Data Visualization and Analytics for Price Elasticity on Commodities Using Machine Learning Techniques

Nowadays, many commodities are being sold across restaurants. Many commodities would earn profit to the seller on the other hand some may provide loss. Predicting the price of a commodity leads to success in terms of sales. Machine learning practices are used to forecast the price elasticities of various commodities. The price elasticity model with the amalgamation of Ordinary least squares will lead to perceiving the seller’s demand. This process leads to an increased profit for Quick Service Restaurants. The seller can identify where the raw materials can be purchased very cheaply according to that price can be also increased or decreased on the facets like commodity exigency and relativism with the antiquated price.