AI-BASED PRICING STRATEGIES AND CONSUMER BEHAVIOUR IN NIGERIAN TELECOMMUNICATION SECTOR

This study investigates the impact of artificial intelligence (AI)-based pricing strategies on consumer behaviour within the Nigerian telecommunication sector. With increasing adoption of AI technologies, pricing strategies such as Dynamic Pricing Implementation (DPI), Personalized Price Recommendations (PPR), AI-Driven Discount Optimization (ADO), and Real-Time Price Adjustment (RTPA) are transforming how telecom providers engage with users. However, issues of trust, fairness perception, and data transparency continue to shape consumer responses. Using a survey research design and a response rate of 364 out of 400 sample of telecom users, the study employed multiple regression analysis to evaluate the effect of each pricing strategy on consumer behaviour. Results reveal that all four AI-based pricing strategies have statistically significant effects, with RTPA showing the strongest positive influence, suggesting that timely and responsive pricing enhances user trust and purchase intention. Conversely, PPR and DPI, though statistically significant, exhibited negative beta coefficients, implying potential backlash due to perceived unfairness or lack of transparency. ADO also had a significant but weaker influence, indicating that the impact of discounts depends on targeting and timing. The study highlights the critical role of fairness perception and user understanding in determining the success of AI pricing tools in emerging markets. It concludes that while AI presents opportunities for revenue optimization and personalization, its effectiveness in Nigeria’s telecom industry depends on ethical deployment, user education, and transparency. Given the strong positive influence of RTPA, telecom providers should leverage it to offer responsive and competitive pricing while ensuring it does not disproportionately affect vulnerable users