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Cuadernos de Administración (Universidad del Valle)

Print version ISSN 0120-4645On-line version ISSN 2256-5078

Abstract

MAYA-RESTREPO, María Alejandra; PEREZ-RAVE, Jorge Iván  and  GONZALEZ-ECHAVARRIA, Favián. Systematic literature review on customer analytics capabilities. cuad.adm. [online]. 2024, vol.40, n.79, e2013472.  Epub Aug 12, 2024. ISSN 0120-4645.  https://doi.org/10.25100/cdea.v40i79.13475.

Although the concept of Customer Analytics Capabilities (CAC) has garnered interest among academics and business professionals, there remains a lack of consensus regarding its conceptualization and observable manifestations. This study conducts a systematic literature review on CAC to contribute to this topic, following the stages of locating (resulting in 42 studies), describing (synthesizing definitions and uses of analytics in customer-related domains, among others), deepening (identifying and interpreting common patterns in the studies), and disseminating (preparing the report). Various ways of understanding analytics in organizational customer contexts are discovered and analyzed using a reference conceptual model, synthesizing conceptions (action/method, complex process, or strategic resource) and roles (development of operational capabilities, dynamic capabilities, or strategy adjustment). Additionally, empirical manifestations corresponding to the different conceptions are identified (e.g., determining the effectiveness of specific campaigns based on data). Nine business profiles summarizing underlying maturity levels in CAC are generated from the combination of conceptions and roles. This study clarifies CAC and its observable manifestations based on evidence from the consolidation, standardization, and synthesis of relevant scientific literature on the subject. Therefore, it is useful for leaders of analytics areas in customer contexts and researchers who wish to have a comprehensive theoretical basis for developing future measurement scales.

Keywords : Customer Analytics; Customer Analytics Capabilities; Analytics.

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