Work

Marketing Optimization: Purchase Data-Based Customer Segmentation Decision Support System

Year: 2025

Type: article

Abstract: —In the era of technological development and changes in shopping culture, e-commerce is increasingly dominating the market, and customer purchase data is becoming a valuable source of information for companies. To address the challenges of inappropriate targeting, customer retention, customer satisfaction, and measuring the effectiveness of marketing campaigns, this research aims to design a decision support system for customer segmentation based on purchase data, identify the optimal parameters of clustering algorithms, and develop appropriate marketing strategies for each group of customers generated from clustering. By using tools such as Matplotlib, Numpy, and Pandas, this research is expected to provide valuable guidance for companies in optimizing their marketing strategies in the competitive e-commerce market.

Source: Matics Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology)

DOI: 10.18860/mat.v17i1.24274

Authors: Vinncent Alexander Wong, Muhammad Althaaf Fadhiilah, Dzikry Aji Santoso, Luthfia Rahmi Setyorini, Andi Ahyar Almuhajir Amrani, Yusi Tyroni Mursityo

Institution: University of Brawijaya

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W4408805928

FWCI:

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