Stereotypes Are a Real Time (and Money) Saver
Featured in a session at the Advertising Research Foundation (ARF) ReThink Conference in 2015, this paper presents data about the types of questions (and answers) that are better predictors of consumer attributes beyond age, gender, and other core demographics. Our data science team looked for meaningful associations between different subsets of survey respondents, based on 608 questions from our syndicated question library.
Consumer Insights Through the Windshield, Not The Rearview Mirror
A top 10 paper at the Advertising Research Foundation (ARF) ReThink Conference in 2014, we use CivicScience’s methodology to demonstrate forward-looking research possibilities and to identify ‘predictive’ consumers.
Assessing the Research Methodology, Validity, and Representativeness of CivicScience Survey Data
Authored by Dr. L. Pierce, Dr. A. Chatterji, Dr. J. Snyder, and Dr. A. Acquisti, academic advisors to CivicScience who conducted an analysis of CivicScience’s data collection, quality assurance, reporting techniques, demographic representativeness, and specific use case examples.