A data-driven approach is a method of making decisions, solving problems, and conducting research based on data and evidence rather than intuition, opinion, or tradition. In a data-driven approach, data is collected, analyzed, and used to inform and guide various processes, including business strategies, scientific research, policy-making, and more
Published in Chapter:
Sentiment Mining: A Data-Driven Approach for Optimizing Digital Marketing Strategies
Anjali Daisy (St. Joseph's Institute of Management, Trichy, India)
Copyright: © 2024
|Pages: 18
DOI: 10.4018/978-1-6684-9324-3.ch009
Abstract
With millions of users active on social media, businesses have the opportunity to reach a vast audience and gain valuable insights into customer preferences and behavior. However, with the increase in social media usage, the challenge for businesses is to effectively analyze and interpret the vast amount of data generated by social media and other digital channels. This is where sentiment mining comes into play. Sentiment mining involves using machine learning algorithms to analyze and classify online content, such as social media posts and reviews, to determine the overall sentiment or tone of the content. The purpose of this chapter is to explore the concept of sentiment mining and its application in optimizing digital marketing strategies. The concept of sentiment mining has gained significant attention in recent years, with businesses recognizing its potential to gain insights into customer sentiment and preferences. This chapter aims to bridge this gap in literature and explore the potential of sentiment mining in optimizing digital marketing strategies.