An In-Depth Study of Retail Sales Trend and Pattern based on Exploratory Data Analysis

  • Amit Kumar Keshav Sonavane
Keywords: Sales Management, Sales Pattern, Machine Learning, Decision Tree, Data Analytics.

Abstract

A world driven by consumer’s means that we are mostly directed by the demands of individuals, which we might call customers. As the world changes, we must plan and restructure our processes for assessing trends and staying on top of the charts with our sales figures. To analyses the shopping or order putting behavior of clients, we have developed an EDA method. As a result of using exploratory data analysis, we were able to determine the monthly patterns in sales. Based on categorical variables, we employed a thorough procedure for sales analysis. We also looked at the top 10 selling goods in terms of profit and quantity. To guarantee that clients have a positive purchasing experience, the shipping method is crucial. As a result, the customer's favorite delivery method is also researched from the analyzed data. Further, we looked at the most lucrative product categories and concentrated on the category that generated profits, in order to understand not only what consumers buy, but also how and why they do so. What product categories customers are most interested in, which product categories have the greatest conversion rates, which of your items are popular both qualitatively and quantitatively, were all revealed through this research. Improved sales & order pipelines may be boosted with better sales & order data analysis. If the firm analyses order data trends, it will be able to keep up with product and pricing changes, utilize optimal distribution channels and continue to improve earnings.

Published
2021-09-05
How to Cite
Amit Kumar Keshav Sonavane. (2021). An In-Depth Study of Retail Sales Trend and Pattern based on Exploratory Data Analysis. Design Engineering, 6313- 6327. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/4064
Section
Articles