ANALYSIS OF CONSUMER BEHAVIOR AND IMPROVEMENT OF MARKETING STRATEGIES BASED ON ARTIFICIAL INTELLIGENCE
Keywords:
artificial intelligence, consumer behavior, marketing strategy, personalization, machine learning, marketing analytics, customer segmentation, marketing effectiveness.Abstract
The rapid diffusion of artificial intelligence (AI) is transforming the way firms observe, interpret, and respond to consumer behavior. This study examines how AI-based analytics influence the effectiveness of marketing strategies. Drawing on a survey of 168 companies engaged in marketing activity, the paper develops a conceptual framework linking AI analytical technologies to consumer-behavior insights, marketing-strategy levers, and marketing outcomes. Multiple regression analysis shows that the firm-level AI Analytics Adoption Index is the strongest predictor of marketing effectiveness (β = 0.451; p < 0.001), and that the full model explains 58.7% of the variance in the Marketing Effectiveness Index. Companies in the highest adoption quartile reported, on average, conversion rates about 70% higher, customer-retention rates 17 percentage points higher, and marketing return on investment 1.8 times greater than firms in the lowest quartile. Despite these benefits, adoption remains uneven and is constrained mainly by cost, analytical-skills shortages, and data-quality limitations. The paper concludes with a staged set of managerial and policy recommendations for AI-driven marketing improvement.
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