Inbound E-Marketing Using Neural Network Based Visual and Phonetic User Experience Analytics

Inbound marketing is the process of attracting the probable customers to a business before they have any intention to become customers. An effective method for inbound marketing is creation of a positive psychological business environment to attract the customers. A significant portion of traditional business environment is moving online and the new business environment is the company website. One of the major elements in online inbound marketing is the website address and the website logo, which are the first factors of brand personality that the visitor to the company website encounters when looking up the website in a search engine. In this paper, a framework for inbound e-marketing using visual and phonetic user experience analytics is proposed. The popular websites are studied and the relationship between website page views and the English phonetic construction of the website address and its logo are analyzed. For demonstrating the relationship between the website logo and name and its appeal to the customers, the proposed model is trained by a neural network. The proposed model is capable to predict website page views based on the company logo and the website address. The experimental results show that the proposed framework is capable of recommending the strategy for inbound marketing for online business and services with high accuracy.