Customer Behavior Analysis Through Data Analytics In The Bangladeshi Retail Industry

This qualitative study aims to investigate the state of customer behavior analysis in the Bangladeshi retail industry, with a particular focus on the role of data analytics. The research seeks to explore the current practices, challenges, opportunities, and best strategies employed by retailers in understanding and responding to customer behavior. The Bangladeshi retail industry has witnessed substantial growth driven by factors such as economic development, urbanization, and evolving consumer preferences. In this evolving landscape, retailers increasingly rely on data analytics to gain valuable insights into customer behavior, optimize business operations, and enhance customer experiences. Understanding customer behavior is vital for retailers to tailor their strategies to meet the ever-changing needs and preferences of Bangladeshi consumers. This study employs qualitative research methods, including in-depth interviews with key stakeholders in the Bangladeshi retail industry. The sample size comprises 40 participants, and data analysis involves a thematic approach. The study explores the current state of customer behavior analysis, challenges, opportunities, best practices, and strategies related to data analytics within the retail sector. The findings reveal a growing integration of data analytics in customer behavior analysis, with retailers utilizing various data sources such as point-of-sale data, online transactions, and customer surveys. Challenges include data security concerns and the need for skilled data analysts, while opportunities encompass improved customer retention, enhanced personalization, and more effective marketing campaigns. Best practices emphasize fostering a data-driven culture, collaborating with external data analytics experts, and continuous staff training. The study’s insights have implications for the Bangladeshi retail industry, highlighting the transformative potential of data analytics in adapting to evolving customer preferences and remaining competitive. Recommendations include clear objective setting, investment in data security measures, and the pursuit of external expertise when needed.