International Conference on Big Data in Retail and Online Markets
(ICBDROM-27)

This track explores the latest advancements in big data analytics specifically tailored for the retail sector. Researchers are invited to present methodologies and case studies that demonstrate the impact of analytics on retail performance and decision-making.

This session focuses on the integration of big data analytics into e-commerce strategies to enhance customer engagement and sales performance. Papers should address innovative approaches to leveraging data for competitive advantage in online markets.

This track aims to uncover how data mining techniques can be utilized to gain deeper customer insights in retail environments. Contributions should highlight practical applications and the implications of these insights for marketing strategies.

This session examines the role of real-time data analytics in creating seamless omni-channel retail experiences. Researchers are encouraged to discuss tools and frameworks that facilitate real-time decision-making across multiple retail channels.

This track delves into predictive analytics methodologies that enhance retail forecasting accuracy. Papers should present novel models and their applications in predicting consumer behavior and market trends.

This session focuses on the development and implementation of data warehousing solutions tailored for retail applications. Contributions should address challenges and best practices in managing large-scale retail data.

This track explores the adoption of cloud analytics in optimizing retail operations and enhancing data accessibility. Researchers are invited to discuss the benefits and challenges associated with cloud-based solutions in the retail sector.

This session emphasizes the application of big data tools for comprehensive market analysis in retail. Papers should explore innovative techniques that provide actionable insights into market dynamics and consumer preferences.

This track investigates the analysis of transaction data to derive insights into consumer behavior patterns. Researchers are encouraged to present studies that link transaction data analysis to marketing strategies and customer retention.

This session focuses on identifying and analyzing emerging trends in retail consumer behavior through big data analytics. Contributions should aim to provide a forward-looking perspective on how consumer preferences are evolving.

This track addresses the challenges and opportunities associated with large-scale data processing in the retail sector. Papers should discuss technological advancements and strategies for effectively managing and analyzing vast amounts of retail data.