Automated Sales Prediction Model:- Kalu, Joshua A

ABSTRACT viii Sales prediction is a critical aspect of business strategy, that helps companies to forecast future revenue, allocates resources efficiently, manage inventory, and make informed decisions. Regression models are statistical techniques used to estimate the relationships among variables. Predictive analytics is a form of business analytics applying machine learning used to generate a predictive model for certain business applications. The problem statement ofthis research focus on the absolute errors which may occur between predicted and actual values, historical sales data and other relevant data might influence sales, inconsistencies in data handling and missing values, more complex models might be needed for non-linear relationships. The project focuses on the development of the automated sales prediction model that would be able to help companies forecast future revenue, allocates resources efficiently and manage inventory. The objectives of this research focuses on the development ofa platform for automated sales prediction model, build a database structure used to store data, design a module used to create new sale, design a platform that displays sales. The project was realized through the adoption ofprimary and secondary sources of data collection which includes interview, observation, questionnaire and the internet. The research methodology used is rapid-application development. The system is implemented by using Html, PHP and java script and MYSQL for the database. The results showed that the sales prediction uses regression models as a powerful tool for businesses to review the forecast future revenue and make data-driven decisions