Analysis and Prediction of Apple’s iphone Sales and Factors Causing Downfall using Deep Learning Techniques

In today’s world adults and children are leading a simple and easier life with the advent of smartphones, in specific Apple’s iPhones. Life has become so taxonomical that by just instructing Siri through voice or text commands, everyday chores can be done with ease. This work aims at proposing deep learning techniques to analyse and predict the sales of Apple iPhone. Sentiment Analysis is also done using product reviews provided by customers from various countries. As virtual work has become the new normal as a consequence of COVID-19, the proposed techniques would help the sales data analysts’ community in a large scale to spot the products which are on the fall and improve the sales. The proposed methodology also involves Text Mining techniques for companies from large scale to small scale to comprehend the customer reviews for Apple products better and to enhance the user experience. The results obtained as a result of deep learning techniques like CNN and Decision Tree models help to obtain a concrete conclusion for the analysis and prediction of the sales involving different versions of Apple iPhone.