Abstract
Customer segmentation analysis, a vital component of marketing strategy, involves the categorization of a diverse customer base into distinct segments, each with unique characteristics and preferences. This process enables businesses to tailor their marketing efforts, create personalized experiences, and ultimately enhance sales performance. Clustering, a powerful data analysis technique plays a pivotal role in identifying these customer segments. By applying clustering algorithms to customer data, businesses gain valuable insights that facilitate the development of targeted strategies. This abstract explores the significance of customer segmentation analysis through clustering in the context of sales improvement. It highlights the benefits of clustering, such as resource optimization, customer retention, and the creation of more effective marketing campaigns. This research emphasizes the practical applications of clustering in identifying customer segments, allowing businesses to allocate resources efficiently, foster customer loyalty, and drive revenue growth. The abstract underscores the importance of data-driven customer segmentation as a strategic tool for businesses aiming to thrive in competitive markets, ultimately leading to improved sales outcomes.
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