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Regression modelDiscrete choice on household panel data

Scanner Panel Analysis

Scanner panel analysis models individual households' brand choices using the purchase histories captured by UPC scanner panels, in which the same households are tracked occasion by occasion with the brand chosen and the prices and promotions they faced. The defining method is Guadagni and Little's 1983 multinomial logit of brand choice, the first model to put scanner panel data to serious analytical use. Its signal innovation is the loyalty variable: an exponentially smoothed measure of each household's past brand purchases that enters the utility function and captures persistent brand preference and state dependence. Alongside loyalty, the model includes price, promotion, and brand intercepts, and yields the probability that a household buys each brand on a given occasion. From the fitted model one recovers price and promotion elasticities at the individual level and can simulate how marketing actions shift choices. The framework launched the modern era of disaggregate choice modeling and remains the reference point for scanner-based brand-choice analysis.

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  1. Guadagni, P. M., & Little, J. D. C. (1983). A Logit Model of Brand Choice Calibrated on Scanner Data. Marketing Science, 2(3), 203-238. DOI: 10.1287/mksc.2.3.203
  2. Van Heerde, H. J., Gupta, S., & Wittink, D. R. (2003). Is 75% of the Sales Promotion Bump Due to Brand Switching? No, Only 33% Is. Journal of Marketing Research, 40(4), 481-491. DOI: 10.1509/jmkr.40.4.481.19386

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ScholarGate. (2026, June 23). Scanner Panel Analysis (Guadagni-Little Brand-Choice Logit). ScholarGate. https://scholargate.app/no/marketing/scanner-panel-analysis

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ScholarGateScanner Panel Analysis (Scanner Panel Analysis (Guadagni-Little Brand-Choice Logit)). Hentet 2026-06-24 fra https://scholargate.app/no/marketing/scanner-panel-analysis · Datasett: https://doi.org/10.5281/zenodo.20539026