A Qualitative Study of Consumer Perceptions of Data-Driven Digital Marketing Practices

Abstract

Data-driven digital marketing (DDDM) — the algorithmic collection, aggregation, and deployment of consumer data to personalize offers, price, and messaging — has become the operating logic of contemporary commerce. Yet the consumer experience of being continuously observed, profiled, and targeted remains only partially understood. This paper undertakes a qualitative study of consumer perceptions of data-driven digital marketing practices using a dual methodological lens: a systematic literature review (SLR) of thirty-eight peer-reviewed and practitioner sources published between 2006 and 2026, and an analytical research design that synthesises qualitative excerpts, survey-based sentiment indicators, and thematic patterns reported across this literature. Using Braun and Clarke's six-phase thematic analysis framework [23], seven recurrent themes were identified: personalization benefit, privacy and surveillance unease, trust in brand or platform, algorithmic opacity, data fatigue and desensitisation, perceived manipulation, and regulatory awareness. The findings confirm and extend the "personalization–privacy paradox" [6,7] by demonstrating that consumer ambivalence is not a fixed trait but a context-dependent appraisal shaped by perceived control, transparency, and institutional trust. The paper further situates these findings within the broader socio-digital literature on algorithmic life, including algorithmic bias [11], platform-mediated precarity [12], and digital fatigue [4,5], to argue that consumer perception of DDDM cannot be separated from wider anxieties about datafied society. A conceptual framework is proposed to guide future empirical and managerial work. Implications for ethical marketing practice, regulatory design, and future mixed-methods research are discussed.