Abstract
The execution of price and/or display promotion has a significant effect on the sales of a brand sold in a supermarket. Information on price and/or sales is available from POS data. However, unless an investigator collects information on the execution of display promotions from every retail store, such information is unavailable. This paper presents a method of identifying whether display promotion has been executed without having to visit individual stores. We treat the execution/non-execution of a display promotion as a state variable. An unknown stationary probability matrix is assumed to describe the probability of a transition between states. Each state is characterized by a different stationary time series model with unknown parameters. The objective of the analysis is to identify the model and to assign a probability model for each state at each time instant. Finally, we provide a high precision estimator of a past execution/non-execution of a display promotion based on the proposed model.
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Sato, T., Higuchi, T. & Kitagawa, G. Statistical Inference Using Stochastic Switching Models for the Discrimination of Unobserved Display Promotion from POS Data. Marketing Letters 15, 37–60 (2004). https://doi.org/10.1023/B:MARK.0000021969.52674.03
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DOI: https://doi.org/10.1023/B:MARK.0000021969.52674.03