise fired him and hired someone who would say yes.
That is the default mindset of most research clients. They do not want the truth. They want a validator. Synthetic tools are built to serve that instinct. Ask a leading question, run it at scale, and you will get back something that confirms what you already believed.
The pathology analogy makes this even clearer. When did you last walk into a lab unprompted and say “I want a blood test, no doctor, no symptoms, just checking”? Almost nobody does that. People do not go looking for bad news. They look away. And if the doctor says “your ECG is concerning but not dangerous,” they go back to their regular lifestyle immediately. The moment the doctor says “you have a 90% risk of a heart attack in the next month”: then they change. Synthetic research exploits this same avoidance instinct: it will tell you the reading is fine.
Approach 2: Traditional research
Section titled “Approach 2: Traditional research”Traditional research firms send people into the field. They meet 2,000 to 3,000 real consumers, conduct interviews, run focus groups, analyze the results. This is expensive and slow: six months from brief to insight is typical.
The market moves on. By the time you have your findings, the conditions you were researching no longer exist. You cannot go back to the same people either: the moment the interview is over, they are gone. If a question comes up in analysis that you did not ask in the field, you pay again to go find new people and start over.
Humans lie, not always consciously, but reliably. Everyone carries a version of themselves they present publicly, and that version is flattering. In a focus group, this effect is amplified by peer pressure. Nobody in a focus group is going to say “I go to Walmart because I’m stingy.” But if you get 20 people in a room who all shop at Walmart for price reasons, every single one of them is stingy. They just will not say it. The one person who does say it gets discarded as an outlier.
The person they show you in a survey is not the person who makes decisions at the shelf.
Approach 3: Consumr.AI
Section titled “Approach 3: Consumr.AI”Consumr.AI starts from a different premise. Millions of people talk openly on social media every day, not to a researcher, not in a focus group, not because someone asked them. They post, comment, complain, and recommend in environments where social desirability pressure is low. They already said what they think. They cannot unsay it.
Consumr.AI ingests those signals and builds a single AI twin that represents the cohort. That twin does not reflect what people say when someone is watching them. It reflects what they actually said when no one was conducting a study.
The result: one AI twin that speaks for a real audience, grounded in real behaviour, available right now, not in six months.
“We back ourselves with millions of people who are on social media talking stuff. We take feedback from them and have one AI twin who represents all of them and tells you exactly what they are going through.”
The myth to bust
Section titled “The myth to bust”The loudest objection you will hear from clients is not “this doesn’t work.” It is the unstated assumption that research exists to confirm what they already decided. They are looking for a validator, not a truth-teller.
The stunt director who told Tom Cruise the Burj Khalifa stunt was too dangerous was right. He got fired anyway, because being right was not what was wanted.
Your job, when presenting Consumr.AI, is to reframe what research is for. Research that only confirms existing assumptions is not research; it is expensive reassurance. The value of accurate consumer insight is exactly proportional to how willing you are to act on findings that surprise you.