How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market
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 lik...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Journal of Theoretical and Applied Electronic Commerce Research |
| Subjects: | |
| Online Access: | https://www.mdpi.com/0718-1876/16/4/44 |
| _version_ | 1797520765569990656 |
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| author | Gokhan Aydin Nimet Uray Gokhan Silahtaroglu |
| author_facet | Gokhan Aydin Nimet Uray Gokhan Silahtaroglu |
| author_sort | Gokhan Aydin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T08:01:15Z |
| format | Article |
| id | doaj.art-a78226be8e6543709b1fe84dd386aa10 |
| institution | Directory Open Access Journal |
| issn | 0718-1876 |
| language | English |
| last_indexed | 2024-03-10T08:01:15Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Theoretical and Applied Electronic Commerce Research |
| spelling | doaj.art-a78226be8e6543709b1fe84dd386aa102023-11-22T11:28:48ZengMDPI AGJournal of Theoretical and Applied Electronic Commerce Research0718-18762021-01-0116476879010.3390/jtaer16040044How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging MarketGokhan Aydin0Nimet Uray1Gokhan Silahtaroglu2Fashion Marketing Department, University of East London, London E16 2RD, UKBusiness Administration Department, Kadir Has University, Istanbul 34083, TurkeyManagement Information Systems Department, Istanbul Medipol University, Istanbul 34810, TurkeyThis 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.https://www.mdpi.com/0718-1876/16/4/44social mediacustomer engagementbrand fan pagespost popularitymachine learningFacebook |
| spellingShingle | Gokhan Aydin Nimet Uray Gokhan Silahtaroglu How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market Journal of Theoretical and Applied Electronic Commerce Research social media customer engagement brand fan pages post popularity machine learning |
| title | How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market |
| title_full | How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market |
| title_fullStr | How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market |
| title_full_unstemmed | How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market |
| title_short | How to Engage Consumers through Effective Social Media Use—Guidelines for Consumer Goods Companies from an Emerging Market |
| title_sort | how to engage consumers through effective social media use guidelines for consumer goods companies from an emerging market |
| topic | social media customer engagement brand fan pages post popularity machine learning |
| url | https://www.mdpi.com/0718-1876/16/4/44 |
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