The Personalization Loop: Engagement Metrics in Algorithmic Retargeted Advertising - S, Vaidhyanathan; P S, Rajeswari (International Journal of Accounting and Economics Studies, 2025)
Algorithmic advertising has seen a massive shift towards more personalized advertising empowered by big data. It has become increasingly important to understand how and if users interact with retargeted advertising across multiple digital environments. As a continuation from Voorveld et al.'s (2018) critiques of treating "social media" as one thing, this paper discusses the interaction between user experience on the platform and associated engagement with the brand, all within the context of personalized retargeting advertising. Our analysis is based on the findings from an original study that used insights collected from over 600 individuals (aged 18 and older). The original study indicated that various platforms provide distinct interaction experiences, such as the real-time topicality of Twitter versus the creative stimulation of Pinterest, which provide unique advertising impressions. In this paper, we build on the premise that personalized ads have different impressions and different engagement outcomes, based on the platforms. We argue that the engagement with retargeted content does not depend only upon ad relevance or frequency but also on the users' cognitive, emotional, and contextual state during each platform interaction. Our synthesis indicates that retargeted ads are more effective (and engage users positively) when operating in concert with platform-specific experiential factors (like social connection in Facebook or visual inspiration in Instagram). In conclusion, we inductively offer a re-conceptualized engagement framework to understand retargeted advertising from a multi-platform context, viewing each interaction within a nuanced digital environment, whereby advertisers need to adapt their personalization strategies to the multiple digital environments that users may inhabit. The intersection of algorithmic targeting, consent, and platform affordances as a framework for further inquiry to assess the efficacy of retargeted advertising.
Keywords: Personalized advertising, retargeted advertising, user engagement, algorithmic targeting, platform-specific engagement, digital advertising effectiveness, social media platforms, contextual relevance, consumer perception, advertising personalization, engagement metrics, data-driven marketing, advertising algorithms, behavioral targeting, digital user experience.