End users of research often extrapolate from crosstab columns with small sample sizes, despite provided caveats. Unfortunately, such crosstabs overstate differences between subgroups. By adopting Bayesian averages, a technique that e-commerce companies use in product reviews, market researchers can present crosstabs with greater predictive validity. Each column is blended with overall responses to calculate the Bayesian average. A 1,000-record subset of a survey of 6,000 U.S. adults was used to prove the validity of the technique: 60% of the Bayesian averages from the subset were closer to the final results, while only 34% of the traditional crosstabs were closer (6% tied). This simple technique can be applied in Excel and does not require any specialized software, or researchers can use ResearchStory to generate Bayesian crosstabs.
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Author Notes:
Jeffrey Henning
Jeffrey Henning, IPC is a professionally certified researcher and has personally conducted over 1,400 survey research projects. Jeffrey is a member of the Insights Association and the American Association of Public Opinion Researchers. In 2012, he was the inaugural winner of the MRA’s Impact award, which “recognizes an industry professional, team or organization that has demonstrated tremendous vision, leadership, and innovation, within the past year, that has led to advances in the marketing research profession.” In 2022, the Insights Association named him an IPC Laureate. Before founding Researchscape in 2012, Jeffrey co-founded Perseus Development Corporation in 1993, which introduced the first web-survey software, and Vovici in 2006, which pioneered the enterprise-feedback management category. A 35-year veteran of the research industry, he began his career as an industry analyst for an Inc. 500 research firm.
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