AI-driven marketing innovation in educational technology

This study investigates the impact of AI-driven marketing innovations on user acceptance and engagement in educational technology contexts, examining how virtual sales personnel characteristics and intelligent promotion strategies influence behavioral outcomes through psychological mechanisms. An explanatory sequential mixed-methods design was employed, combining structural equation modeling analysis of survey data from 650 educational technology users with thematic analysis of 45 semi-structured interviews. Machine learning algorithms, particularly XGBoost (AUC=0.89), were utilized to predict user acceptance patterns and identify five distinct user segments. Trust emerged as the critical mediating mechanism between AI anthropomorphism and user acceptance, accounting for 76.5% of the total effect. Personalization capabilities demonstrated the strongest impact on continuous engagement (β=0.52, p<0.001). Qualitative analysis revealed three overarching themes: intelligent companion experience (82.2% prevalence), personalization value perception (88.9%), and privacy-convenience trade-offs (68.9%). The validated framework provides educational technology enterprises with actionable guidelines for implementing AI marketing systems that balance technological sophistication with humanization principles through moderate anthropomorphism and progressive personalization strategies. This research extends the Technology Acceptance Model by integrating AI-specific constructs, including algorithm trust and perceived intelligence, offering novel theoretical insights and empirical evidence for optimizing human-AI interactions in educational marketing contexts. AI fundamentally transforms educational technology marketing through trust-based mechanisms, requiring careful balance between innovation and humanization for sustainable adoption.