Designing a Business Intelligence Framework Based on User Behavior Mining in E-Businesses: With an Emphasis on Marketing 4.0
Subject Areas : Technology Transfer and Commercialization of Researches
Mohammadali Sharafian
1
*
,
Yaser Ghasemi Nezhad
2
,
Faezeh Esmaeelbeigi
3
1 - :Faculty of Management, Islamic Azad University, South Tehran Branch, Tehran, Iran
2 - Faculty of Industrial Management, Imam Hossein Comprehensive University, Tehran, Iran
3 - Faculty of Tourism, University of Tehran - Tehran - Iran
Keywords: Business Intelligence, User Behavior Mining, Marketing 4.0, Meta-Synthesis, E-Businesses, Sentiment Analysis,
Abstract :
In the current digital age, e-businesses are faced with a massive amount of user behavioral data, the accurate and timely analysis of which can lead to creating a competitive advantage, intelligent decision-making, and improving the customer experience. The present study aimed to design a comprehensive, integrated, and innovative framework for user behavioral data mining in the context of Marketing 4.0. This study used a systematic review method and a meta-synthesis approach to identify key components affecting user behavioral data mining and combine them into a conceptual and practical model. The proposed framework is based on the standard CRISP-DM process and is developed using deep learning-based sentiment analysis, technology acceptance model (UTAUT), and social network analysis. The findings show that components such as data quality, sentiment analysis, social interactions, demographic data, purchasing preferences, smart technologies, and data security play a decisive role in understanding user behavior and predicting their needs. The main innovation of the research is in combining the technical and behavioral dimensions of data mining and presenting a three-layer structure including the input layer (data sources), the processing layer (analysis and modeling), and the output layer (Marketing 4.0 results). This framework provides practical guidance for marketing managers and digital decision makers to adopt more effective marketing strategies, more personalized services, and data-driven decisions by relying on big data analysis and user behavior. As a result, it can lead to improving the business intelligence of organizations, increasing customer loyalty, and creating a sustainable competitive advantage in the digital business environment.
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