Predictive Analytics for Enhanced Decision-Making: For Sales Forecast and Equilibrium in Supply and Demand

Predictive analytics is a data-based method used by organisations to estimate future events and customer behaviour. It uses past and present data, statistical methods, and computer-based models to identify possible future outcomes. In marketing management, predictive analytics helps businesses understand customers, forecast demand, improve advertising, manage inventory, and make better decisions. For example, an e-commerce company can study previous purchases and browsing activity to predict which products a customer may buy next. A bank can use customer transaction data to identify possible repayment risks. A retailer can estimate the demand for a product before placing a new order. This assignment explains the concept of predictive analytics, its role in decision-making, major applications, benefits, challenges, practical examples, and future scope. It also compares traditional decision-making with modern data-driven decision-making.

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Published
2026-10-31
DOI
https://doi.org/10.33774/coe-2026-bc6vk
Primary Topic
Big Data and Business Intelligence
Type
preprint
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Predictive Analytics for Enhanced Decision-Making: For Sales Forecast and Equilibrium in Supply and Demand

Anurag Yadav
Big Data and Business Intelligence
preprint

Predictive Analytics for Enhanced Decision-Making: For Sales Forecast and Equilibrium in Supply and Demand

Anurag Yadav
preprint en

Abstract

Predictive analytics is a data-based method used by organisations to estimate future events and customer behaviour. It uses past and present data, statistical methods, and computer-based models to identify possible future outcomes. In marketing management, predictive analytics helps businesses understand customers, forecast demand, improve advertising, manage inventory, and make better decisions. For example, an e-commerce company can study previous purchases and browsing activity to predict which products a customer may buy next. A bank can use customer transaction data to identify possible repayment risks. A retailer can estimate the demand for a product before placing a new order. This assignment explains the concept of predictive analytics, its role in decision-making, major applications, benefits, challenges, practical examples, and future scope. It also compares traditional decision-making with modern data-driven decision-making.

University of Lucknow (IN)
Big Data and Business Intelligence
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Predictive Analytics for Enhanced Decision-Making: For Sales Forecast and Equilibrium in Supply and Demand — Anurag Yadav · (2026) | TGRS Research Map | TGRS