In market research, we talk a lot about “clean” data, but not all clean data is created equal. At Canadian Viewpoint, we believe that it’s not enough to simply collect data. You need to know your data is both high-quality and handled with integrity. These two concepts, data quality and data integrity, may sound similar, but they’re not the same. And understanding the difference is crucial to getting data you can trust.
Data Quality vs. Data Integrity
Data quality refers to how accurate, relevant, and complete your data is. Good-quality data reflects real opinions and behaviours. It’s consistent, detailed, and collected in a way that aligns with your research objectives.
Data integrity, on the other hand, focuses on the security, consistency, and traceability of data through every stage, from collection to reporting. Even the most accurate responses lose their value if the data is compromised, mismanaged, or altered along the way.
In short:
- Data quality ensures your results are meaningful.
- Data integrity ensures your results are trustworthy.
You need both to make confident, informed decisions.
Poor-Quality vs. Fraudulent Data
It’s also important to distinguish between low-quality data and fraudulent responses, because they come from different sources and require different strategies.
Low-quality data is often unintentional. It may include:
- Incomplete responses
- Straight-lining through a grid
- Rushed answers or short open-ends
- Confusion due to poorly worded questions
To reduce poor-quality responses, many researchers use a layered approach that includes both automated and manual checks. Common practices include:
- IP validation to confirm respondent location
- Trap questions to assess attention and comprehension
- Red herring brands to catch over-claimers
- Open-end review using AI models trained to flag vague or low-effort answers
- Response quality thresholds to disqualify speeders or disengaged participants
These steps help filter out unengaged respondents before their data can compromise results. We explored these techniques in more detail in our post on how AI and in-survey controls improve open-ended responses.
Fraudulent data, however, is deliberate. It includes:
- Fake respondent identities
- Bot activity or automated tools
- Location spoofing to falsely qualify
- Exaggerated or fabricated answers to trigger incentives
For instance, someone might use a disguised IP address to appear eligible for a Canada-only study, or falsely claim they purchase high-end luxury products weekly to be selected for a premium panel. These aren’t signs of fatigue, they’re signs of deception.
Our Commitment to Reliable, Secure Research
At Canadian Viewpoint, we take both quality and integrity seriously. We’ve built our processes to address both dimensions with rigour and accountability. Here’s how:
Technology + Human Oversight
We pair advanced fraud detection tools with real human review. Our system flags unusual behaviour like inconsistent answers or abnormal completion times, and our Project Management team manually verifies open-end quality and response logic. This hybrid approach ensures nothing falls through the cracks.
Cheque Payments for Verification
We pay our respondents by physical cheque, which adds a layer of identity confirmation and makes it harder for fraudsters to game the system. We explored this approach further in our post, Physical Cheque Payments: Still the Gold Standard.
Vetted Sample Partners
We work only with sample providers who meet our strict data sourcing and validation criteria. Our sampling practices are explained in more detail in our blog, 5 Ways to Ensure High Quality Online Samples.
Quality Control Handbook
Our Quality Control Handbook outlines the detailed processes we use to uphold data quality, from pre-survey validation and fraud detection to open-end reviews and data checks. It reflects over 40 years of experience and a deep commitment to transparency and consistency.
We’ve Signed the Data Quality Excellence Pledge
As proud signatories of the Data Quality Excellence Pledge, we’re part of a global commitment to raising the bar on ethical and transparent research practices.
Accredited CRIC Member
Canadian Viewpoint is an accredited member of the Canadian Research and Insights Council (CRIC), which means we uphold Canada’s highest standards for data collection, privacy, and respondent rights. CRIC’s Client’s Guide to Data Quality in Online Research (PDF) provides a valuable framework for evaluating quality at every stage of a project and we proudly align our practices with its principles.
Setting the Standard for Trustworthy Data
As data fraud becomes more sophisticated and respondent behaviour evolves, maintaining both quality and integrity isn’t a nice-to-have, it’s a necessity.
At Canadian Viewpoint, we don’t take shortcuts. We invest in the people, tools, and practices that ensure every data point we deliver is defensible, relevant, and ethically sourced.
We are committed to setting the highest standards in data quality. To learn more about the processes that ensure every project we deliver is of the utmost integrity, download our Quality Control Handbook and see how we deliver results you can trust, every time.
Ready to discuss data quality for your next project? Let’s connect!
