Event FinderData Quality in the Age of AI: A framework for defensible survey research
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About This Event
Most researchers never get a clear look at what's actually happening inside their own studies. The data comes back, the charts get built, decisions get made, but where the problems entered, how they were caught, and what the survey design itself did to the results usually stays invisible. Across the industry, that blind spot is big: research-on-research scans of billions of survey attempts put fraud at roughly a third of all traffic and inattentive responses at roughly a quarter, with up to 70% of that fraud slipping past standard data cleaning. The "clean" dataset most teams report isn't always what they think it is. Jonathan Goodbread, aytm's Head of Data Quality Strategy, walks through a practical framework for evaluating data quality across the full arc of a study. aytm's own Data Quality Benchmark Report landed to strong response earlier this year, and a second wave of the report is arriving this fall alongside a new per-study Data Quality Report tool. Attendees will leave with a framework they can apply to their own research programs right away.