顾客多样性的战略洞察:通过k均值聚类分析购买模式、收入差异和关系动态,以增强参与和忠诚度

Shraddha Sharma , Rupali Satsangi , Preeti Manani , Priti Sharma , Jyoti Gupta
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引用次数: 0

摘要

本文探讨了顾客细分在现代营销策略中不可或缺的作用,强调了它在理解和满足不同顾客需求方面的重要性。该研究承认探索性数据分析(EDA)是关键的初步步骤,研究了EDA如何通过揭开原始数据中的隐藏模式,作为有效分割算法的催化剂。通过实证和案例研究,本文展示了在部署分割模型之前结合EDA的变革性影响。结果强调了一个强大的EDA框架的必要性,以提取可操作的见解,提高目标营销工作的准确性,并使细分战略与现实世界的客户动态保持一致。这项研究为从业者和研究人员提供了宝贵的见解,通过将客户细分与探索性数据分析相结合的整体方法来优化营销策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strategic Insights into Customer Diversity: Unraveling Purchase Patterns, Income Disparities, and Relationship Dynamics through K-means Clustering for Enhanced Engagement and Loyalty
This research paper explores the integral role of customer segmentation in modern marketing strategies, emphasizing its significance in understand-ing and catering to diverse customer needs. Acknowledging Exploratory Data Analysis (EDA) as a crucial preliminary step, the study investigates how EDA acts as a catalyst for effective segmentation algorithms by un-veiling hidden patterns in raw data. Through empirical evidence and case studies, the paper demonstrates the transformative impact of incorporat-ing EDA before deploying segmentation models. The results underscore the necessity of a robust EDA framework to extract actionable insights, enhancing the precision of targeted marketing efforts and aligning seg-mentation strategies with real-world customer dynamics. This research contributes valuable insights for practitioners and researchers seeking to optimize marketing strategies through a holistic approach that combines customer segmentation with exploratory data analysis.
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