" Social Media Marketing: Uncovering Consumer Sentiments"

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Ch Siddharth Nanda, Boya Venkatesu

Abstract

The emergence of social media has given birth to a wide range of innovative and advanced marketing strategies. The growth of many brands including e-commerce industries can largely be attributed to the widespread use of social media marketing strategies. The future of marketing is expected to see significant growth due to advancements in the shopping process facilitated by various social media platforms. Among these platforms, Facebook is at the forefront, offering distinctive and pleasurable customer experiences.


Purpose: The primary objective of this study is to examine the influence of social media marketing efforts through sentiment analysis, namely those conducted on the Facebook platform.


Design/methodology/approach: Both Primary and secondary data were collected and analyzed. NVivo Qualitative Analysis software was used for Sentiment analysis. The research employs a purposive selection approach and focuses on respondents who own a smartphone and use Facebook.


Primary data was obtained for the research via an In-depth Interview procedure with 32 participants.


Secondary data was gathered via literature reviews. Journals, books, and e-resources etc.


Findings: The presence of both “moderately” and “very positive” sentiment with a percentage of 75. This gives a sign that Facebook as a social media marketing platform is playing a key role in influencing their consumer decision-making process. The “theme references” reflected the responses that NVivo Software has tracked to analyze sentiments, wherein “Reference1 is 1 response and Reference 2 represents 2 responses” etc. This % of coverage reflected the significance of crucial factors that could help in creating customized marketing campaigns for its target group.  


These findings would be of immense importance in academia in relation to in-depth qualitative study and have managerial implications to attract customers with a focus on repetitive and impulse purchases by identifying “sentiments” from their responses.

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