Data-Driven Visitor Tracking Analytical Insights and Recommendation System

Rutuja Khedkar, Prema Sahane, Anushka Patil, Abhijit Jawkar, Sharvayu Dhemse

2025

Abstract

Novel Way of Visualizing Visitor Behavior: From behavior on a website to behavior in a buildingAbstract—In the digital age, it is crucial to understand visitor behavior in websites and physical locations to improve user experience and optimize business strategy. We present a Visitor Tracking, Analytical, and Recommendation System (VTARS) able to log, process and produce insights about visitor interactions. VTARS uses cutting-edge tracking technologies to record the movements, preferences, and activities of individual visitors across multiple touchpoints. It aggregates data from different sources, such as web analytics, location-based services, IoT devices to create holistic visitor profiles. VTARS captures visitor insights using machine learning algorithms and statistics, tracking visitor interaction data like browsing, purchases, and engagement frequency. This information is then synthesized, resulting in an interactive report and visualizations to give stakeholders a better idea of who their visitors are and what things interest them. It functions by anticipating the specific needs that users may have during their engagement and suggesting relevant content, products, or services that users may be interested in based on their previous interactions and behaviors, with the purpose of improving user satisfaction and conversion rates. Iterative learning improves recommendations over time, as they adapt to changing patterns in visitor behavior and preferences.

Paper Citation

in Harvard Style

Khedkar R., Sahane P., Patil A., Jawkar A. and Dhemse S. (2025). Data-Driven Visitor Tracking Analytical Insights and Recommendation System. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 705-711. DOI: 10.5220/0013640700004664

in Bibtex Style

@conference{incoft25,
author={Rutuja Khedkar and Prema Sahane and Anushka Patil and Abhijit Jawkar and Sharvayu Dhemse},
title={Data-Driven Visitor Tracking Analytical Insights and Recommendation System},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={705-711},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013640700004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Data-Driven Visitor Tracking Analytical Insights and Recommendation System
SN - 978-989-758-763-4
AU - Khedkar R.
AU - Sahane P.
AU - Patil A.
AU - Jawkar A.
AU - Dhemse S.
PY - 2025
SP - 705
EP - 711
DO - 10.5220/0013640700004664
PB - SciTePress