The Synthetic Data Problem: What Your Research Vendor Isn't Telling You
How a 31% AI error compounds into bad media decisions
AI tools are everywhere in marketing, but using AI to simulate customer survey data is one shortcut that’s quietly distorting the decisions brands make every day. Most don’t realize their media, creative, and pricing strategies could be built on audience data that’s statistically inaccurate.
This whitepaper shows you exactly what’s at stake when you choose to use synthetic data, and what to use instead.
Download the Research
AI tools are everywhere in marketing, but using AI to simulate customer survey data is one shortcut that’s quietly distorting the decisions brands make every day. Most don’t realize their media, creative, and pricing strategies could be built on audience data that’s statistically inaccurate.
This whitepaper shows you exactly what’s at stake when you choose to use synthetic data, and what to use instead.
Inside You’ll Learn:
Why synthetic survey data is systematically wrong – the four built-in AI biases that make simulated responses diverge from real consumers.
Where AI actually belongs in your research stack – the right division of labor between AI analysis and real consumer data.
Red flags to audit your current vendors – six questions to find out if the data you’re buying is real or AI-generated.
The downstream cost of bad data – how a 31% AI error compounds into mispriced positioning, media spend, and creative.
