Understanding E-Commerce Sales Performance: Insights for Strategic Business Decision-Making (Published)
This study examines sales performance in a synthetic e-commerce dataset and evaluates the business relevance of an order-level revenue model. The analysis covers 5,000 transactions with information on product category, region, quantity, price, discount, payment method, delivery time and customer rating. Descriptive statistics, grouped revenue summaries, visualisations and Pearson correlations are combined with an ordinary least squares regression model. Recorded total revenue is 5,109,775.74 monetary units, and average revenue per order is 1,021.96. Electronics accounts for the largest revenue share at 35.81%, while Beauty has the highest average order value at 1,059.28. Card payments represent 45.40% of transactions. Revenue has positive correlations with unit price and quantity, whereas delivery time and customer rating have little linear association with revenue. The recorded regression results indicate a test R² of 0.870 and mean absolute error of 219.76. However, displayed transactions suggest that revenue is derived from quantity, price and discount, limiting the model’s independent predictive value. The study demonstrates how managers can interpret sales dashboards while distinguishing descriptive patterns, accounting relationships and causal claims. Its managerial recommendations are proposals for validation with real business data rather than evidence of proven commercial effects.
Keywords: E-Commerce, Linear Regression, Sales performance, average order value, business analytics, synthetic data
Understanding E-Commerce Consumer Behavior Through Data Analytics: A Business Intelligence Approach (Published)
With the rise of e-commerce, data-based learning of consumer behavior has become ever more vital. This research adopts a business intelligence approach to investigate e-commerce customer behavior based on a dataset containing 1,000 records and 28 customer attributes. Native technologies (Data pre-processing, exploratory data analysis, visualization to understand customer demographics, purchasing behavior, customer loyalty, customer satisfaction, level of engagement in marketing, etc. The results are reflected in differences in customer demographics, spending habits, shopping channels, and engagement with the brand. The importance of such integration (across different areas of consumer behavior) to generate useful and actionable insights for marketing, customer relationship management, and e-commerce management is thus presented in the study.
Keywords: Business Intelligence, Consumer Behavior, Data analysis, E-Commerce, customer analytics
Determinants Assessment of Consumers’ Intention to Use Of Tokopedia for Shopping Agribusiness SMES Products (Case Study: Toko Laurike) (Published)
Indonesian economics are dominated by the Small Medium Enterprises (SMEs) group. However, only 5% of them have been utilizing online platform s to sell their products. Toko Laurike where is located in Bogor Regency is a member of SMEs group. It produces coconut oil or Virgin Coconut Oil (VCO) and sells its products through several e-marketplaces, namely Tokopedia, Bukalapak and Elevenia. Among these e-marketplaces, Tokopedia sells its more than Bukalapak or Elevenia. This might be suggested by design, security, perceived ease of use or perceived usefulness among these factors. Therefore, we examined the factor of consumers’ intention to use of Tokopedia, specifically for SMEs food agribusiness products in the form of liquid and gel. We also analyzed the correlation of its design and its security to the consumers’ intention to use. We examined the 71 respondents’ data using structural equation modeling – partial least squares (SEM-PLS) and used technology acceptance model (TAM). The results showed that Perceived Ease of Use increases as Design and Security increases. But, Security insignificantly correlated to Perceived Usefulness and consumers’ intention to use. In addition, the result can be used to enhance Laurike’s e-commerce performance.
Keywords: E-Commerce, Small & Medium Enterprise’s (SMEs), Technology Acceptance Model, Tokopedia, structural equation modeling - partial least squares (SEM-PLS)