Article
Drivers and Outcomes of Digital Marketing Analytics Adoption in Consultancy and Financial Advisory Services
Digital marketing analytics is increasingly positioned as a lever for business development in professional and financial advisory services, yet the organizational conditions under which analytics-related perceptions and capabilities translate into expected performance gains remain under-examined in this sector. Drawing on the Technology-Organization-Environment framework, this study examines how perceived strategic value, organizational readiness, and competitive and market pressure relate to expected business development performance. Primary data were collected through a structured, five-point Likert questionnaire from 52 respondents working in and closely connected to a consultancy and financial advisory services firm, using convenience sampling. The retained raw item-level responses were reanalysed for this manuscript using descriptive statistics, Cronbach's alpha reliability analysis, Pearson correlation, and simultaneous (standard) multiple regression. All four multi-item scales showed acceptable to good internal consistency (α = .73 to .83). All three predictors were positively and significantly correlated with expected business development performance (r = .777, .746, and .768 for perceived strategic value, organizational readiness, and competitive and market pressure, respectively; p < .001 in each case) and with one another (r = .72 to .78). When entered simultaneously, all three predictors retained statistically significant unique associations with expected business development performance (β = .32, .26, and .33, respectively; p < .05 in each case), jointly explaining 69.8 percent of the variance (R² = .698, adjusted R² = .679), F(3, 48) = 36.95, p < .001. The findings indicate that, in this professional-services context, perceived value, organizational capability, and external market pressure each contribute independently to expected performance rather than one dominating the others. The study offers a transparent contribution to analytics-adoption research in knowledge-intensive professional services and identifies larger and more diversified samples and longitudinal designs as priorities for future research.