Privacy Policy
At KTM Media Pulse, we are committed to protecting the privacy of our visitors while conducting rigorous academic research. This policy outlines how we collect, use, and safeguard the data generated during this capstone project.
In accordance with our research methodology, we focus on aggregated behavioral patterns rather than individual identities. We do not require users to create accounts or provide personal names, home addresses, or phone numbers to access our core research artifacts.
Data Collection Philosophy
To validate our research question regarding the "selective engagement" of Kathmandu youth, we collect the following:
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Behavioral Metrics: Session duration, bounce rates, and navigation paths throughout the microsite.
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Engagement Data: Interaction with micro-videos, button clicks on the Decision Tool, and infographic view times.
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Technical Data: Device type (Mobile-first focus), browser type, and general geographic location (City-level).
Information We Collect
We utilize Google Analytics specifically to:
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Verify that our traffic originates from the Kathmandu Valley demographic.
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Compare the effectiveness of Narrative vs. Informational content styles.
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Measure the "Interaction Depth" required to prove our audience-led framework.
Use of Google Analytics
This site uses cookies to improve user experience and provide us with insights into how our research is being consumed. You can choose to disable cookies through your browser settings, though this may affect some interactive features of the Brand Campaign Decision Tool.
Cookies
As this is a project for the University of Niagara Falls, we adhere to ethical research guidelines. All data is anonymized. We do not sell, trade, or rent user data to third-party commercial entities. Data is used solely for the purpose of completing the Capstone project and illustrating research findings.
Data Security and Ethics
The data collected during Phase 3 and Phase 4 of this project will be presented in an aggregated format in the final Capstone report. No individual user behavior will be singled out or identified.