LEVERAGING DATA SCIENCE TECHNIQUES FOR CUSTOMER SEGMENTATION AND TARGETED MARKETING IN THE RETAIL INDUSTRY
Keywords:
Data Science Techniques, Customer Segmentation, Targeted Marketing, Retail Industry, Customer Data Analysis, Personalization, Machine Learning Algorithms, Predictive Analytics, Competitive AdvantageAbstract
Leveraging data science techniques has become increasingly essential for businesses, particularly in the retail sector, to understand and effectively engage with their customer base. This abstract explores the application of data science methodologies for customer segmentation and targeted marketing strategies within the retail industry. By analyzing vast amounts of customer data, including demographic information, purchase history, and behavioral patterns, businesses can identify distinct customer segments and tailor their marketing efforts accordingly. This targeted approach enables retailers to deliver personalized experiences, optimize product recommendations, and ultimately enhance customer satisfaction and loyalty. Furthermore, the integration of advanced analytics and machine learning algorithms facilitates the prediction of future customer behaviors, allowing retailers to anticipate market trends and adapt their strategies proactively. Overall, the implementation of data science techniques empowers retailers to unlock valuable insights from their data, driving informed decision-making and competitive advantage in today's dynamic retail landscape.
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Copyright (c) 2023 Ananth Raja Muthukalyani (Author)
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