Deriving consumer insights with segmentation for identity and consent

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.