Business Intelligence for optimizing web traffic analysis in a metal structures company

Abstract

Without a specialized technological solution, web traffic analysis in many companies is performed manually, making it difficult to integrate, consult, and prepare data in a timely manner to support strategic decisions. In scenarios of this type, Business Intelligence tools have established themselves as a fundamental resource for organizations, as they enable large volumes of data to be transformed into useful information through automated analysis and visualization. Therefore, the objective of this study was to optimize web traffic analysis at Grupo Lifcom S.A.C. through the implementation of a Business Intelligence system. The research was applied, with a quantitative approach, a pre-experimental design, and an explanatory level. The population consisted of 80 web traffic records, from which a sample of 66 records was selected through probabilistic sampling. Tools such as Google Analytics and Power BI were used to implement the system, integrating it with a website developed in WordPress. The agile Scrum methodology was used to develop the Business Intelligence system, allowing for iterative and incremental implementation. The results achieved after implementing the Business Intelligence system show a 50.68% increase in the total number of visits, a 75.86% increase in session duration, and a 71.28% reduction in report generation time, demonstrating that the implemented solution significantly optimizes web traffic analysis and strengthens decision-making within the company.