A Novel Approach to Identify the Promotion of Sales in Supermarkets using Machine Learning Algorithms

Prediction of sales promotion is a significant method to attract customers and enable retailers in successful planning and forecasting. The core objectives of this paper are to introduce a novel interpretable machine language algorithm to enhance the sales in supermarkets based on the buying behaviour of the customers, and to find the factor of sensitivity that stimulates, satisfies, and builds loyalty among the customers. Decision tree, gradient boosted trees, and support vector machine learning algorithms will be mainly used to compare the accuracy level and to analyse the promotion of sales in supermarkets based on the buying behaviour of customers, and also to find factors influencing customer retention.