This analysis demonstrates how AI-driven demand forecasting impacts financial outcomes by improving in-stock consistency in e-commerce.
This project examines the significance of in-stock consistency and the function of AI-driven demand forecasting in the Indian e-commerce industry. Product availability is essential for retaining and satisfying customers in the cutthroat retail industry of today. While regular availability fosters trust, repeat business, and market share, frequent stockouts damage a brand's reputation, diminish customer loyalty, and result in revenue loss. The study demonstrates how AI-based demand forecasting enhances inventory control by precisely estimating demand, which lowers overstocking and understocking. Better use of resources, reduced operating expenses, and quicker supply chain reaction are the results of this. Uses machine learning models and predictive analytics to improve cash flow, reduce waste, boost margins, and align customer expectations with financial objectives. Examination of financial information, industry reports, and consumer insights.
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Karthik Bharath (2025) studied this question.
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