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This study aims to empirically analyze the influence of Brand Image, Service Quality, and  Price on Guest Loyalty in CV Betah Banget Corp, an entity in the accommodation industry that faces fierce competition in the digital era. The quantitative method was used with a multiple linear regression analysis approach to test the relationships between variables. The results of the partial test showed that Brand Image had a significant influence on Guest Loyalty (Count = 2.701 > Ttable = 1.659; sig = 0.008 < 0.05), confirming that positive perception of Brand Image is a key factor in building customer loyalty. Service quality showed a very significant influence (Thcal = 7,338 > Ttable = 1,659; sig = 0.000 < 0.05), strengthening the role of service as a key driver of guest retention amid increasing consumer expectations. In contrast, the  Price variable did not show a significant influence on Guest Loyalty (Thcal = 0.709 < Ttable = 1.659; sig = 0.480 > 0.05), indicating that the  Price aspect is not a major determinant in a customer's decision to remain loyal. These findings provide strategic implications for accommodation industry players to prioritize strengthening Brand Image and improving service quality in an effort to maintain customer loyalty.

Customer segmentation plays a pivotal role in driving marketing strategies and improving customer retention across various industries. This study explores the application of the RFM (Recency, Frequency, Monetary) model for customer segmentation in a Software-as-a-Service (SaaS) business, using Python for efficient data processing and analysis. By analyzing one year of customer purchase data, we segmented customers into key groups such as "Champions," "Loyal Customers," and "At Risk." The results highlight that targeted discount strategies significantly affect profitability, especially for high-value customer segments. Furthermore, the research builds upon existing methodologies, demonstrating how Python-based implementations streamline RFM analysis and allow for scalable solutions in business contexts, as illustrated in prior works by Hermawan et al. (2024). This study offers actionable recommendations, including tailored discounting, loyalty programs, and personalized engagement strategies, to enhance customer retention and business profitability. The findings underscore the importance of data-driven marketing approaches for customer segmentation and engagement, reinforcing the relevance of the RFM model in modern business environments.

Abstract. In an effort to create customer retention, the company improves product quality, service and purchasing power suitability so that consumers can feel satisfaction in using the product and create barriers to switching to Hanasui products at Beauty Shoppy Jombang. The purpose of this study is to determine the influence in maintaining customer satisfaction and switching barriers to customer retention in customers of Hanasui brand products at Beauty Shoppy Jombang by using quantitative methods. The total population in this study is 150 customers. This study uses multiple linear regression analysis techniques and hypothesis testing. The results of this study indicate that customer satisfaction and switching barriers have a significant effect on customer retention of Hanasui products at Beauty Shoppy Jombang.