JOURNAL ARTICLE

AI-Driven Retail Analytics: Leveraging Predictive Models for Consumer Goods and Retail Optimization

Ruchi Agarwal

Year: 2024 Journal:   Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023 Vol: 2 (1)Pages: 271-277

Abstract

The increasing complexity of consumer behavior, coupled with the globalized nature of retail, has prompted the adoption of advanced analytics to optimize operations and enhance customer experiences. Artificial Intelligence (AI) has emerged as a cornerstone of this transformation, enabling predictive models that drive data-informed decision-making in the retail and consumer goods sectors. This paper explores the role of AI-driven predictive models in optimizing retail operations, from demand forecasting and inventory management to personalized marketing and supply chain efficiencies. Through a detailed examination of the methodologies, use cases, and challenges in AI adoption, we aim to offer a comprehensive understanding of how predictive analytics is shaping the future of retail and consumer goods.

Keywords:
Analytics Predictive analytics Business Retail industry Big data Data science Marketing Computer science Data mining

Metrics

1
Cited By
0.95
FWCI (Field Weighted Citation Impact)
0
Refs
0.78
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Big Data and Business Intelligence
Social Sciences →  Business, Management and Accounting →  Management Information Systems
Customer churn and segmentation
Social Sciences →  Business, Management and Accounting →  Marketing
Stock Market Forecasting Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research

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