The Impact of Generative Artificial Intelligence on Marketing Decision-Making in Online Retail Companies
Keywords:
Generative Artificial Intelligence, Marketing Decision-Making, Customer Relationship Management, Online Retail, Digital Marketing, Customer Data AnalyticsAbstract
This study aimed to examine the impact of generative artificial intelligence on improving marketing decision-making effectiveness through enhanced data analysis capability, faster decision processes, and improved customer behavior prediction in online retail companies. The research employed an applied quantitative approach using a descriptive-survey design. The statistical population consisted of marketing managers and specialists working in online retail companies in Tehran with experience using AI-based marketing tools. A total of 180 participants were selected through purposive sampling. Data were collected using a structured questionnaire based on a five-point Likert scale. Content validity was confirmed by expert evaluation and reliability was verified using Cronbach’s alpha coefficients. Data analysis was conducted through Structural Equation Modeling using SPSS and SmartPLS software. The results indicated that generative artificial intelligence had significant positive effects on marketing data analysis capability, decision-making speed, and customer behavior prediction. These variables also played significant mediating roles in enhancing marketing decision effectiveness. Structural path coefficients were statistically significant at p < 0.01, and the model explained a substantial proportion of variance in marketing decision effectiveness, demonstrating strong model fit. The findings suggest that generative artificial intelligence transforms marketing decision-making from intuition-based processes into intelligent data-driven systems, improving agility, accuracy, and overall marketing effectiveness in online retail organizations.
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