Optimizing Dynamic Pricing through AI-Powered Real-Time Analytics: The Influence of Customer Behavior and Market Competition
DOI:
https://doi.org/10.55737/qjss.370771519Keywords:
Dynamic Pricing, AI-Powered Real-Time Analytics, Customer Behavior , Market Competition, Business OperationsAbstract
This study explores the role of AI-powered real-time analytics in enhancing the effectiveness of dynamic pricing strategies within competitive markets. Leveraging the growing relevance of artificial intelligence in business operations, the research investigates the direct impact of AI on pricing outcomes while assessing the moderating effects of customer behaviour and market competition intensity. Drawing on quantitative analysis, the study reveals that AI-driven pricing significantly improves pricing effectiveness, especially in highly competitive industries. However, price sensitivity among customers weakens the positive influence of AI, suggesting the need for businesses to carefully navigate AI applications in dynamic pricing. The study provides crucial insights for firms to enhance their real-time pricing strategies, emphasizing the significance of market competition and customer preferences. This study provides empirical evidence of AI's impact on pricing dynamics, contributes to the academic literature on AI integration in business models, and offers practical recommendations for businesses. The implications underscore the strategic advantage of AI in competitive environments yet caution against the indiscriminate use of dynamic pricing in markets with high customer price sensitivity. This study establishes a foundation for future research on the integration of AI in real-time pricing decisions and its broader impact on market competitiveness and consumer behaviour.
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