How To Engage Consumers Through Effective Social Media Use-Guidelines for Consumer Goods Companies From an Emerging Market

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Date

2021, 2021

Authors

Aydın, Gökhan
Uray, Nimet
Silahtaroğlu, Gökhan

Journal Title

Journal ISSN

Volume Title

Publisher

Universidad de Talca

Open Access Color

GOLD

Green Open Access

Yes

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Publicly Funded

No
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Top 10%
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Abstract

This study aims to establish actionable guidelines and provide strategic insights as a means of increasing the social media effectiveness of consumer brands. Post-related factors in addition to the contextual and temporal factors influencing consumer engagement (i.e., reposting, commenting on or liking posts), as an indicator of social media effectiveness, are considered in detail in the research model. Moreover, the model considers differences between industries as well as social media platforms. A total of 1130 posts made by four brands, two each from the durable goods and fast-moving consumer goods sectors, were collected from Facebook and Twitter in Turkey. Through predictive analysis, four different machine learning algorithms were utilized to develop easy-to-apply plans of action and strategies. The findings highlight the significant impact of videos, images, post frequency and interactivity on engagement. Furthermore, social media platforms and the brands themselves were found to be instrumental in influencing engagement levels, indicating that more than one formula is needed for effective social media management. The range and depth of the post-related factors (e.g., image type, video length, kind of interactivity) considered go far beyond those found in the significant majority of similar studies. Moreover, the unique setting and the novel data analysis algorithms applied set this study apart from similar ones. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Keywords

Brand fan pages, Customer engagement, Facebook, Machine learning, Post popularity, Social media, Twitter, post popularity, Facebook, HF5001-6182, Customer engagement, social media, Twitter, Brand fan pages, Machine Learning, Social media, customer engagement, brand fan pages, machine learning, Post popularity, Customer Engagement, Machine learning, Business, Brand Fan Pages, Post Popularity, Social Media

Fields of Science

05 social sciences, 0502 economics and business

Citation

WoS Q

Q2

Scopus Q

Q1
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OpenCitations Citation Count
35

Source

Journal of Theoretical and Applied Electronic Commerce Research

Volume

16

Issue

4

Start Page

1

End Page

23
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CrossRef : 36

Scopus : 38

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Mendeley Readers : 392

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