Retail Analytics through Visualization: Exploring the Superstore Dataset

Abstract

This project explores sales performance and operational trends within a retail business using the Superstore dataset, which includes detailed records of customer orders, sales, profits, and shipping information. Through comprehensive data visualization techniques, we analyze key business metrics across multiple dimensions such as region, product category, sub-category, customer segment, and shipping mode. The primary objective is to identify patterns and insights that can drive better business decisions, such as recognizing high-performing products, understanding regional sales differences, and evaluating profit margins. Tools like Tableau were employed to create interactive dashboards and static visualizations. The analysis reveals actionable insights such as the imbalance between high sales and low profitability in certain categories, and the impact of shipping choices on customer satisfaction. This project demonstrates how effective data visualization can simplify complex datasets and support strategic planning in retail environments.

Country : India

1 Mohammad Afnaan Anwar2 Fouzan Taha Hussain3 Prof. P. Lavanya

  1. Student, Department of Artificial Intelligence and Data Science, Methodist College of Engineering and Technology, Hyderabad, India
  2. Student, Department of Artificial Intelligence and Data Science, Methodist College of Engineering and Technology, Hyderabad, India
  3. Professor, Department of Computer Science and Engineering, Methodist College of Engineering and Technology, Hyderabad, India

IRJIET, Volume 9, Issue 6, June 2025 pp. 35-41

doi.org/10.47001/IRJIET/2025.906006

References

  1. Wang, Shuming, and Phisanu Chiawkhun. "Using data visualization for supermarket retail analysis." Data Science and Engineering (DSE) Record 3.1 (2022): 93-111.
  2. Upadhye, Akshata. "ENHANCING BUSINESS STRATEGY WITH SALES DATA VISUALIZATION." Journal ID 2811: 6201.
  3. Arora, Monika. "An Application of Dash Board: A Case of Superstore Sales." Monika Arora, Nikhil Pal Singh, Pranav Chhabra (2016),“An Application of Dash board: A Case of Superstore sales”, National Seminar on “TECHNO TRYST. 2016.
  4. Arista, Artika, Theresiawati Theresiawati, and Henki Bayu Seta. "Big Mart Sales Data Visualization and Correlation." JOIV: International Journal on Informatics Visualization 8.2 (2024): 576-582.
  5. Mohamed, Rabab Hussien, and Kamel Hussien Rahouma. "Research for Big Data Storage and Analysis Based on Artificial Intelligence." Journal of Advanced Engineering Trends (2025).
  6. Patil, Manisha M. "A Case Study-Visual Analysis of Sales Records Using Tableau." International Journal of Advanced Research in Science, Communication and Technology (2021).
  7. Anggrainy, T. Difa, and A. Rusiana Sari. "Implementation of extract, transform, load on data warehouse and business intelligence using pentaho and tableau to analyse sales performance of offlist store." Science 7.2 (2022): 368-374.
  8. Lawson-Body, Assion, et al. "Anomaly identification through data visualization: regression analysis revisited." Issues in Information Systems 24.4 (2023).
  9. Yeng, Lim Jia, Mohd Norshahriel Abd Rani, and Nabilah Filzah Mohd Radzuan. "Data Analytics Model for Home Improvement Store." Advances on Smart and Soft Computing: Proceedings of ICACIn 2021. Springer Singapore, 2022.
  10. Tajiri, Shintaro, et al. "Integrating Tableau into a First-Year Information Literacy Course: A Practical Approach to Enhancing Data Science Education." IIAI Letters on Institutional Research 4 (2024).