B2B customer segmentation and market basket analysis: a case study of an office supplier company

การจัดกลุ่มและการวิเคราะห์ตะกร้าตลาดของลูกค้าที่เป็นธุรกิจ (B2B) กรณีศึกษาบริษัทขายอุปกรณ์สำนักงาน

Name: Sutiwat Tinburanakul

LCSH: Business -- Analysis

LCSH: Business -- Data processing -- Management

LCSH: Database marketing

Abstract: In today's highly competitive business landscape, B2B companies are constantly seeking innovative ways to better understand and serve their customers. This study explores customer segmentation in a B2B office supply company using K-means clustering to segment customers into distinct groups based on recency, frequency, and monetary Value (RFM) analysis and number of product section variety, we employ the Apriori and FP-Growth algorithms. These Market Basket algorithms are used to identify frequent itemsets and association rules among purchased products. By comparing the results and runtime performance of Apriori and FP-Growth, we aim to determine which algorithm is more efficient for uncovering meaningful business insights within the context of B2B office supplies. Furthermore, association rules generated by these algorithms serve as additional criteria to justify the segmentation results obtained from K-means clustering. This integration of customer behavior analysis through Market Basket algorithms not only enhances the quality of customer segmentation but also provides valuable insights into cross-selling opportunities, product bundling strategies, and overall business performance

King Mongkut's Institute of Technology Ladkrabang. Central Library

Address: BANGKOK

Email: Lifelong@kmitl.ac.th

Created: 2023

Modified: 2024-11-12

Issued: 2024-11-12

วิทยานิพนธ์/Thesis

application/pdf

eng

DegreeName: Master of Science

Level: Master's Degree

Descipline: Data Science and Analytics

Grantor: King Mongkut's Institute of Technology Ladkrabang

©copyrights King Mongkut's Institute of Technology Ladkrabang

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