PureScore™ vs. The Industry Standard: A Deep Dive into Multi-Device Fraud Prevention.
Data Quality In Online Sample
Today everyone, including survey respondents, can be increasingly anonymous online. This anonymity offers a host of issues in quantitative research, such as panel duplication, fraudulent responses, and responses from click farms or bots. Survey fraud has become an ever-morphing game of cat and mouse, requiring deduplication and fraud mitigation techniques to be fluid and dynamically adaptable.
Is Device Fingerprinting Enough?
To benefit from multiple panels, researchers need tools to prove that they can trust that respondents are unique, honest, and engaged. Device fingerprinting has become the online sample industry-standard data quality methodology. But what is device fingerprinting as it relates to market research? Device fingerprinting is a data quality technique that tracks a device to recognize if it has already responded to an online survey. Is panel quality really on the decline? puts device fingerprinting in context, examining three years of PureSpectrum reconciliation data to show what happens to quality metrics when behavioral profiling is layered on top of device checks. Respondents are terminated if their device has participated in the same study through another panel. But what if the respondent uses multiple devices to access the same survey? A solution is needed to look at respondents longitudinally, beyond a single session or device.
Why PureScore™ Is Different
To answer this need, PureSpectrum has developed tools that offer visibility into respondent behavior beyond device fingerprinting and single-session behavior. Each respondent sourced on the PureSpectrum platform is screened by PureScore™ and supported by data scientists and quality analysts.
Below we demonstrate the two commonalities shared between device fingerprinting and PureScore™, but also the critical data quality tools that only PureScore™ brings to online sample collection:
PureScore™ technology effectively profiles the present and past behavior of the respondents to evaluate their credibility, reliability, and consistency in surveys. The further a respondent’s fraud markers and behaviors deviate from the ideal, the lower their PureScore™. Only respondents with a passing PureScore™ direct to PureSpectrum surveys.
Continuously Working to Ensure Reliability of Survey Data
PureSpectrum is committed to providing industry-leading data quality methodologies. As sample buyers’ expectation for quality respondents increases, PureScore™ will ensure they always reach them. Earlier this year, we introduced PureText™, which works in conjunction with PureScore™—utilizing natural language processing technology, PureText™ screens respondents based on their textual responses to open-ended questions. You can read more about PureText in our article, Announcing PureText™.
By constantly advancing methods to catch and prevent potential fraud and increasing data validity and reliability, PureSpectrum works hard to set the standard for data quality in the online market research industry. For the 2025 view of where that standard is being tested, specifically by AI-assisted mid-survey fraud, the 2025 quality shift: a practical look at AI fraud and PureScore™ 5.0’s new safeguards covers this in detail.
Ready to experience the PureSpectrum data quality difference? Reach out to our team below: