Abstract: Customer segmentation is a key component of marketing strategies that allows companies to segment their customer base into specific groups by common attributes and behavior. The present research investigates the process of data-driven customer segmentation through clustering methods and demographic research to determine target customer profiles. Based on historical customer information, this research seeks to create actionable segments to match marketing goals to improve customer targeting and one-to-one marketing efforts.

The success of segmented marketing campaigns is measured through the determination of customer response rates, conversion rates, and total return on investment (ROI) for identified segments. Statistical analysis and predictive modeling are used in this research to measure the effect of segmented marketing campaigns and offer information on the differing effectiveness of various promotional strategies within each segment. Comparative analysis is used to determine the most profitable customer segments and the best marketing channels for each segment.

This research emphasizes the importance of customer segmentation as a marketing strategy to improve campaign effectiveness. With customer segmentation aligned with marketing efforts, businesses are able to secure higher response rates, decrease customer acquisition, and drive more ROI.

Keywords: Customer Segmentation, Campaign Effectiveness, Targeted Marketing, Data Analysis, Clustering Techniques

| DOI: 10.17148/IARJSET.2025.125207