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The purpose of this study is to analyze how food brands use UGC on their social media as part of their marketing strategies to promote their products and services. This study in particular will focus on how chain businesses and small businesses use UGC on their Instagram profiles, and analyze trends regrading the characteristics present within this content. Therefore, a content analysis was the chosen methodology to directly evaluate UGC and discover key findings related to popular UGC trends and consumers' comments associated with selected posts.
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Source: @starbucks on Instagram
Content Analysis
Content Analysis
A content analysis was employed to consider the UGC food brands utilized to strengthen their social media presence on Instagram and consumers’ envious indications resulting from their exposure to Br–UGC. A content analysis allows for quantitative data to be collected to answer and test the four research questions and hypotheses. This method will be used because, according to Davis and Lachlan (2017), content analysis specializes in quantifying content, and permits researchers the ability to answer multiple research questions by analyzing media texts and producing meaningful contextual analysis reports (p. 222). Additionally, this method helps evaluate the research questions’ independent and dependent variables, and allows for an easier study of the relationships between them through associated concept categories and cross-tabulation analyses. Content analysis allows this study to focus on quantitative information regarding food brands’ use of UGC on their Instagram profiles and analyze other users’ interactions with it.
Procedure
Procedure
The sampling method for this research utilized a stratified random sampling methodology. In total, 200 Instagram posts were analyzed, 100 of which were from the Instagram accounts of chain businesses and 100 were from small businesses. Every fifth oldest post on a food brand’s profile was assessed for analysis. In the event a selected post could not be identified as UGC, the following post(s) were considered until a post featuring UGC was identified.
This research also used Export Comments, a program that extracts comments from social media posts and exports them into an excel document. This tool was used to make assessments during the comment level of analysis for each post. The first 20 comments for each post was considered for analysis. If a post had less than 20 comments, Export Comments was not used. Chain businesses and small-businesses were chosen for this study to strengthen external validity and to provide useful insight for a diverse range of food brands regarding the practice of UGC activity on these brands’ social media accounts.
Export Comments spreadsheet for an Instagram post in the sample
Regarding criteria for inclusion, samples must clearly demonstrate that the original post was created by a user. Confirmation that samples were created by users were evident if the food brand tagged the original creator in their repost of their content. Additionally, if a food brand screenshot and reposted content generated by other users and they included their username and profile icon, this confirmed that the selected post was UGC. The data analysis collection process took place during a four-week period, starting on February 25, 2022 and finishing on March 25, 2022. The first two weeks were dedicated to coding for posts on the Instagram accounts of chain businesses and the last two weeks focused on posts on small businesses’ accounts.
The second coder coded for 20 Instagram posts, 10 of which were from the Instagram profiles of chain businesses and 10 from the profiles of small businesses. To ensure intercoder reliability, the two coders for this study practiced with a sample data set of four posts (two from chains and two from small businesses). The second coder also coded at the comment level and at the profile level. The posts and comments used in the pilot test were not included in the actual samples coded. If the reliability index was above 80 percent, the research commenced. If it was below 80 percent, the coders would discuss their data and rework the codebook and codesheet. At the end of the study, the two coders discussed their findings and calculated the intercoder reliability rate. The two independent coders for this study were in agreement on 100% of coding determinations, indicating fair internal validity. Moreover, this study’s intercoder reliability index is 100% (1.00), which indicates that this research provides acceptable reliability.
Chain Businesses
Chain Businesses
To represent chain businesses, content was selected from the Instagram profiles of 10 fast food chains from a list of the top 50 food chains in America according to Ang (2020): McDonald’s, Starbucks, Chick-fil-a, Taco Bell, Burger King, Subway, Wendy’s, Dunkin’, Panera Bread, and Chipotle. Ten posts from each account were selected.
Small Businesses
Small Businesses
To represent small businesses, Instagram posts on the profiles of 10 restaurants from each of the five main regions of the U.S. – Northeast, Southeast, Midwest, Southwest, and West – were selected for analysis. Every state in each region was entered into a random number generator and five states were randomly selected; a state could be selected more than once. There was a Google search for the two highest-rated restaurants that are small businesses in each selected state, and they were chosen according to their five-star ratings on Google. Two Instagram posts on each of their profiles were analyzed. In the event a restaurant did not have an Instagram profile, the next highest rated restaurant with a profile was selected.
Source: National Geographic
Research Instrument
Research Instrument
The research instruments that was used to conduct this study were a codebook and a codesheet in the format of a Google form. These instruments focused on specific concepts that helped answer the research questions, and provided further insight to this area of analysis for other professionals in the field to study. The universe of content for this study considered brand–related (Br) UGC on food brands’ Instagram accounts from January 1, 2020 to January 1, 2022. The units of analysis were food brands’ Instagram accounts, Br–UGC on food brands’ Instagram accounts, and comments on Br–UGC. There were three levels of analysis: profile level (food brands’), post level (Br–UGC), and comment level (comments posted on the selected Br–UGC). Cross-tabulations were designed to investigate the differences between chains and small-businesses when leveraging Br–UGC on Instagram. Moreover, cross-tabulation analyses can provide deeper insights regarding trends associated with the practice of utilizing UGC for marketing purposes on Instagram.
Click below to read about the key findings that were uncovered in this study:
This study was administered in 2021-22 as a component of Endicott College's Senior Thesis requirement for undergraduate students. This research pertains to education, theories, concepts, and practices within the communication field. Please provide any feedback, queries, or recommendations to mhale245@mail.endicott.edu.
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