Improved Advertising Using SEO Powered by Neural Networks

Abstract

Neural networks are optimizing content shaping and understanding. Going beyond internet forecasting reaching heights of real time prediction is made possible by SEO using these automated tools. By automating content production and adjusting methods to match changing search engines, AI-powered SEO tools revolutionize digital marketing. Real-time campaign modifications and highly customized consumer experiences are made possible using natural language processing, GPT models, and predictive analysis. Artificial intelligence and deep learning powered SEOs improve intelligence in many areas of the advertising industry.  The current study focuses on the algorithms used behind the AI-powered SEOs to get the desired results. A literature review to understand SEO in the current markets, budget ad campaigns accordingly. It uses neural network methods to calculate the advertisement launch and conversion rates. The study takes a precise quantitative approach to optimize the ad campaign, and improvise the results of it using budgeting, and this in turn to analyse the Click through rates and conversion rates of the customers using EVs. The research aims to implement neural network involving Relu activation function and sigmoid activation to predict the probability of customers opting for a test drive.