Website Traffic Patterns and User Behavior: A Comprehensive Study of Visitor Interactions and Engagement Metrics

Authors

  • Roger S. Mission College of Computer Studies, University of Antique, Sibalom, Antique, Philippines

DOI:

https://doi.org/10.69478/JITC2023v5n1a02

Keywords:

Website behavior, User experience, Web analytics, Website statistics, University of Antique

Abstract

Websites play a crucial role in disseminating information, promoting communication, and engaging various stakeholders. In the context of universities, websites serve as central online hubs for academic programs, campus life, faculty profiles, resources, news, and more. This study focuses on the website of the University of Antique (UA), a state university in the Philippines, to analyze visitor behavior and engagement. The research objectives include collecting and analyzing data on website visits, page views, bounce rates, time spent on pages, and navigation patterns. The study aims to identify frequently accessed pages, assess the impact of marketing campaigns, capture visitor demographics, and identify areas for website improvement. Data collection took place over a 60-day period using Google Analytics tools, including acquisition, page statistics, and search tools. The study follows a systems approach, where visitor data is automatically recorded in the Google Analytics database. The research methodology involves measuring acquisition metrics, page and screen metrics, device and browser metrics, and geographic metrics. The results indicate that organic search traffic performs well in attracting new users, with the home page showing the highest engagement. Mobile devices are dominant in accessing the website, while the majority of users are from the Philippines. The findings provide insights for optimizing website design, content relevance, and user experience to enhance engagement and achieve conversion goals.

Published

2023-06-30

How to Cite

Website Traffic Patterns and User Behavior: A Comprehensive Study of Visitor Interactions and Engagement Metrics. (2023). Journal of Innovative Technology Convergence, 5(1). https://doi.org/10.69478/JITC2023v5n1a02

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