Piloting personalization research through data-rich environments: a literature review and future research agenda

Abstract

PurposeOver the last 50 years, increased attention for personalization paved the way for one-to-one marketing efforts, but firms struggle to deliver on this promise. The purpose of this manuscript is to provide a complete picture on personalization, develop a future research agenda and put forth concrete advice on how to move the field forward from a theoretical, methodological, contextual, and practical viewpoint.Design/methodology/approachThis research follows a systematic literature review process, providing an in-depth analysis of 135 articles (covering 184 studies) to distill the (1) key building blocks and components of personalization and (2) theoretical, contextual, and methodological aspects of the studies.FindingsThis manuscript uncovers six personalization components that can be linked to two personalization building blocks: (1) learning: manner, transparency, and timing and (2) tailoring: touchpoints, level, and dynamics. For each of these components, the authors propose future research avenues to stimulate personalization research that accounts for challenges in today's data-rich environments (e.g. data privacy, dealing with new data types). A theoretical, contextual, and methodological (i.e. industry, country and personalization object) review of the selected studies leads to a set of concrete recommendations for future work: account for heterogeneity, embed theoretical perspectives, infuse methodological innovation, adopt appropriate evaluation metrics, and deal with legal/ethical challenges in data-rich environments. Finally, several managerial implications are put forth to support practitioners in their personalization efforts.Originality/valueThis research provides an integration of personalization research beyond existing and outdated review papers. Doing so, it accounts for the impact of new technologies and Artificial Intelligence and aims to advance the next generation of knowledge development on personalization.

The transformative potential of AI-enabled personalization across cultures

“…Notably, we implement this approach in a multicountry context. This decision aligns with findings by Mehmood et al. (2023) that highlight a significant skew in personalization studies toward single-country research, predominantly in cultures characterized as Western, educated, industrialized, rich, democratic (WEIRD).…”

“…Ameen et al. , 2021), while only anecdotally highlighting other well-being facets that consumers care about (Mehmood et al. , 2023).…”

“…Indeed, extant literature has predominantly focused on privacy-related implications of AI-enabled personalization (e.g. Ameen et al, 2021), while only anecdotally highlighting other well-being facets that consumers care about (Mehmood et al, 2023). By considering the mental models held by consumers about the well-being implications of AI-enabled personalization, this research expands the boundaries of personalization research (Mehmood et al, 2023), broadens the scope and boundary of TSR work (Previte and Robertson, 2019) and also responds to calls for a consumer-oriented approach in TSR (Russell-Bennett et al, 2019).…”

“…Personalization, in general, involves understanding individual consumer needs and tailoring market offerings accordingly (Fan and Poole, 2006; Libai et al. , 2020; Montgomery and Smith, 2009), with learning and tailoring as its key building blocks (Mehmood et al. , 2023).…”

Improving the effectiveness of personalized recommendations through attributional cues

“…A better understanding of the effects of attributional cues, therefore, presents a potentially simple, cost-effective, and impactful way of increasing the effectiveness of personalized recommendations. Furthermore, personalized recommendations are not only one of the most common forms of personalization in the marketing mix (Mehmood et al, 2022), they are also similar to additional personalized elements of the marketing mix such as personalized advertising or personalized communications. Our findings on attributional cues are therefore likely also relevant for these personalized elements.…”