Prediction of Customer Purchase Intention Using Linear Support Vector Machine in Digital Marketing

Abstract

Abstract Digital marketing is taken into account the well-liked method comparing to traditional marketing. It can be used by both researchers and academicians for social media marketing and to predict the customers purchase intention. The Proposed work revolves around some valuable information and processes in accordance to the behavior of customer during the online purchase. Business owners, scientists, researchers all post their ads, details on the Web so that they can be linked to owners quickly and easily by web scrap searching on searchable product websites to gain a lot of data from websites. Details on websites are stored in an unstructured manner. To avoid this issue, Web Scraping helps to gather unstructured content and turn it into a structured type that can be used for further study. Hence, customer price and rating of product evaluation and prediction has become an important research area. The analysis is done by Support Vector Machine (SVM-Linear) to gather several information and provide variation analysis. The major goal remains to investigate and analyze the extracted dataset using ML oriented algorithms with best accuracy possible. The analysis has a proper path to sentimental analysis of parameters in accordance to the ratings and price of the product to find proper accurate calculations.