Market research teams are making high-stakes decisions using data that is increasingly unreliable. The real question is no longer if survey fraud exists, but how much of your data is compromised.
How bad is it?
These aren’t edge cases. Fraud is now a systemic issue across online surveys. A 2025 study across six leading online sample sources flagged more than 30% of respondents as suspicious or outright fraudulent [source]. A peer-reviewed study in Frontiers in Research Metrics found that usable responses from online surveys dropped from 75% to just 10% in recent years [source].
And it’s getting worse
Three forces are colliding:
Industrialized fraud rings are running survey farms with trained workers and stolen identities.
Sophisticated AI-powered bots are using LLMs to complete surveys, passing 99.8% of standard quality checks. A Dartmouth researcher found that these AI responses are essentially indistinguishable from real people.
Outdated defenses like CAPTCHAs, IP filtering, and attention checks are increasingly ineffective. Bad actors use VPNs, device spoofing, browser emulators, and cookie clearing to avoid detection.
Why fraud is so dangerous
Fraud doesn’t usually create obvious outliers. Instead, it quietly flattens data. Fraudulent respondents select fewer brands, show weaker preferences, and create false patterns that look “clean” but are wrong.
The result: millions are spent on product, messaging, and strategy decisions built on corrupt data. Organizationally, as markets invalidate decisions, trust in research itself erodes.
This creates several problems:
Business decisions are based on fiction. Product teams believe a feature is a hit when the audience never wanted it. Marketers target segments that don't actually exist. Brands chase trends that only appear in bot-generated responses.
Confidence in research erodes. When stakeholders discover data quality issues, they question everything. Research teams spend more time defending methodology than generating insights.
Resources get wasted twice. First on the compromised study. Then on the cleanup, rerun, and investigation that follows. Research teams end up hiring more staff for fraud detection instead of insight generation.
Why surveys are fundamentally vulnerable
Surveys combine incentives, anonymity, asynchronous completion, and scale, the perfect setup for bots and click farms. The industry response has been better detection and cleaning, but that’s an arms race researchers are losing.
This isn’t a tooling problem. It’s a structural one.
A fraud-resistant alternative: voice
When people have to talk, fraud falls apart. Conversation makes identity harder to obfuscate and data becomes much richer. Participants tell stories. They go off-script in ways that reveal genuine perspectives. The data is deeper, and the barrier to fraud is materially higher.
What research teams should do now
Audit data quality aggressively and demand transparency from panel providers
Reduce dependence on incentive-driven panels
Diversify methods beyond surveys
Conduct voice conversations at scale to gain both qualitative and quantitative insights
Where Keplar Fits In
Keplar was built for this moment. Our AI voice interviewer conducts natural, 1:1 conversations at scale, delivering qualitative depth in days instead of weeks without relying on fragile, fraud-ridden surveys.
Unlock qual at quant scale.
Every Keplar conversation is stored in a centralized, queryable repository, turning each study into a lasting evidence asset. Researchers can re-mine past conversations with new questions to surface fresh insights without re-fielding. Because the data is conversational and deeply indexed, it compounds in value rather than going stale.
Curious how voice-based research can reduce fraud and deliver deeper insight? Try out the Keplar Voice AI moderator for yourself here or book a meeting with us here.