Social Media Platform Prediction for Digital Marketing using Machine Learning Techniques

Abstract

Every business wants to connect with their users in seamless and efficient manner. Social media play vital role in achieving that goals. Social media plays vital role in the marketing of any business. But on the other side, there are so many social popular media platforms and it is difficult for businesses to choose which social media platform will perform better for them. This study focuses on choosing best social media platform for digital marketing using machine learning techniques. We studies various algorithms and then after careful consideration we pick Random Forest algorithm for choosing optimal social media platform. Machine learning is playing very important role in making informed decisions and we are taking advantage of that in the shape of utilizing past data related to various business categories to generate most accurate results. To train the model and make accurate results, we collected data from 10,000 businesses having various parameters like business category, location, audience demographics, and past advertisement data. After making dataset, we preprocessed and cleaned the data and to obtain better results from the model. We trained our model on 70% of the data and then tested it by 30% of the remaining data. Our model shows 77% accuracy in choosing social media platform for promoting their businesses. We also made a mobile application for the businesses so that they can use it and predict the best social media platform for promoting their business.