نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Introduction and Purpose: As the volume and complexity of market and customer data continue to increase, the ability to effectively utilize information has become a decisive factor in marketing performance. Marketing analytics, which involves collecting, processing, and interpreting market-related data to generate actionable insights, has become a central tool for organizations seeking to improve their marketing outcomes. However, access to analytical technologies and data does not, in itself, guarantee superior results. Firms must also possess the capabilities required to integrate analytical insights into their marketing processes and managerial activities. This issue is particularly relevant to knowledge-based enterprises, which rely heavily on knowledge, technology, and information but often face challenges in translating these resources into tangible market outcomes. Drawing on Organizational Information Processing Theory, the Resource-Based View (RBV), and Dynamic Capabilities Theory, this study examines the effect of the Use of Marketing Analytics (UoMA) on Marketing Performance (MP). It also investigates the mediating roles of Marketing Capabilities (MC) and Marketing Decision-Making (MDM) in this relationship among Iranian knowledge-based enterprises. Eight hypotheses were formulated to examine the direct relationships among these constructs and the indirect effects mediated by MC and MDM.
Methodology: This study employed an applied, quantitative, descriptive-survey, and cross-sectional design, following a deductive approach within the positivist paradigm. The statistical population consisted of 11,097 active knowledge-based enterprises in Iran. Power analysis using G*Power indicated a minimum required sample size of 222 enterprises. Due to access limitations, convenience sampling was employed, resulting in the collection of 261 completed questionnaires. After excluding 24 invalid responses, 237 questionnaires were retained for analysis. The respondents were managers and specialists working in marketing, sales, business development, or related fields, all of whom had at least five years of relevant professional experience. Data were collected using a standardized 45-item questionnaire covering UoMA, MC, MDM, and MP. The measurement model was assessed using factor loadings, Cronbach's alpha, rho_A, composite reliability, average variance extracted (AVE), the Fornell–Larcker criterion, and the heterotrait–monotrait ratio (HTMT). The structural model was estimated using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 3. Path coefficients, t-statistics, R², and Q² were employed to evaluate the structural model, while bootstrapping was used to examine the significance of indirect effects.
Findings: UoMA had significant positive effects on MC (β = 0.498, t = 6.993, p < 0.001), MDM (β = 0.523, t = 7.980, p < 0.001), and MP (β = 0.337, t = 3.647, p < 0.001). MC also had significant positive effects on both MDM (β = 0.375, t = 4.228, p < 0.001) and MP (β = 0.448, t = 5.179, p < 0.001). Furthermore, MDM positively affected MP (β = 0.207, t = 2.484, p = 0.014). The mediation results, however, were mixed. MC significantly mediated the relationship between UoMA and MP (β = 0.223, t = 2.557, p = 0.011), thereby supporting H7. In contrast, the mediating role of MDM was not supported based on the reported t-value (β = 0.108, t = 1.946). The model explained 24.8% of the variance in MC, 52.9% in MDM, and 62.2% in MP. Moreover, the positive Q² values indicated the predictive relevance of the model for the endogenous constructs.
Discussion and Conclusion: The findings demonstrate that the value of marketing analytics extends beyond providing information for individual managerial decisions. The significant relationship between UoMA and MC suggests that the systematic use of analytical insights can strengthen organizational capabilities in marketing planning and implementation, customer relationship management, and new product development. This finding is consistent with the RBV and Dynamic Capabilities Theory, as analytical information becomes strategically valuable only when firms possess the capabilities required to integrate and effectively exploit it. Although UoMA significantly enhanced marketing decision-making, the non-significant mediating role of MDM suggests that improved decision-making alone may not be sufficient to translate analytical insights into sustained marketing performance. By contrast, the significant mediating role of MC highlights the importance of embedding analytical insights in organizational routines and marketing processes. Accordingly, knowledge-based enterprises should move beyond investing solely in analytical technologies and dashboards and simultaneously develop the human and organizational capabilities required to transform analytical insights into effective marketing actions. From a managerial perspective, this entails strengthening collaboration between marketing and data specialists, developing employees' analytical skills, establishing systematic mechanisms for incorporating analytical findings into marketing decisions, and institutionalizing the use of these insights across marketing planning and implementation, customer relationship management, and product development. Future research should employ longitudinal research designs, multiple data sources, objective performance indicators, and probability sampling methods. It could also investigate the sequential mediating roles of marketing capabilities and marketing decision-making, as well as contextual factors such as top management support, marketing–IT integration, and environmental uncertainty, to provide a more comprehensive understanding of how marketing analytics generates organizational and market value.
کلیدواژهها English
