Data Quality
Preventing Fraud Before it Happens
Paradigm’s philosophy centers on prevention, not just detection. Our approach is built on several core principles: Client-Centric Approach Every project is unique. We tailor tools, quality checks, and parameters to meet each study’s specific goals and audience characteristics. Reliable Data Starts with Reliable Partners Paradigm is building a Partner Evaluation Framework that integrates performance metrics from…
Read MoreParadigm’s Integrated Approach to Data Quality
At Paradigm Sample, we take a holistic approach to data quality that combines technology, human judgment, and process discipline. Across every phase of the fielding process, our Veraproof Suite is much more than a technical implementation it’s a methodology that combines best in class proprietary and 3rd party tools into an overall process designed to ensure…
Read MoreExploring the influence of AI and Synthetic Data at ESOMAR NA 2025
This year’s ESOMAR North America conference highlighted a central theme: exploring the landscape of research as it is increasingly shaped by AI and synthetic data. Whether leveraging AI for generating outputs or synthetic data for forecasting election results, there we see a strong a connection to how Paradigm approach’s data quality in quantitative sampling. AI’s…
Read MoreParadigm signs the Global Data Excellence Pledge
Global Data Quality (GDQ) Pledge – a global collaboration led by organizations like MRS, ESOMAR, Insights Association, SampleCon, and more. Its core purpose is to establish a global, cross-industry standard for trustworthy, high-quality data -especially in market and social research, analytics, and insights. This pledge upholds our dedication to data quality as it requires a…
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