Webform Optimization using Machine Learning

Forms are used in websites for improving business and user experience[3]. If the form length is big, then we get more information but information is less accurate and vice versa. Nowadays, A/B testing algorithm is being used for getting the optimal web form from a number of web forms to choose. A/B test distributes the forms uniformly to the visitors. The winning form will be the form which has more no. of conversions. So, after deploying new version of form, A/B test explores all the forms equally[1]. Even though some forms do not perform well, it still explores which is wastage of time and resources. So, there is more time given for exploration in A/B test. And also owner of website during testing period focuses more on testing than running the website, due to which there may be a loss of visitors. To overcome this problem, we can use some automated machine learning algorithms to predict the optimal web form from a number of forms to choose. These algorithms does not waste time and resources exploring inferior forms due to which we will get the results in less time and also we can simultaneously run the website.