Not all, but some researchers have accepted that survey fraud creates statistical “noise,” random data that can be diluted with larger sample sizes. Not so!
See what we found on "noise vs. bias" in survey fraud.
At it's worst, entire segments of your dataset may lean in a direction that:
- Misrepresents reality.
- Leads to skewed insights.
- Creates inaccurate conclusions.
- Ultimately flaws business decisions.
When fraudulent respondents answer similarly, they aren’t canceling each other out. They’re creating patterns that look real but aren’t. A biased dataset can:
- Convince you that a product is preferred when it’s not.
- Show that a market segment is viable when it’s saturated.
- Highlight a trend exists when it’s entirely fabricated.
And that wastes budgets, misdirects strategy, and erodes stakeholder trust.
Don’t just try to suppress noise, fight bias at the source.
See how in this video.
