AI-Driven Data Analytics Unveiling Sales Insights from Demographics and Beyond - Raju Mudunuru, Krishnamurty; Remala, Rajesh; Kali Sankar Nagarajan, Sevinthi (International Journal of Computer Sciences and Engineering, 2024)
Leveraging a synthesis of literature review and case studies, it illuminates how AI empowers organizations to discern intricate patterns and correlations within vast datasets. Through sophisticated algorithms and machine learning techniques, AI facilitates the nuanced understanding of the interplay between consumer demographics and purchasing behaviors, enabling targeted marketing strategies. Moreover, the study extends beyond demographics, encompassing psychographic, geographic, and behavioral factors through the amalgamation of diverse data sources. By employing predictive modeling, AI enables businesses to forecast market trends, optimize product positioning, and deliver personalized customer capabilities. Ethics around artificial intelligence-driven data analytics, incorporating consumer discretion and algorithmic fairness, are also addressed. Transparent methodologies and regulatory compliance are emphasized as crucial elements in fostering trust and mitigating risks. This paper explores the utilization of AI-driven data analytics in uncovering profound sales insights derived not only from demographics but also from diverse sources beyond traditional parameters. Machine learning deeper into consumer behavior patterns, market trends, and socio-economic indicators to gain a comprehensive understanding of their target audience. The paper discusses various methodologies employed in AI-driven data analytics, including predictive modeling, clustering techniques, and sentiment analysis, to extract valuable sales insights. Furthermore, it shows how crucial it is to incorporate data from various sources, including social media, geospatial information, and transactional records, to enrich the analytical process and enhance the accuracy of predictive models. Through real-world case studies and examples, this paper demonstrates how AI-driven data analytics can empower businesses to optimize their sales strategies, personalize marketing campaigns, and identify untapped market opportunities. By leveraging the capabilities of AI, organizations can move beyond traditional demographic segmentation and uncover nuanced insights that drive competitive advantage and foster sustainable growth.