The Role of Social Media Analytics in Digital Marketing
LOKESH SAINI
22GSOB2011079
UNDER THE GUIDANCE OF
MR. Ashish Kumar Singh
GALGOTIAS UNIVERISTY
ABSTRACT
The rise of the Internet and smartphones in the 21st century has created and developed social media as an extremely effective means of communication in society. In life, business, sports, and politics, social media facilitates the democratization of ideas like never before. Social media content gives consumers different information sources that they must decipher to discern its trustworthiness and influence in their own opinions. Marketers must be savvy about using social media in their attempts to persuade consumers and build brand equity. As social media has permeated our everyday lives, scholars in various disciplines are actively conducting research into this aspect regarding our way of life. In this scholarly endeavor, marketing has taken a leading role in this research endeavor as a discipline involving human communications and idea persuasion. Thus, rather than considering social media broadly across multiple disciplines, in this monograph, we concentrate on social media analytics in marketing. This monograph comprises the following four sections: • First, we provide an overview of social media and social media analytics (SMA). While much has already been said about social media generally, relatively less has been said about social media analytics. Thus, much of our focus is on SMA in terms of contributing to the current understanding of SMA in the field. • Second, we concentrate on social media analytics in marketing. We discuss practical industry perspectives and examples, as well as recent marketing research by academics. Notably, we show how analytics may be used to address concerns about social media privacy and help detect fake reviews. • Third, we summarize common tools for social media analytics in marketing. These methods can be complex, but they must be mastered for sound SMA practice. They encompass big data, artificial intelligence, machine learning, deep learning, text analytics, and visual analytics. • Fourth, we discuss trends and a future research agenda. We also discuss how SMA might be better integrated into higher education.
