Investigating the Impact of AI-Driven Predictive Analytics on Hyper-Personalized Marketing in Niche Retail Markets
Sonu Pradheen Kotapati *
University of Cincinnati, Cincinnati, Ohio, United States.
Kotapati Brahmini
R. V.R. & J.C.College of Engineering, Chowdavaram, Guntur, India.
*Author to whom correspondence should be addressed.
Abstract
This manuscript presents a well-executed and timely investigation into how AI-driven predictive analytics can empower niche retail markets through hyper-personalized marketing. It addresses a significant gap in the current literature by focusing on smaller retail businesses that are often excluded from mainstream AI applications. By demonstrating both quantitative and qualitative outcomes from real-world implementations, the study offers valuable insights into the democratization of AI technology. The findings are relevant for both scholars and practitioners, particularly those interested in digital transformation, SME competitiveness, and customer-centric marketing strategies.
This research uses both qualitative and quantitative methods as a mixed-methods design. The research uses case studies of particular niche retailers who applied AI tools which include Google Analytics and Dynamic Yield as well as predictive modeling software to optimize their marketing operations. Survey responses along with performance measurement data from businesses participate in the study to assess AI-based marketing strategies' success rate. The qualitative aspect gives background and perception into the issues and advantages of AI in real-life scenarios, whereas the quantitative aspect reveals trends in customer involvement, revisit rate, as well as income increase attributable to the use of AI.
The key findings demonstrate that AI-powered predictive analytics has a tremendous impact on the preciseness of customer targeting and increases sales by offering the personalized clients’ offers, product suggestions and timely messages. Businesses documented a 30% jump in customer retention rates while showing better results in email click-through and conversion rates. The research shows that businesses at any size can successfully implement these technologies through free or low-cost AI platforms which work well for their budget.
Finally, the study proves that AI can be an effective enabler for niche retailers who want to improve their marketing efforts regardless of the vast amounts of money invested. Subscribing to AI-assisted predictive analytics, small business can develop highly relevant and individualized experiences for their customers, thus nurturing loyalty and sustainable growth in the competitive markets.
Keywords: Impact, AI-Driven predictive, analytics, hyper-personalized, marketing, niche retail markets