Analyzing and evaluating the impact of using artificial intelligence technologies on improving digital marketing, enhancing consumer purchasing behavior, and fostering customer loyalty.

Abstract

The present study aimed to analyze and assess the contribution of digital technologies and artificial intelligence (AI) applications to improving marketing operations efficiency, enhancing customer experience, and strengthening consumer purchasing behavior and brand loyalty in Libyan companies and institutions. The study examined the relationships between digital marketing platform usage, AI technology adoption, marketing operations efficiency, customer experience enhancement, and AI-supported digital marketing effectiveness. A descriptive-analytical and applied research approach was adopted, using a structured questionnaire comprising 30 items distributed across five main dimensions. Data were collected from 250 participants working in marketing and customer service within Libyan institutions. Descriptive and inferential statistical techniques were employed, including Pearson's correlation analysis, multiple linear regression, independent-samples t-tests, and one-way analysis of variance (ANOVA). The findings indicated a high overall level of digital technology utilization and perceived marketing effectiveness (M = 3.66, SD = 0.58). AI-supported digital marketing effectiveness recorded the highest mean score (M = 3.81, SD = 0.66), whereas AI technology adoption demonstrated a moderate level (M = 3.36, SD = 0.84). Pearson correlation analysis revealed positive relationships among the study variables, with coefficients ranging from 0.60 to 0.72. The regression model explained approximately 63.6% of the variance in perceived AI-supported digital marketing effectiveness (R² = 0.636, F = 107.02, p < 0.001). Marketing operations efficiency demonstrated the strongest standardized regression coefficient (β = 0.27), followed by digital marketing platform usage (β = 0.24), customer experience enhancement (β = 0.21), and AI technology adoption (β = 0.20). Furthermore, statistically significant differences were identified according to job category (p = 0.022) and years of professional experience (p = 0.003), whereas gender (p = 0.589) and educational qualification (p = 0.512) showed no statistically significant differences. The study recommends strengthening the integration of AI applications with digital marketing platforms, enhancing employees' competencies in consumer data analysis, developing personalized marketing campaigns, and providing specialized training to improve marketing operations and customer service performance in Libyan organizations.