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

31 October 2026, Version 1
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

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.

Keywords

Predictive Analytics
Decision-Making
Marketing Management
Customer Behaviour
Data Analysis
Demand Forecasting

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