A statistical method for estimating piecewise linear sales trends

Taku Moriyama (), Masashi Kuwano and Masahito Nakayama
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Taku Moriyama: Tottori University
Masashi Kuwano: Tottori University
Masahito Nakayama: Tottori University

Journal of Marketing Analytics, 2024, vol. 12, issue 2, No 23, 436-444

Abstract: Abstract Due to the structural breaks in time series, estimated current trend of product sales differs between the case where data for the entire span are used and the case where only the most recent data are used. The purpose of this study is to establish the piecewise linear approximation (PLA) as a trend analysis method that accounts for the structural breaks. PLA uses the complete data to simultaneously estimate the breakpoints and the continuously connected trends, immediately before and after the break. Thus, PLA not only ensures the ease of interpretation of the results, but also eliminates the probability of using discretion by uniquely determining the current trend, making the estimated result reliable. The case study demonstrates the proposition that, several products’ sales trends and the necessity of determining an appropriate time span for data analysis, underwent changes at least once. The method’s validity is demonstrated by showing the changes of the sales trends immediately after analyzed store’s renovation. Data collection from the time period immediately prior to a structural break can help identify the factors changing the product sales.

Keywords: Trend analysis; Structural break; Time series analysis; POS data; Piecewise linear approximation (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1057/s41270-023-00207-9

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