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3rd International Conference on Artificial Intelligence, Machine Learning and Big Data

Copenhagen, Denmark

Shahrzad Yaghtin

University, Tehran, Iran


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Title: How Machine Learning Can Help the Marketers to Communicate to the Customers More Successfully Through Creating More Relevant Digital Content

Biography

Biography: Shahrzad Yaghtin

Abstract

Digital content marketing is known as a strategic marketing approach focused on producing and distributing valuable, relevant, and consistent digital content to attract target audiences and to retain the customers. Content marketing can yield great results as it is an effective way to reach desired target audiences, also it enriches interactions with customers at every stage of their buyer journey. On the other hand, Machine learning is defined as the study of computer algorithms that allow computer programs to automatically improve through experience. Machine learning relies on working with small to large data-sets by examining and comparing the data to find common patterns and explore nuances. Machine Learning algorithms are characterized by a unique ability to learn system behavior from past data and estimate future responses based on the learned system model. This ability can help the content marketers to identify and provide the more relevant and useful information to the audiences. Therefore, the main purpose of this study is to describe how machine learinng can be used for identifiying more relevant and compelling digital content for improving communicayion with the customers and audiences. For this purpose, data were drawn from the 1156 questionnaires filled by the participants of three conferences and exhibition held in the energy sector. Python in Jupyter environment was used as the main program for data analysis maching learning purposes. In total, 4 main content classes were identified as the most popular and helpful content to communicate to the audiences more successfully.