The objective of the proposed system is to predict if an ad will be clicked by the user or not
In the recent time, internet and social media users have grown tremendously. As a result of this, many companies prefer to advertise their products on websites and social media platforms. However, targeting the right audience is still a challenge in online marketing. Companies spend lot of money to display the advertisement of their products and if the consumers are not likely to buy the product, the advertisement cost can be a burden for the company. This comes as a challenge for the company to analyze online internet users who view advertisements on their web pages. Always, a higher value of Click Through Rate plays a crucial role in increasing the revenue of the business. Showing the user an Ad that is relevant to his/her need greatly improves user’s satisfaction. It’s important to predict the Click Through Rate of ads accurately. Unsuccessful online advertising leads to a variety of problems. First, it has a bad influence on user experience, especially when the user is searching on the website. That's because the users of search engine always have clear searching purpose and needs. Second, bad recommendation of advertising will reduce the revenue of both the advertisers and the search engine company. That is why advertisers need to know if an ad will be clicked by the users or not. In order to advertise successfully predicting whether a particular consumer click on an advertisement displayed plays a crucial role.
https://www.kaggle.com/fayomi/advertising/version/1# The data consists of 10 variables: • Daily Time Spent on Site • Age • Area Income • Daily Internet Usage • Ad Topic Line • City • Male • Country • Timestamp • Clicked on Ad