Lost Revenue Recognition in E-commerce: Identifying Causes and Implications

In order for e-commerce companies to remain financially healthy, revenue recognition is essential. The sector encounters various problems, including slow-loading pages, problematic web resources, and errors, which can result in revenue losses. This research aims to investigate the causes of lost revenue in e-commerce and propose algorithmic solutions to address these challenges. This study examines the impact of slow pages, problematic web resources, and errors on revenue recognition in the e-commerce industry. In this study, real-world data is analyzed and used to identify how these factors negatively impact e-commerce companies' revenue. Additionally, the study proposes a methodology for calculating the potential revenue that could have been recognized in the absence of the identified factors contributing to lost revenue recognition. This methodology incorporates machine learning techniques, and data visualization tools to estimate the extent of revenue loss. The resulting insights provide decision-makers in e-commerce companies with valuable information for optimizing revenue recognition strategies and maximizing financial performance. This research aims to identify the causes of revenue loss in e-commerce. In order to improve revenue recognition accuracy and maximize business performance in the digital marketplace, e-commerce companies will need to develop algorithmic solutions and implement revenue calculation methodologies to address these issues.