International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Volume 6 Issue 6
November-December 2024
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The New Frontier of Ad Analytics: Privacy-Centric Approaches to Campaign Measurement and Optimization
Author(s) | Swati Sinha |
---|---|
Country | United States |
Abstract | This article explores the transformative shift in digital advertising measurement techniques in response to growing privacy concerns and regulatory pressures. It examines the transition from traditional third-party cookie-based tracking to advanced data modeling approaches that prioritize user privacy. The article provides a comprehensive overview of privacy-preserving ad measurement techniques, including aggregated and anonymized data analysis, probabilistic attribution models, and differential privacy. It delves into Big Tech's advancements in conversion modeling, highlighting the role of machine learning in developing more accurate and privacy-compliant attribution methods. The implications for advertisers and marketers are discussed, addressing the challenges of adapting to this new paradigm and strategies for optimizing campaigns using modeled data. Ethical considerations and the importance of building consumer trust are emphasized, underscoring the need for transparency and responsible data stewardship. By synthesizing current research and industry practices, this article offers insights into the future of ad measurement in a privacy-centric digital ecosystem, demonstrating how the industry can balance effective campaign analytics with robust privacy protection to create a more sustainable and trustworthy advertising landscape. |
Keywords | Privacy-Preserving Ad Measurement, Data Modeling in Advertising, Conversion Attribution, Machine Learning for Ad Analytics, Ethical Digital Advertising |
Field | Computer |
Published In | Volume 6, Issue 6, November-December 2024 |
Published On | 2024-11-16 |
Cite This | The New Frontier of Ad Analytics: Privacy-Centric Approaches to Campaign Measurement and Optimization - Swati Sinha - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.30381 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i06.30381 |
Short DOI | https://doi.org/g8rd42 |
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