Article
Version 1
This version is not peer-reviewed
Exploring the Use of Data Mining Techniques in Marketing Strategies
Version 1
: Received: 31 July 2024 / Approved: 1 August 2024 / Online: 2 August 2024 (05:27:01 CEST)
How to cite: Wilson, G.; Johnson, O.; Brown, W. Exploring the Use of Data Mining Techniques in Marketing Strategies. Preprints 2024, 2024080039. https://doi.org/10.20944/preprints202408.0039.v1 Wilson, G.; Johnson, O.; Brown, W. Exploring the Use of Data Mining Techniques in Marketing Strategies. Preprints 2024, 2024080039. https://doi.org/10.20944/preprints202408.0039.v1
Abstract
This study explores the application of data mining techniques in marketing strategies, highlighting their impact on customer segmentation, predictive analytics, and personalization. Data mining has emerged as a transformative tool for businesses seeking to enhance their marketing effectiveness by providing deep insights into customer behavior and preferences. Techniques such as clustering, predictive modeling, and personalization are examined for their roles in improving marketing outcomes. Clustering methods, including K-means and hierarchical clustering, enable businesses to categorize customers into meaningful segments, allowing for more targeted marketing efforts. Predictive analytics, utilizing models like decision trees and neural networks, offers the capability to forecast future customer behaviors and trends, thereby optimizing resource allocation and strategy planning. Personalization techniques, such as collaborative filtering and dynamic recommendations, enhance customer engagement by delivering tailored content and offers. Despite these advantages, the study also addresses the challenges associated with data mining, including data privacy concerns, data quality issues, and the shortage of skilled personnel. These challenges underscore the need for effective data management practices and ethical considerations in the application of data mining. Furthermore, the integration of emerging technologies like artificial intelligence and real-time analytics is discussed as a means to overcome existing obstacles and drive future advancements in marketing strategies. The findings underscore the significant role of data mining in revolutionizing marketing practices and highlight the ongoing need for adaptation and innovation in response to evolving market dynamics.
Keywords
data mining; marketing strategies; customer segmentation; predictive analytics; personalization; data privacy; emerging technologies
Subject
Business, Economics and Management, Business and Management
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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