Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)

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Improving the Effectiveness of MSME Marketing through Data Mining Integration In CRM Systems

Authors
Marike A. S. Kondoj1, *, Anthoinete Waroh1, Stephy Walukow1, Toban Pairunan1
1Electrical Engineering Department, Politeknik Negeri Manado, Manado, Indonesia
*Corresponding author. Email: marikekondoj@polimdo.ac.id
Corresponding Author
Marike A. S. Kondoj
Available Online 31 December 2025.
DOI
10.2991/978-94-6463-926-1_87How to use a DOI?
Keywords
CRM; Customer Segmentation; Data Mining; Digital Marketing; MSMEs
Abstract

This study investigates the enhancement of MSME (Micro, Small and Medium Enterprises) marketing effectiveness through the integration of data mining techniques within CRM (Customer Relationship Management) systems. Using a private wholesale transaction data from SMEs for the 2023–2025 period, key variables including CustomerID, InvoiceDate, Quantity, and Total transaction values were analyzed through comprehensive data cleansing protocols to ensure validity and reliability. Customer segmentation analysis using RFM (Recency, Frequency, Monetary) methodology revealed that the majority of customers fell into the “Lost” (58.90%, n = 32,376), “High Value” (18.24%, n = 10,023), “Mid Value” (12.85%, n = 7,063), and “Low Value” (10.01%, n = 5,501) categories. The research demonstrates how automated CRM systems can generate tailored campaign recommendations with specific promotion types, frequencies, and estimated response rates ranging from 5–45% depending on customer segments. These insights indicate significant opportunities for loyalty improvement, targeted up-selling, and customer reactivation strategies. The implementation of data mining-powered CRM enables customization of marketing campaigns with optimized resource allocation. Findings underscore the critical role of automated, data-driven strategies in optimizing marketing effectiveness and fostering sustained customer engagement for MSMEs in competitive digital landscapes.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)
Series
Advances in Engineering Research
Publication Date
31 December 2025
ISBN
978-94-6463-926-1
ISSN
2352-5401
DOI
10.2991/978-94-6463-926-1_87How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Marike A. S. Kondoj
AU  - Anthoinete Waroh
AU  - Stephy Walukow
AU  - Toban Pairunan
PY  - 2025
DA  - 2025/12/31
TI  - Improving the Effectiveness of MSME Marketing through Data Mining Integration In CRM Systems
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)
PB  - Atlantis Press
SP  - 778
EP  - 786
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-926-1_87
DO  - 10.2991/978-94-6463-926-1_87
ID  - Kondoj2025
ER  -