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data, different statistical methods and models can give different readings. Gray states, “Causation requires correlation of some kind but correlation and causation are not the same.”
When looking at probabilities and categories, Gray cautions the researcher to, “Avoid confusing the possible with the plausible and the plausible with fact. It’s also not difficult, though, to miss something of genuine practical significance that lies hidden beneath…
Highly satisfied customers = revenue dollars. Or do they? Some data has shown that the relationship between customer satisfaction and customer spending behavior is surprisingly weak. In this article, the authors share their analysis of the relationship between satisfaction and business outcomes, gathering data from more than 100,000 consumers covering more than 300 brands. This data came from two sources, the American Satisfaction…
Using a philosophy of test and learn, Heinz looks to multiple information sources for research, including electronic-point-of-sale, Nielsen data, panel data, and social media and brand monitoring. One such panel, Heinz 57, is an online community of 300 consumers that the company uses as a source of customer feedback.
Analysis of actual shopping behavior conducted from mobile devices suggests that conventional definitions of seasonal shopping behaviors are being disrupted by mobile shopping. Beyond the powerful implications for marketers in general, this also has implications for market researchers who may be timing research on purchase plans and branding around seasonal shopping assumptions.
On a survey, do you check “yes” the same amount as someone in India? Probably not! Cultural differences in multi-country surveys yield inaccurate results. Propensity to agree, untruthfulness, and survey “speeders” vary from country to country.
