• ISSN: 2148-2225 (online)

Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

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

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Ural Gökay Çiçekli, Ph.D.

İnanç Kabasakal, Ph.D.


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.

Keywords: Association Rule Mining, Data Mining, Demographic Association Rules, Market Basket Analysis

Jel Classification: C01

Suggested citation

Çiçekli, U. G. & Kabasakal, İ. (). Market Basket Analysis of Basket Data with Demographics: A Case Study in E-Retailing. Alphanumeric Journal, 9(1), 1-12. http://dx.doi.org/10.17093/alphanumeric.752505

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Volume 9, Issue 1, 2021

2021.09.01.MIS.01

alphanumeric journal

Volume 9, Issue 1, 2021

Pages 1-12

Received: June 13, 2020

Accepted: Jan. 26, 2021

Published: June 30, 2021

Full Text [552.3 KB]

2021 Çiçekli, UG., Kabasakal, İ.

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

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