USING MARKET BASKET ANALYSIS TECHNIQUE TO FIND CONSUMER PURCHASING PATTERNS AND OPTIMIZE INVENTORY MANAGEMENT

KASA HALILI, Merita and HALILI, Festim and RUSTEMI, Avni and Rufati, Eip and SELIMI, Aliadis (2026) USING MARKET BASKET ANALYSIS TECHNIQUE TO FIND CONSUMER PURCHASING PATTERNS AND OPTIMIZE INVENTORY MANAGEMENT. In: INTERNATIONAL CONFERENCE “FROM RESEARCH TO APPLICATION”, 20 May, 2026.

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Abstract

Market Basket Analysis (MBA) is a data mining technique that plays a key role in finding consumer purchasing patterns to aid in optimizing inventory management and marketing strategies. It assists in the decision-making process and increases the success of the marketing strategy. A competitive market requires businesses to observe the market using data to further optimize their marketing and business strategy. Retail stores need to use all of the available resources, including data, to improve their inventory management but also their marketing strategy. Data processing is able to provide details that can be used to support marketing strategies. One of the data processing methods that is often used in marketing strategies is the use of data mining techniques. This study uses association rule mining and the Apriori algorithm to analyze transaction data from a German dataset, which included over 541,000 transactions from December 2010 to December 2011. The analysis found important product associations and customer behavior patterns using metrics such as confidence, lift, leverage, conviction, and certainty to find the strength and dependability of the discovered associations. Results showed strong associations between specific product pairs, offering insight for marketing strategy and inventory optimization.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Unnamed user with email zshi@unite.edu.mk
Date Deposited: 24 Sep 2026 10:22
Last Modified: 24 Sep 2026 10:22
URI: http://eprints.unite.edu.mk/id/eprint/2491

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