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Market Basket Analysis of Basket Data with Demographics: A Case Study in E-Retailing

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  • Ural Gökay Çiçekli
  • İnanç Kabasakal

Abstract

Businesses overcome with a high degree of competition that necessitates customer-focused strategies in most industries. In a digitalized business environment, the implementation of such strategies often requires the analysis of customer data. Market basket analysis is a well-known method in marketing that examines basket data to discover useful information about customers’ purchase intentions. The analysis has been a playground for data mining researchers that aim to overcome with its practical challenges. Our study extends the conventional basket analysis by incorporating demographic variables along with purchase transactions. With such modification, we provide an example for the extraction of segment-specific rules that relate product-level purchase decisions with gender, location, and age group. For this purpose, we present a case study on monthly basket data obtained from an e-retailer in Turkey. Our findings demonstrate association rules that might guide marketing practitioners who need to discover segment-specific purchase patterns to designate personalized promotions.

Suggested Citation

  • Ural Gökay Çiçekli & İnanç Kabasakal, 2021. "Market Basket Analysis of Basket Data with Demographics: A Case Study in E-Retailing," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 9(1), pages 1-12, June.
    • Handle: RePEc:anm:alpnmr:v:9:y:2021:i:1:p:1-12
    DOI: http://dx.doi.org/10.17093/alphanumeric.752505
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    References listed on IDEAS

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    1. Katrin Dippold & Harald Hruschka, 2013. "Variable selection for market basket analysis," Computational Statistics, Springer, vol. 28(2), pages 519-539, April.
    2. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
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    1. Yuliia Biliavska & Yevgeny Romat & Valentyn Biliavskyi & Olena Sydorenko & Tetiana Ostapenko, 2024. "Diagnosing category management in a pharmacy retail chain," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 1(13 (127)), pages 22-32, February.

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    More about this item

    Keywords

    Association Rule Mining; Data Mining; Demographic Association Rules; Market Basket Analysis;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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