| The Evolution of Internet Analytics Platforms: A Comprehensive Literature Review | ||
| Egyptian Journal of Health Sciences Technology | ||
| Articles in Press, Accepted Manuscript, Available Online from 29 October 2025 | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ejhst.2025.403325.1005 | ||
| Authors | ||
| Alyaa Elrashedy* 1; Hassan R. Saad2; Ahmed A Ahmed2; Eman M Ashour2; Shimaa H Fathy2; Youssef Gamal2; Mahmoud Fayez2; Abdelrahman Ibrahim2; saeed Awad2; Mohamed E. Hasan3 | ||
| 1Department of Animal Medicine and Infectious Diseases, Faculty of Veterinary Medicine, University of Sadat City, Egypt. Faculty of Applied Health Science, Borg Al Arab Technological University (BATU), Alexandria, Egypt | ||
| 2Faculty of Applied Health Science, Borg Al Arab Technological University (BATU), Alexandria, Egypt | ||
| 3Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Egypt Faculty of Applied Health Science, Borg Al Arab Technological University (BATU), Alexandria, Egypt | ||
| Abstract | ||
| Abstract: This literature review explores the evolution and current landscape of internet analytics platforms, emphasizing the integration of artificial intelligence (AI). By analyzing recent research and industry practices, the review categorizes analytics platforms into four key areas: web analytics, social media analytics, network performance monitoring, and market trend analysis. It evaluates AI’s transformative role in enhancing predictive modeling, automated reporting, anomaly detection, and sentiment analysis, driving a shift from descriptive to prescriptive analytics. This transition enables organizations to derive actionable insights with greater precision and efficiency. However, challenges such as data privacy concerns, algorithmic transparency, and ethical implementation remain significant hurdles. The review also highlights emerging trends, including real-time analytics and cross-platform data integration, which further amplify AI’s impact. By synthesizing these findings, this study contributes owing to understanding how organizations can effectively leverage AI-enhanced analytics while addressing technical and ethical challenges to ensure responsible adoption and maximize strategic value. | ||
| Keywords | ||
| Artificial intelligence; Internet analytics; Machine learning; Market analysis; Web analytics and Social media analytics | ||
| Statistics Article View: 2 | ||