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Practice paper

Deriving consumer insights with segmentation for identity and consent

Pamela Castricone and Lucas Long
Applied Marketing Analytics: The Peer-Reviewed Journal, 10 (3), 245-254 (2024)
https://doi.org/10.69554/JZEK9481

Abstract

The emerging privacy landscape is placing constraints on how consumer data can be collected and processed, especially for advertising use cases. Given the privacy-centric environment, organisations should approach their first party consumer data through the lens of what can be done with the data. This paper proposes a framework for segmenting consumer data based on identity and consent state, with strategies to derive the most consumer insights possible from each. Strategies focus on the role of data modelling in uncovering insights from first party data, and various modelling techniques are explored, including customer lifetime value modelling, propensity modelling, regression-based attribution and aggregate data modelling. By adopting a privacy-centric approach to data collection and leveraging advanced modelling techniques, organisations can gain valuable insights into consumer behaviour, optimise marketing and advertising efforts, and thrive in the evolving landscape of consumer data analysis.

Keywords: consumer data privacy; first party data; data segmentation; data modelling techniques; consumer insights; privacy-centric advertising; consumer behaviour analysis

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Author's Biography

Pamela Castricone is an emerging solutions strategist at InfoTrust. She holds a bachelor's degree in mathematics from John Carroll University and a master's degree in statistics from Miami University. Pamela is a Google certified professional data engineer and has served as an adjunct instructor at the University of Cincinnati's Lindner College of Business. With expertise in statistical and machine learning models, Pamela is passionate about leveraging analytical techniques and cloud technologies to enhance marketing return on investment.

Lucas Long is Head of Global Privacy Strategy at InfoTrust, working with organisations at the intersection of digital strategy, privacy regulations and technical data collection architecture. He helps companies to understand limitations for data enablement due to privacy challenges and design strategies to accomplish core use cases in a compliant manner. Lucas is also a presenter and contributing writer, featured at industry events organised by Google, the Digital Analytics Association and the American Marketing Association.

Citation

Castricone, Pamela and Long, Lucas (2024, December 1). Deriving consumer insights with segmentation for identity and consent. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 10, Issue 3. https://doi.org/10.69554/JZEK9481.

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cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 10 / Issue 3
© Henry Stewart
Publications LLP

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