Global E-Commerce Dynamics: Analyzing Cross-Border Consumer Behavior and Insights from Electronic Sales Data

Abstract

This study explores the key factors influencing e-commerce sales transactions by analyzing electronic sales data from September 2023 to September 2024. Using regression analysis, the findings reveal that unit price and quantity purchased strongly predict total sales, with unit price having the highest predictive power. A positive correlation between quantity and total sales highlights the impact of bulk purchasing, while add-on totals show minimal influence, suggesting opportunities for improved marketing strategies for complementary products. Descriptive statistics indicate significant variability in customer spending, with a right-skewed distribution showing that most customers spend less, while a few contribute disproportionately to total revenue. ANOVA results confirm the significance of differences between stores, reinforcing the importance of targeted pricing and inventory strategies. However, limitations such as unaccounted variance (12.4%), static data, and the absence of qualitative factors like customer satisfaction suggest avenues for further research. Future studies should incorporate seasonal trends, customer segmentation, and machine learning techniques to enhance predictive accuracy and strategic decision-making in e-commerce.