MANUFACTURED AUTHENTICITY: HOW BEAUTY BRANDS USE CONSUMERS' CONTENT TO COMMUNICATE BRANDING MESSAGES - DIVA

Örebro University
School of Humanities, Education, and Social Sciences
Media and Communications

 Manufactured Authenticity: How Beauty Brands Use
 Consumers' Content to Communicate Branding Messages

 Social Analysis, Second Cycle
 Independent Project, 30 credits, 2020
 Author: Meagan Nouis
 Supervisor: Göran Eriksson

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Abstract

While beauty brands are often known to set industry trends, the consumers pave the way for
branding communications on social media. Companies have adapted their marketing strategies to
build interactivity into their branding outreach. Therefore, this study answers the question, “How
do beauty brands utilize consumer posts to convey branding messages?” To answer this, a
content analysis was performed using two sets of data: brand posts (n=314) from July 2019 and
January 2020, and consumer posts (n=100) which tagged the beauty brands. Using consumer
culture theory, the study examines several themes, including branding messages, consumer
engagement, and brand authenticity. Results reveal that beauty brands typically use consumer-
produced content to convey experiential or user-centered branding messages, while company-
produced content most often includes informative and emotional messages. Further discussed is
the inclusion of Calls-to-Action (CTAs) which brands use to encourage user engagement. This
study found a significant correlation between posts with CTAs and increased numbers in Likes
and comments; however, these numbers are often misleading and represent manufactured
engagement. At the same time, users were found to engage more with the brands when
incentives or self-promotion opportunities were available.

Keywords: branding messages, digital self-branding, Instagram marketing, consumer
engagement, content analysis

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 Table of Contents
1. Introduction 4

2. Literature Review 6
 2.1. Key Concepts 6
 2.2. Social Media Influencers (SMIs) and General Users 7
 2.3. Social Media Platforms 9
 2.4. Consumer-Branding 9
 2.5. Consumer Engagement 11
 2.6. Literature Review Summary 11

3. Research Question and Hypotheses 12

4. Methodology 15
 4.1. Research through Content Analysis 15
 4.2. Criteria and Design 16
 4.3. Consumer Posts 17
 4.4. Codebooks and Coding Process 18
 4.5. Pilot Study 20
 4.6. Ethical Considerations 20

5. Results 21
 5.1. Data Adjustments for Outliers 21
 5.2. Brand-created Content vs. User-created Content 21
 5.3. Post Elements 22
 5.4. Engagement 23
 5.5. Branding Messages 25

6. Discussion and Implications 28
 6.1. Branding Messages 28
 6.2. Engagement and Authenticity 29
 6.3. Self-Branding and “Justification” 32

7. Study Limitations and Solutions 32
 7.1. Original study 33
 7.2. The Solution 34
 7.3. Limitations with Engagement 34
 7.4. Intercoder Reliability 35

8. Conclusion 36

References 38

Appendix 1 41

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1. Introduction

 With the world becoming more digitally connected than ever before, companies are
quickly evolving their marketing strategies to reach global audiences. Having an online presence
has become a marketing standard for any business, as it allows consumers the opportunities to
connect with and discover the brand and its products. This business-customer relationship is
achieved through social media and social media marketing. “Social media” refers to a plethora of
digital platforms where user-generated content is produced and shared with others. Although
Facebook, YouTube, and Twitter have consistently dominated as the top social networks (Kallas,
2020), other platforms are quickly catching up, along with entirely new digital communications
strategies tailored to fit these platforms and their users. Instagram has exploded into popularity in
recent years, as has the term “influencer,” which refers to an online personality who has gained a
massive following from sharing digital content (Lou and Yuan, 2019).
 With traditional online marketing methods continuously losing impact due to ad-blockers
and specialty web browser plug-ins (De Veirman, Cauberghe and Hudders, 2017; De Veirman
and Hudders, 2020; Pöyry et al., 2019), businesses are using new tactics to reach audiences and
build brand recognition. Social Media Influencers (SMIs) have become ubiquitous across all
forms of social media. SMIs are “regular” people who have achieved a successful online profile,
and companies have been quick to recognize the potential for advertisement opportunities
through sponsored posts and endorsements. A staggering 94% of marketing campaigns which
collaborated with an influencer were reported effective (Ahmad, 2018, cited in Lou and Yuan,
2019). This suggests that influencer marketing will continue to play a large part in marketing
strategies.
 Existing research has consistently proven the effectiveness of celebrity endorsements due
to their ability to convey meaning and identity. Pöyry et al. (2019) provides a cohesive
description: “The culturally relevant symbolic meanings first reside in the celebrity, and, through
the endorsement, they transfer to a product, and from the product to the consumer” (p. 337). We
are in a new age of “celebrity” endorsements because social media influencers are not traditional
celebrities. SMIs have attained followings through their own content-generation, thus their
method and style of sharing a sponsored post online is perceived as less “commercial” to their
followers (Pöyry et al., 2019). That being said, SMIs have their very own symbolic meanings

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which become familiar to their followers. While influencer marketing could be seen as
disadvantageously narrow in consumer reach, most research explains the value in using niche
SMIs to promote relatable products (Neal, 2018). Influencers come from all professional and
cultural backgrounds. Therefore, companies which choose to collaborate with SMIs should
consider their primary audience and which influencers would be most congruent for the
sponsored product.
 Because influencer marketing has quickly become front and center for online businesses,
it comes with an immense amount of unexplored research questions. Voorveld (2019) offers a
helpful overview of existing research in social media marketing and brand communications;
research in this area is increasing exponentially, but Voorveld et al. (2018) identifies the majority
of studies focused either on Facebook by itself or “social media platforms” as a whole. While
Facebook is understandably the most studied platform--due to being one of the first social media
platforms and attaining global popularity--Voorveld (2019) suggests new research should break
away from Facebook as newer platforms are gaining traction. Likewise, limited research exists
about how consumers play a role in branding communications. Because brands are using SMIs in
their marketing efforts, branding methods have shifted and become more casual and low-effort.
 Brands often face the challenge of delivering consistency in their messages and content
across different media outlets. SMIs are a recent addition to online marketing, and hence, an
extra obstacle to overcome when achieving coherent branding. Because of this, many questions
arise around the topic of branding communications and how messages are delivered from
consumers versus the messages shared by the company itself. Analysis of language use, photo
elements, calls-to-action, hashtags, emotional elements, and more are necessary to better
understand regular consumers and their role in brand communications. As companies continue to
navigate online communications strategies, it is important to understand how branding messages
are changing and what that means when growing a following on social media. With all of this in
mind, and by following Voorveld’s recommendations, this paper centralizes around the social
media platform Instagram and how branding messages change between company-produced
content and consumer-produced content. More specifically, the aim of this paper is to answer the
research question: “How do beauty brands utilize consumer posts to convey branding
messages?”

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 To answer this question, a literature review was conducted to identify existing research in
this field. The literature review points to key concepts surrounding online branding, consumer
behavior, and company-audience engagement. The literature review also identifies possible
research gaps and where further research is necessary. This transitions into the present study
including the methodologies, statistical results, and study implications. Finally, the paper ends
with my concluding thoughts and suggestions for future research.

2. Literature Review

 Before presenting my own research, it is important to introduce existing literature as a
reference point. This not only identifies commonalities within previous findings, but it also
includes a comprehensive look at the theories and methodologies used when conducting research
in media and communications--specifically online branding and consumer behaviors. Thus, the
results from the literature review offer relevant guidance for the present study.

2.1. Key Concepts

 With social media and online marketing constantly changing and developing, the existing
research appears to be somewhat scattered and incohesive (Sundermann and Raabe, 2019;
Voorveld, 2019). Certain communicative themes have emerged within marketing and social
media research, which will be acknowledged in this paper; however, many concepts remain
unexplored. Therefore, the current study shall attempt to expand on these themes and
subsequently contribute to the existing body of research within media and communications.
 While online advertising has been utilized by companies since the beginning of the
Internet, “social media” completely changed how brands view and navigate online resources.
Research has proven this as the marketing messages themselves have shifted over time from
product-centered to more informative and personalized (Ashley and Tuten, 2014; Shen and
Bissell, 2013). This is fitting given that “social media” is exactly that--social. Companies have
adapted to the interconnectedness of social media platforms, and rightfully so, as companies face
the ever-growing amount of ad-blockers installed by users (De Veirman, Cauberghe and
Hudders, 2017; De Veirman and Hudders, 2020; Pöyry et al., 2019), preventing organically
sponsored ads from reaching larger audiences. Additionally, social media have led to companies

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losing significant control over their branding communications (Rokka and Canniford, 2016).
This is due to the abundance of review websites and the freedom for users to share opinions and
criticisms on social media platforms. Thus, the emergence of electronic word-of-mouth or
“eWOM” has become a target branding strategy for marketers (De Veirman and Hudders, 2020;
Loureiro, Serra and Guerreiro, 2019; Sung, Kim and Choi, 2017; Voorveld, 2019). Companies
have leveraged their audiences or “regular consumers” as a way of brand communication, and
even more recently, “social media influencers” (SMIs).

2.2. Social Media Influencers (SMIs) and General Users

 Social media influencers are the new spokespeople of brand campaigns. They have
become ubiquitous across social media in recent years, and marketing companies continue to
increase their budgets on SMI endorsements (Schouten, Janssen and Verspaget, 2019; Stubb,
Nyström and Colliander, 2019; Voorveld, 2019). “Social media influencers” have been defined
differently (Klassen et al., 2018; Lou and Yuan, 2019; Sundermann and Raabe, 2019), but they
are commonly understood and accepted as individuals who have gained a significant following
through social media platforms from sharing original content (De Veirman, Cauberghe and
Hudders, 2017). Studies have observed that most of the successful SMIs encompass attributes of
authenticity, relatability, and likeability (De Veirman and Hudders, 2020; Neal, 2018; Schouten,
Janssen and Verspaget, 2019). While several articles claim SMIs to have “expertise” in various
lifestyle areas, such as interior design, fashion, fitness, etc. (De Veirman, Cauberghe and
Hudders, 2017; Lou and Yuan, 2019; Sundermann and Raabe, 2019), not every SMI fits into the
“guru” category. Many influencers gain followings for their personalities, photography styles, or
entertaining content disregarding their professional backgrounds. “Influencers” can have
anywhere from a few thousand to several millions of followers across different platforms. While
no exact number of followers defines an influencer, research generally concludes SMIs are
people who create their own content and have the ability to actually influence consumer behavior
(De Veirman, Cauberghe and Hudders, 2017; Klassen et al., 2018; Neal, 2018).
 Many aspects of influencer marketing crossover into the much-researched topic of
celebrity endorsements. Using a celebrity figure has proven highly successful in branding efforts
for decades (Lou and Yuan, 2019; Schouten, Janssen and Verspaget, 2019; Sundermann and

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Raabe, 2019). Thus, it is no surprise that popular online personalities produce similar marketing
effects as traditional celebrities. SMIs, however, are a modern-day phenomenon; they make their
impact by maintaining the “social” aspect of social media, which in turn, drives higher brand
attitudes than traditional celebrities (De Veirman and Hudders, 2020; Schouten, Janssen and
Verspaget, 2019). Companies today utilize SMIs as a way to reach target demographics,
especially younger audiences who use social media platforms more often than older generations
(De Veirman and Hudders, 2020; Lou and Yuan, 2019; Sundermann and Raabe, 2019). Reaching
these different target audiences has become much easier and more efficient for companies,
whereas before, traditional celebrity endorsements could reach larger audiences but were more
general and not targeted towards niche demographics.
 Of course, many traditional celebrities have a social media presence and could also fall
under the category of “influencer.” However, in terms of social media marketing, research has
explored the differences of sponsored posts between traditional celebrities versus social media
influencers, and results have shown a much higher brand attitude towards SMIs and their
affiliated endorsement (Schouten, Janssen and Verspaget, 2019). Several conclusions have been
drawn about the power of SMI endorsements--one of them being their perceived authenticity (De
Veirman and Hudders, 2020; Neal, 2018). Research has found consumers tend to be resistant
towards celebrity endorsements because they believe celebrities have ulterior motives (Neal,
2018). In other words, celebrities will endorse products “just for the money.” When followers
see sponsored posts from SMIs, however, they tend to trust SMIs’ intentions or understand the
need for SMIs to accept endorsements in order to continue creating content for their followers
(Stubb, Nyström and Colliander, 2019).
 Influencer endorsements also communicate a better sense of relatability compared to
celebrities (De Veirman and Hudders, 2020; Neal, 2018). SMIs emulate “regularity” and are
active in sharing their personal lives, which is largely part of the appeal for others to “follow”
them on social media. Meanwhile, traditional celebrities attain a certain “untouchable” trait about
them that disconnects them from their mass of fans. SMIs thrive because of their seemingly
“regular lives” and the connectedness between them and their followers, and marketers use this
to expand their branding outreach.
 The discussion of SMIs and influencer marketing is important to consider when looking
at online branding strategies. Not only are companies using SMIs more frequently, but general

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consumers are working to achieve “influencer status.” Therefore, general users with low follower
counts are mimicking SMIs as a technique to grow their own followings.

2.3. Social Media Platforms

 The majority of communications research dedicated to social media marketing focuses on
either Facebook exclusively, or an umbrella of “social media platforms” for their measurements
(Sundermann and Raabe, 2019; Voorveld et al., 2018; Voorveld, 2019). This leaves large gaps
for other platforms to be studied more closely, which this paper achieves. Voorveld (2019)
explicitly recommends Instagram to be more thoroughly researched as its immense popularity
has led to entirely new marketing approaches. Instagram is a social media platform used for
sharing photos or video clips accompanied with captions and “hashtags.” Each post has its own
comments section where users can leave direct replies and “tag” other users. Comments sections
can be publicly viewed, but the platform does include other features where private messages can
be sent between users.
 Previous social media research has attempted to measure the level of interactivity
between businesses and their audiences; for example, studies which observed Facebook
engagement have recorded the numbers of Likes, shares, and comments received on public posts
and used these quantitative values as a determinator for “outreach success” (Grigsby, 2020; Shen
and Bissell, 2013). Instagram has similar Like and comment features (and is owned by
Facebook); however, the exact numbers of Likes and comments can be misleading, and the
number of shares is hidden information to public users.

2.4. Consumer-Branding

 Online communication strategies are evolving and consequently being perceived
differently by consumers. In their research paper, Rokka and Canniford (2016) explain the
evolution of branding messages and how consumers actively contribute to the production of
“brand assemblages.” The idea stems from consumers acting as participants in a brand’s identity-
-most recently by posting original content, such as selfies, which incorporate a particular brand,
and thus the brand’s meaning is molded through “cultural transfer” (Shen and Bissell, 2013).

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Social media have consistently been a digital hub for self-expression opportunities. For some
users, their personal identities are shaped through brand-identities; therefore, many people
choose to incorporate brands into their own shared images, referred to as “brand-selfies” by
Sung, Kim and Choi (2017). Their article goes on to explain the existence of brand-selfies as an
extension of the brands’ own identities. As a result, brands lose a bit of control over their
branding messages. Similarly, after conducting a visual content analysis, Rokka and Canniford
(2016) concluded that “selfies are becoming a nodal point at which official brand assemblages
and consumer microcelebrity assemblages intersect. This intersection potentially undermines
stable symbolic and material properties of heritage brands through heterotopian selfie practices”
(ibid, p.1806).
 Brand-selfies are prevalent on platforms such as Instagram. While companies could face
unstable branding messages, many of them have utilized these brand-selfies within their own
strategic communications practices. This largely explains why “influencer marketing” has
skyrocketed into popularity in recent years. Companies have quickly realized the impact
audiences have in regards to electronic word-of-mouth, and as a result, companies have adapted
their marketing methods to utilize these user-generated marketing opportunities. As mentioned
earlier, SMIs have become increasingly popular across the Internet on numerous social media
platforms because of their ability to generate brand loyalty; both the company and the influencer
benefit from sponsorships. Generally, sponsored posts on Instagram are in line with the
influencer’s lifestyle, and most likely the lifestyles of the followers, which makes influencer
marketing a prime tactic to reach target audiences (Lou and Yuan, 2019).
 While influencers are compensated for their brand-selfies, many “regular” users are
voluntarily active (whether they are aware of it or not) in the participation of brand marketing.
Sometimes regular users purposefully create misleading posts which appear sponsored by certain
brands in order to build their own followings (Grigsby, 2020). This brings an interesting dynamic
when evaluating branding messages. Prior to social media, “self-branding” was virtually non-
existent. With the evolution of influencers, however, many individuals have actively worked to
build their own followings as a way of eventually gaining legitimate sponsors and advertising
compensation (Grigsby, 2020). When posting photos to Instagram, users have the ability to “tag”
other accounts indicating that the tagged accounts are somehow relevant to the post. This
includes users tagging official company accounts on Instagram. By tagging others--more

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specifically beauty companies--visitors can view the tagged posts on the brands’ profiles.
Although the posts are presumably related to the brand itself, many times users will tag multiple
brands, sometimes dozens, which are all within the same industry or lifestyle (Rokka and
Canniford, 2016). Users use this technique for exposure of their own content. The more brands
they include, the more chances of others seeing these posts when visiting the brand accounts’
pages. Because there are no restrictions for who can tag or be tagged, all posts, regardless of their
relevance, can appear in company accounts’ profiles.

2.5. Consumer Engagement

 Previous studies have analyzed the levels of engagement between consumers and brands.
Most of these studies, however, only reviewed Facebook pages for business accounts. Shen and
Bissell (2013) performed a content analysis of six beauty brands and examined how they retained
“brand loyalty” among consumers. From their findings, they determined companies which had
higher posting frequency, and which shared posts containing interactive questions for their
audiences received the most attention--thus, receiving the highest scores of brand awareness and
loyalty according to their study conclusions. Similarly, in a netnography approach, brands which
showed higher social media engagement on Instagram were determined to have “online success”
(Loureiro, Serra and Guerreiro, 2019). In both of these studies, quantitative data were used to
measure empirical concepts, suggesting that further research methods are needed in this area.
 The differences in interactivity levels could be a result of several different elements.
First, branding pages are more inclined to build relationships with consumers as part of their
marketing strategies. Higher levels of interaction strengthen the “emotional bond” between
consumers and the companies (Ashley and Tuten, 2014). Further, brand pages also offer
incentives through hosting contests and “calls-to-action” (CTAs). One example is the push for
followers to Like, comment, and share certain posts to qualify for gift cards or free products.
There are currently no known studies which measure engagement levels when CTAs are present.
Consequently, the current paper addresses this.

2.6. Literature Review Summary

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 Social media platforms have allowed increased opportunities for companies to better
connect with their target consumers, both through the use of their own branding accounts and
through influencers who have successfully generated their own audiences. Companies have
shifted from traditional celebrity endorsements to social media influencers, and their branding
practices overall have become more “casual.” Furthermore, consumers have historically looked
to pop culture, celebrities, and brand identities when developing their personal identities.
Therefore, when consumers choose to include brands in their social media posts, branding
messages and “assemblages” become unstable.
 In addition to branding messages, many studies have examined companies’ abilities to
drive user-engagement. While most of the existing research relies on quantitative data when
measuring engagement, further research is required to better understand not only how many
Likes, comments, and shares there are, but also understand the intrinsic value and tonality of
these comments.
 Additionally, research heavily focused on social media “content” versus the actual
message of the content (Voorveld, 2019, p.18). While several studies used experimental methods
and content analyses, the majority of research relied on survey methods. Consequently, the
existing themes and methodologies found within prior research guide the framework for the
present study.

3. Research Question and Hypotheses

 As stated earlier, the purpose of this thesis is to answer the question, “How do beauty
brands utilize consumer posts to convey branding messages?” To the best of my knowledge,
there are no existing studies which directly compare the content and messages between original
brand content and audience content which has tagged the brand in their posts. This is an
important question to answer because influencers and “regular consumers” create the posts
themselves (Stubb, Nyström and Colliander, 2019), leaving brands vulnerable to inconsistent
marketing messages. Based on what we know of brand advertising, product messages have
transitioned from transactional to informative (Ashley and Tuten, 2014; Shen and Bissell, 2013).
Brands create more product-centered content, while the consumer participates in brand visibility.

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Thus, when comparing the two message motives between brands and consumers on Instagram,
we can expect the first hypothesis as such:

 H1: Company-produced content will convey informative branding messages, while
 consumer-produced content will contain user-centered messages.

 A common goal of marketing campaigns is outreach and user-engagement (Ashley and
Tuten, 2014; Klassen et al., 2018; Neal, 2018; Shen and Bissell, 2013). This can be measured in
several ways, most commonly through quantitatively documenting the number of comments,
shares, and Likes received on each post.
 Voorveld et al. (2018) observed consumer engagement more thoroughly and discovered a
significant correlation between engagement and the selected social media platform. Their
research included a survey method using a dichotomy approach (e.g. questions asked the users
whether they did or did not experience a certain event). Users who frequented eight unique social
media platforms were surveyed, and the results confirmed that advertisements on each platform
were perceived differently depending on how the platform was typically used and how the
advertisements interfered with users’ experiences. These results are relevant for marketing and
communications research. Voorveld et al. (2018) concluded that platform-type was critical in
determining consumer behavior and that not all advertising messages were created equal.
Although Instagram was one of their observed platforms, the study was conducted in 2015, and
today’s results may be much different; thus, further investigation is necessary.
 Several studies have also identified successful strategies to increase consumer
engagement. In Ashley and Tuten’s (2014) content analysis, they discovered brands which
posted most frequently also had the highest number of followers on various social media
platforms. Likewise, content which encouraged consumer engagement, such as posing questions,
hosting competitions, or other calls-to-action, generated higher user-interactivity. Similar
findings appeared in another study which specifically reviewed company pages on Instagram.
Brands such as H&M were scored as having higher “online success” due to their high frequency
of posting, while Nike scored lowest (Loureiro, Serra and Guerreiro, 2019). Frequency was not
the only factor, as their analysis also revealed the content of H&M’s posts were more “passive”
in nature and meant as a means of entertainment. This is reflected in the following excerpt: “Use
and gratifications theory suggests social media participants are likely to desire entertainment and

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informativeness, but perhaps entertainment is a stronger motivator of engagement with top
brands than informativeness” (Luo, 2002, cited in Ashley and Tuten, 2014, p. 24).
 User engagement is often accepted as a high indicator of branding “success.” Therefore,
the present study shall consider aspects of engagement between brands and consumers through
the use of Instagram. The following hypothesis is stated as:

 H2: A positive correlation will exist between user-engagement and posts which directly
 encourage users to comment and Like through the inclusion of Calls-to-Action.

 A blurred line exists between “regular consumers” and social media influencers. This is
because “influencers” are, in fact, regular consumers who have achieved a large following and
subsequent sponsorships for their online posts. Nowadays, users in every corner of the Internet
are seeking ways to build an audience of their own because of the money-making potential.
Regular users are incorporating new strategies into their personal posts to expand their
reachability, such as creating “fake ads” (Grigsby, 2020) or tagging company pages which are
not necessarily included in the post itself (Rokka and Canniford, 2016). This suggests that users
are more focused on building their own online presence than on engaging with the brands
themselves. With this, the third set of hypotheses read:

 H3a: Consumers tag and mention multiple beauty brands to increase their own
 reachability.

 H3b: Consumers focus more on self-branding rather than the brands themselves.

 Many consumers are striving to reach “influencer” status. However, as mentioned in the
literature review, there is no exact threshold or qualifications to achieve the label of social media
influencer. As a result, these different labels between consumers, influencers, and audience are
somewhat interchangeable. For the purposes of the present study, the focus lies on company
branding messages versus non-company branding messages; therefore, “influencer” content will
be grouped into the more general labels of regular consumer and/or audience content.

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4. Methodology

 The following section provides the methodology used in the present study. This includes
both the logistical aspects, as well as the reasons behind choosing these methods. Further details
are provided about testing reliability and finally, ethical considerations.

4.1. Research through Content Analysis

 From the results of my literature review, I recognized an overwhelming amount of
research was derived from surveys or manipulated simulations of marketing advertisements.
While this data can be useful in understanding consumer behavior and attitudes towards brands,
other research methods have been neglected. Therefore, for the purposes of this report, I have
chosen to conduct a content analysis following the guidelines of Neuendorf (2002).
 There are several reasons why content analyses are a widely used research method in the
communications and media sphere. Content analyses take the form of a quantitative method
which closely resembles a scientific method approach (Neuendorf, 2002). Through intricate
planning, coding, and systematic protocol, the results should be objective and point to direct
causal relationships. This method, just as the scientific method, relies on “generalizability,”
meaning that randomness in samples can accurately represent a larger message set (Neuendorf,
2002, p. 12).
 A content analysis approach for this thesis is appropriate for answering questions
regarding company versus consumer posts on Instagram. By sampling and coding posts from
each group, we can observe patterns and compare differences both in qualitative and quantitative
data. The beauty industry has one of the largest presences on Instagram, so by performing a
content analysis on a smaller sample of posts, we can draw conclusions representative to the
beauty industry as a whole.
 Prior to conducting my own content analysis, I have generated an a priori design, as
recommended by Neuendorf (2002). This design ensures the research protocol is clearly laid out
ahead of time, including “all decisions on variables, their measurement, and coding rules” (ibid,
p.11). These criteria are presented in the following section.

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4.2. Criteria and Design

 The majority of Instagram users are female (Schouten, Janssen and Verspaget, 2019).
Consequently, Instagram has drawn in brands which cater to female audiences, especially in the
fashion, beauty, and lifestyle categories (ibid.). Therefore, this study will focus on beauty brands
and their communication practices on Instagram.
 Based on previous research designs (Ashley and Tuten, 2013; Loureiro, Serra and
Guerreiro, 2019; Neal, 2018; Shen and Bissell, 2013), I have chosen five beauty brands using
stratified random sampling. This sampling method allows for representation from different
groups, which ultimately translates to the beauty industry as a whole. The selected brands
represent a range of popularity and product affordability, and they all primarily sell makeup and
skincare products.
 The first brand I chose was Caia Cosmetics, which is a Swedish makeup brand. Because
of the high price point [e.g. Bibbz Signature Eye Palette with 12 shade options costs $65 USD
(Ögonskuggor, 2020)] , Caia is considered a luxury brand. Although the company has only
existed since 2018, it is quickly gaining international attention (cf. Englund, 2019). Caia was
founded by Swedish personality Bianca Ingrosso, who is a well-known celebrity and influencer
among the Swedish population. At the time of this study, the Caia Instagram page had around
120,000 followers.
 The second brand is E.L.F. Cosmetics--an American brand known for its cruelty-free
makeup and skincare products (Metrus, 2020). E.L.F. falls into the affordable to mid-range
category and is considered a drugstore brand. To give a price reference, their Rose Gold Eye
Shadow Palette contains 10 different shades and costs $26 USD. With a large international reach,
the brand has 5.6 million followers on Instagram as of August 2020.
 Next is Maybelline. As one of the oldest beauty brands to exist today, Maybelline has
consistently offered affordable makeup across the world. Founded in 1915 (Wischhover, 2015),
Maybelline has navigated through over a century of marketing strategies and consumer reach and
continues to be a powerhouse in the makeup industry. Their follower count is over 10 million.
Although Maybelline has used celebrity campaigns for many years, the company also endorses
SMIs on social media. As a price comparison, their 16-shades Nudes of New York Palette is
$13.99 USD, and their products are in the low-cost category.

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 The fourth brand selected was Huda Beauty. Similar to Caia Cosmetics, “Huda” (for
short) was founded by influencer and celebrity makeup artist Huda Kattan in 2013 (Sorvino,
2018). Huda has become one of the top makeup brands (ibid.) among other luxury cosmetic
companies. Their NUDE Obsessions Eye Shadow Palette costs $37 but has only nine shades
instead of 12 compared to Caia. Because Kattan is Iraqi-American, many of her followers are
middle eastern, and oftentimes Kattan’s content reflects her cultural background. There are two
different Instagram accounts related to Huda Beauty: one of them has the same name
(@hudabeauty) with a massive following of 47.6 million. However, this account is focused on
Kattan herself and not the company. Therefore, the account @hudabeautyshop was selected for
analysis. They have a following of 6.7 million and post similar beauty content as the other
selected brands.
 Lastly, Pixi by Petra was selected as the fifth brand for analysis. Out of the five brands,
Pixi is the only one to have built its company on skin care products first followed by the addition
of makeup products (Tan, 2018). The price range fits into low to mid-range, and their products
can be found in both drug stores and high-end cosmetic stores. For reference, the Eye Reflections
Shadow Palette has 12 shades and costs $24 USD. The brand has an international reach, and their
Instagram account has 1.6 million followers.
 The five brands give a strong representation of the beauty industry as a whole. The
brands cover a range of affordability (E.L.F. versus Huda), traditional and modern branding
(Maybelline versus Caia), and product range (E.L.F versus Pixi). They all have Instagram
accounts and have follower counts from 120,000 to over 10 million followers.
 As suggested by Neuendorf (2002), the findings from this diverse sample will be
applicable to the beauty industry as a whole. Brand posts were measured during two different
time periods: the first two weeks of July 2019 and the first two weeks of January 2020. These
timeframes were chosen because beauty and fashion trends typically reflect seasonal styles, so
having two opposing seasons offer more balanced insights for analysis.

4.3. Consumer Posts

 In addition to the five beauty brands, posts from consumers on Instagram were also
recorded and analyzed. 20 consumer posts were randomly selected from each brand during the

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month of July 2020. All tagged posts had an equal chance of selection. Any posts in a language
other than English or Swedish were not considered and therefore replaced. There were 20 posts
coded for each brand for a total of 100 consumer posts.

4.4. Codebooks and Coding Process

 To answer the hypotheses, there are several areas which will be observed. First, the
brands’ own Instagram accounts set the stage for branding expectations: which messages are
shared, how the products are shown, which emotional elements are present, how they encourage
engagement, and how their communication techniques are effective. Likewise, consumer content
will be coded following similar criteria but with additional elements tailored specifically to
general users, including the presence of additional brands and tags in their posts.
 Because the study design required two sets of data (beauty brands vs. consumer posts),
there were two similar but separate codebooks used, which can be viewed in full in Appendix 1.
Both codebooks were divided into two sections: content characteristics and branding messages.
The first section focused on the physical elements of the post, such as content type (i.e. photo,
video, other), product visible, and person/consumer visible. These categories were based on
Rokka and Canniford’s (2016) visual content analysis. By documenting the physical
characteristics of each post, we will be able to measure visual frequencies between each group.
This will be beneficial in answering the first and second hypotheses. Several categories related to
calls-to-action and promotional incentives were also included from Shen and Bissell’s (2013)
content analysis. The presence of CTAs on brand posts will assist in answering questions about
engagement for Hypothesis 2. One category unique to this paper was identifying whether or not
the content was originally produced by the company or taken and shared (referred to as a
“regram”) from another user. This category was coded exclusively on brand posts. Posts which
are user-made are essential in identifying which branding messages are selected and shared with
the brands’ millions of followers.
 The second half of the codebook was related to branding messages as used by Ashley and
Tuten (2014). This category identified informative, experiential, emotional, and user-centered
messages. Both data sets were coded for branding messages. In doing so, the results will provide
insight into Hypotheses 3a and 3b, which center around self-branding.

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 All coded elements used ratio data and were given numerical values during the coding
process. A sample of coded elements are presented below in Figure 4.4.1:

Figure 4.4.1
Codebook Sample: Beauty Brands - Physical Characteristics*

 Content type: 1=Photo 2=Video 3=Other

 Advertised product in photo: 1=Yes
 Product name is visible and/or product 2=No
 packaging is shown.

 Person/consumer present: 1=Influencer shown and identified
 Must show the face. Photos with only close- 2=Only unknown person or persons in advertisement
 ups, including hands, arms, lips, cheeks, etc. 3=No persons/consumers present
 are coded 3.

 Call-to-Action used: 1=Like** 2=Comment* 3=Tag 4=Share 5=Follow
 6=Visit (another account or external URL)
 7=Other/None

 *This includes verbiage such as “leave an emoji below” or
 asking users to “double-tap” the post. “Double-tap” is
 synonymous with “Like.” Any commands which have the
 intention to increase user engagement are categorized
 under this variable.
*Based on content analyses from Rokka and Canniford (2016) and Shen and Bissell (2013)

Codebook Sample: Branding Messages***

 Informative content about brand or product: 1=Yes
 Utility or functionality of the product/service, where to purchase products 2=No

 Emotional 1=Yes
 Psychological/social need--how it will make them feel, “your favorite 2=No
 product”

 Experiential 1=Yes
 Visually shows or explains how the consumer will experience sight, sound, 2=No
 taste, touch, smells. Includes makeup tutorials.

 User-centered 1=Yes
 2=No

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 The main focus is the SMI. If main focus is the brand/product, code 2.
 Examples: “you deserve it,” “you’re worth it.”

 Self-branding 1=Yes
 Does the user regularly post make-up photos? 2=No
*** Based on Ashley and Tuten (2014, p.21)

4.5. Pilot Study

 To ensure the codebook was sufficient for analysis, a smaller sample size was used as a
pilot study. Each post was coded for a total of ten posts, and then the results were submitted to
my advisor for review. Together we discussed the changes that should be made to the codebook
before applying it to the full data set. With the improved codebook in place, the full datasets
were ready to be coded for analysis.

4.6. Ethical Considerations

 There were several important ethical considerations while designing and implementing
the present study. As recommended by the American Sociological Association (ASA), their
Code of Ethics (1997) handbook provides an outline of expectations and practices when
conducting sociological research. In particular, the concept of confidentiality offers relevant
discourse regarding the data collected from Instagram:

 … [Sociologists] ensure the integrity of research and the open communication with
 research participants and to protect sensitive information obtained in research, teaching,
 practice, and service. When gathering confidential information, sociologists should take
 into account the long-term uses of the information, including its potential placement in
 public archives or the examination of the information by other researchers or
 practitioners. (ibid., p.11)

Although all of the data gathered was publicly available to anyone with an Instagram account,
any information which included “personal identifiers” was omitted herein. This was to ensure
privacy and anonymity for the individuals whose content was used or shared personally or by the
beauty brands. Brand-produced content did not need to be modified.

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5. Results

 In this section, the statistical data and results are presented. The discussion and
implications of these results will follow thereafter in Section 6.

5.1. Data Adjustments for Outliers

 After gathering all brand posts from the two time periods (July 2019 and January 2020),
there were a total of 314 posts. All data were scanned for errors and outliers using SPSS
Statistics software. After running a series of descriptive analyses to determine “normalcy,” two
outliers were identified and adjusted as recommended by Pallant (2016). One post from Huda
Beauty had 37,823 comments and one E.L.F post had 29,709 comments. Both of these were
replaced with the third highest count of 2,160. Further discussion of these outliers is found in
Section 6.2: Brands and Authenticity.

5.2. Original Brand Content vs. Shared Consumer Content

 All five brands shared (“regrammed”) images created by other users on their company
accounts. Out of 314 posts, 207 (65.9%) posts were original content created by the brand, and
107 (34.1%) were photos uploaded and created by other Instagram users. Looking more closely
at the five brands in particular, four of them (Caia, E.L.F., Maybelline, and Pixi) posted original
content more often than user-produced content. However, Huda Beauty only shared 13 (26.5%)
original images and was the only brand to use others’ images more often than their own. Figure
5.2.1 provides a visual representation of how many posts were original to the company. This
leaves us with two sub-categories for further analysis: original brand content (OBC) versus
shared consumer content (SCC). While all 314 posts came from the beauty brand accounts, 107
represent not only how consumers communicate branding messages, but which messages brands
choose to use for their own branding strategies.

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Figure 5.2.1

5.3. Post Elements

 Posts were coded for physical characteristics, such as media type (e.g. photo, video,
other), product visible, consumer/person visible, gender of consumer, and promotional elements.
When considering the two sub-categories, brand-produced images included an advertised
product in 156 (75.4%) posts out of 207. Consumer-produced content had a product visible in 70
(65.4%) images. Conversely, Figure 5.3.1 shows consumer-produced content had a
consumer/person visible in the photo 56.1% of the time compared to only 31.4% of brand-
produced images.
 A chi-square test for independence (with Yates’ Continuity Correction) was used because
of its ability to examine relationships between two categorical variables (Pallant, 2016). The test
revealed a significant relationship between user-produced content and consumers visible, ! (1,
n=314) = 16.907, p < .000, phi = -.24. The negative phi value represents a negative correlation
between variables. The results of a second chi-square test indicated there was no significant
association between company-produced content and product visibility, ! (1, n=314) = 2.98, p =
.084, phi = .11.

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Figure 5.3.1

5.4. Engagement

 Only a few quantitative values were publicly available for this study. One of those values
was the number of comments on each post. Because each beauty brand had a different number of
followers, the average number of comments were also different. A visual comparison of the
averages is available in Figure 5.4.1. As mentioned earlier, two outliers were adjusted. The
number of Likes were also recorded for each post, which is shown in Figure 5.4.2.
 Both of these quantifiable variables were used to help determine the level of engagement
between the brands and their followers. Two independent-samples t-tests were performed
because of their ability to process continuous variables across different groups. For the two tests,
the dependent variables were set to Number of Likes and Number of Comments, and the
grouping variable set to Brand-Produced Content. With equal variances not assumed for Number
of Likes, there was a significant difference found between brand-produced content (M = 23.02,
SD = 19.8) and consumer-produced content (M = 31.52, SD = 25.59; t (314) = -3.00, p = .003,
two-tailed). A Cohen’s d effect size statistic revealed a medium difference between means
(Cohen's d = (31.52 - 23.02) ⁄ 22.8789 = 0.372.) Conversely, there was no significant difference
with equal variances assumed for Number of Comments: brand-produced content (M = 246.29,

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SD = 357.01) and consumer-produced (M = 275.38, SD = 253.97; t (314) = -.750, p = .454, two-
tailed). Because both tests produced negative t-values, this indicates the means were lower for
consumer content (Gillespie, 2018).

Figure 5.4.1

Figure 5.4.2

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 One of the coding variables was “calls-to-action,” which included any verbiage asking
users to physically Like, comment, or engage with the post. Again, an independent-samples t-test
was used with the same continuous variables measured. A significant difference was found when
brands included a “comment” CTA (M = 339.15, SD = 370.88) versus posts without a CTA (M
= 217.45, SD = 294.91; t (314) = 2.883 [equal variances not assumed], p = .004, two-tailed). The
effect size was medium: Cohen's d = (217.45 - 339.15) ⁄ 335.055685 = 0.363. Because there were
only eight posts which were coded as having a CTA for “Like,” there was insufficient data to
perform a correlation or significance analysis.

5.5. Branding Messages

 On Instagram, users can tag people or companies in their posts. This is how beauty
brands find which audience-posts to share on their company accounts. Other users can also view
these posts by visiting the brand’s Instagram account and navigating to the “recently tagged”
icon. For this part of the analysis, 20 “consumer posts” from each brand were coded. This group
of data allows for direct comparison between brand posts, and more specifically, the photos
which brands chose to “regram” as their own.
 After running a frequencies analysis, some content elements proved to be drastically
different between consumer posts and brand posts. For example, advertised products were shown
22% of the time in consumer posts, while brands posted images of their products 72% of the
time. Conversely, a consumer/person was visible in 78% of consumer posts, while only 39.8% of
brand posts featured consumers.
 As for branding messages, brands were more likely to include informative content
(52.5%) compared to consumer posts (14%). Likewise, “product testimonials” were more
frequently included in brand posts (31.1%) than in consumer posts (13%). Content from
consumers were coded more frequently as emotional, experiential, and user-centered. A visual
representation of the branding messages can be seen in Figure 6.5.1:

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Figure 6.5.1
Branding messages: Brand posts versus Consumer posts

 Branding # of Brand Posts Brand Post # of Consumer Consumer Post
 Message (n=314) (Percentage) Posts (Percentage)
 (n=100)

 Informative 165 52.5% 14 14%

 Emotional 101 32.2% 43 43%

 Experiential 203 64.6% 75 75%

 User-Centered 203 64.6% 82 82%

 Social Cause 4 1.3% 1 1%

 Product Review 99 31.1% 13 13%

 Exclusivity 16 5.1% 5 5%

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Branding messages: Beauty brands original content versus shared consumer-produced

 Branding Brand- Brand Post Consumer- Consumer Post
 Message Produced Posts (Percentage) produced (Percentage)
 (n=207) (n=107)

 Informative 112 54.1% 53 52.5%

 Emotional 64 30.9% 37 34.6%

 Experiential 124 59.9% 79 64.6%

 User-Centered 115 55.6% 88 82.2%

 Social Cause 4 1.9% 0 0.0%

 Product Review 65 31.4% 34 31.8%

 Exclusivity 11 5.3% 5 4.7%

 As the tables above show, consumers typically include messages which are experiential
and user-centered more than any other message type. This was even more apparent when brands
chose to share consumer-produced content on their own accounts.
 A chi-square test for independence revealed a significant difference between branding
messages and whether the content was OBC or SCC. Experiential messages were significant, !

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(1, N = 314) = 5.39, p = .02. Likewise, user-centered messages were also significant, ! (1, N =
314) = 20.83, p < .000.

6. Discussion and Implications

 As we know, the content analysis included two sets of data: the first set being beauty
brand posts and the second set being consumer posts. After reviewing the beauty brand posts,
two apparent sub-groups were identified, as 107 of 314 posts were, in fact, consumer posts which
had been shared by the brand. For the purposes of this discussion, these sub-groups are identified
as “original brand content” (OBC, n=207) and “shared consumer content” (SCC, n=107). This
distinction is pertinent in the upcoming discussion when considering which posts brands
selectively integrate into their public Instagram accounts.

6.1. Branding Messages

 The primary focus of this study is to answer the question, “How do beauty brands utilize
consumer posts to convey branding messages?” With this in mind, the results revealed several
trends. Brands which borrowed or “regrammed” others’ posts most often chose images of
consumers using the products and/or showcasing different makeup looks. Meanwhile, original
brand content most frequently shared information about products, sales, or upcoming product
releases. Hypothesis 1 is therefore confirmed: Company-produced content will convey
informative branding messages, while consumer-produced content will contain user-centered
messages.
 This is in line with previous literature as companies have transitioned their branding
messages over time to reflect a more personable brand identity (cf. Ashley and Tuten, 2014;
Shen and Bissell, 2013). The online culture on social media has required companies to adapt
their approaches to communications strategies. As stated in Shen and Bissell’s article, “[brand’s
have shifted] their focus from products to people and from information delivery to information
exchange” (2013, p.646). The results of this study reveal that companies are approaching these
message types with the consumers as “spokespeople.”
 From a communications perspective, beauty brands are greatly benefiting from organic
Word-of-Mouth (eWOM) generated by other Instagram users. Moreover, consumers are most

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frequently sharing experiential content, which communicates ideas of brand functionality and
authenticity. Brands reap the benefits of “free marketing” through eWOM but still carefully
balance other branding messages which are more informative.

6.2. Engagement and Authenticity

 The perception of authenticity is pertinent when building an online presence. As
discussed in the literature review, authenticity is one of the most influential factors in brand
attitudes among consumers. The results from this content analysis revealed several interesting
tactics brands use to communicate authenticity which should be addressed.
 One of the few measuring methods available for engagement was the number of Likes
and comments received on each post. There are many reasons why the number of comments
inaccurately reflects user-engagement, but this will be discussed later in the Section 7.3:
Limitations with Engagement. As the analysis results showed, content which was created by the
brand itself received more Likes than posts that were “regrammed” or created by other users.
This is contradicting when considering the level of engagement from users who tag the brands.
For example, brands support their consumers by sharing consumer-produced content on their
own accounts, yet these consumer posts received fewer Likes (engagement) than organically
produced content. Beauty brands are therefore compensating for these lower-engagement posts
by uploading multiple times a day with an average mix of original content (65.9%) and consumer
content (34.1%).
 Furthermore, every brand post was coded for the inclusion of Calls-to-Action. Although
the codebook included a number of categories, such as asking followers to “tag” others, share the
post, or visit an external URL, the most common CTA was asking users to leave comments. The
posts would most often say something along the lines of “comment your favorite summer lipstick
shade” or ask users what their New Year's resolutions were. Some examples are shown in Figure
6.2.1.
 A significant correlation was found between posts which included a CTA and the number
of comments. This corresponds with previous research (Shen and Bissell, 2013), and also
confirms Hypothesis 2: A positive correlation will exist between user-engagement and posts
which directly encourage users to comment and Like through the inclusion of Calls-to-Action.

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 At first, this approach used by brands to increase engagement seemed effective in terms
of quantitative data. However, after looking more closely at the comments themselves, I
uncovered several misleading assumptions about the level of engagement.
 First, the number of comments shown represents the total number including both original
comments from followers and any replies from the brand or other users. In other words, if a post
shows as having 100 comments, this does not necessarily mean 100 different people left
comments or engaged with the post. After observing the different brands in this study, brands
such as E.L.F. and Pixi were highly responsive to other comments and would oftentimes leave
replies to further the engagement level with their followers. This means that posts which initially
show 100 comments, hypothetically, could only have 50 unique users engaged with the post and
the brand represented the other 50 comments. For the purposes of this research study, these
misrepresented numbers are problematic for analysis. However, for the millions of followers of
these brands, these numbers communicate different perceptions of community engagement and
how likely others are to engage with posts.

Figure 6.2.1

 Second, the inclusion of any CTA potentially generates manufactured engagement. When
brands add certain Calls-to-Action for followers to Like and comment on posts, then the
followers are contributing to the physical “numbers” but not necessarily engaging with the brand
itself or adding anything of intrinsic value. This was most apparent when coding and analyzing