| Summary: | 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.
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