Analysis of Consumer Behavior Using Business Intelligence and Machine Learning in Digital Marketplaces
Keywords:
Predictive Analytics, Consumer Behavior, Data-Driven Decision Making, Digital Marketplace, Business IntelligenceAbstract
The rapid growth of digital marketplaces has led to a significant increase in the volume and diversity of transaction data. This condition requires methods capable of transforming large-scale data into valuable information that can support organizational decision-making. In this context, Business Intelligence (BI) is utilized to process and present historical data through various visualization techniques, while Machine Learning is employed to identify customer behavior patterns and predict potential future transaction trends. This study aims to analyze consumer behavior in digital marketplaces through the integration of Business Intelligence and Machine Learning to generate predictive insights that support more accurate, effective, and data-driven business decisions. The research approach encompasses Business Intelligence processes, including Extract, Transform, Load (ETL), data warehouse development, and the design of interactive dashboards to visualize sales performance and customer activities. Subsequently, Machine Learning techniques are applied to develop predictive models based on historical transaction data, purchase frequency, product categories, and customer attributes. Model performance is evaluated using several metrics, including accuracy, precision, recall, and F1-score. The findings indicate that Business Intelligence effectively provides relevant insights into sales trends, top-performing products, and customer purchasing patterns through intuitive visual representations. Furthermore, the Machine Learning implementation successfully develops predictive models capable of estimating repurchase likelihood and identifying potential customers with satisfactory performance levels. These results demonstrate that the integration of Business Intelligence and Machine Learning offers more comprehensive analytical capabilities compared to descriptive approaches that rely solely on historical data. The combination of Business Intelligence and Machine Learning has proven effective in supporting predictive consumer behavior analysis within digital marketplace environments. In addition to providing insights into past transaction patterns, this approach delivers predictive intelligence that can be utilized to formulate marketing strategies, improve customer retention, and enhance long-term business performance.
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