Customer engagement on
Facebook: The Case of Dutch fast
fashion retail start-ups.
Stacey V.C. Plantijn
11017716
June 23, 2017
Master Thesis (Final)
MSc. Business Administration:
Entrepreneurship & Management in the Creative Industries
University of Amsterdam
Supervisor: Ieva Rozentale
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Statement of originality
This document is written by Stacey V.C. Plantijn who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Abstract
Social media as a marketing tool for businesses is becoming indispensable, as it is considered to be one of the best methods for companies to connect with current and potential customers. Most research studies focus on the use of social media as a marketing tool for already well established brands, leaving start-ups clueless on how to proceed when building their brand in order to bridge the gap between being new and becoming well known company. Social media as a marketing tool is important for start-ups considering the low cost related to this method and the financial difficulties start-ups face. Previous studies showed that customer engagement on social media has a positive effect on brand awareness and brand awareness is the first building block towards creating and establishing a brand. Therefore, this thesis focused on answering the question of “What are the motivations for customer engagement on
social media for branding in fast fashion retail start-ups?”. Results of this study indicated
that not all the motivation factors identified in a previous study had a significant effect on actual customer engagement for content posts on Facebook. This clearly shows that what was mentioned by customers in a previous study as the reasons behind their engagement with brands on social media is different from reality. A reason for this result might be that other factors underlie actual customer engagement on social media, indicating that further studies are necessary in order to help start-ups with guidelines on how to approach their social media marketing.
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Table of Contents
1. INTRODUCTION 5 2. LITERATURE REVIEW 82.2. FAST FASHION RETAIL 8
2.2 BRANDING IN THE START-UP CONTEXT 9 2.2.1 BRAND EQUITY BUILDING 10 2.2.2 CUSTOMER-BASED BRAND EQUITY 11 2.2.3 BRAND AWARENESS 11 2.3 CUSTOMER ENGAGEMENT 12 2.3.1. RELATIONSHIP BETWEEN BRAND AWARENESS AND CUSTOMER ENGAGEMENT 13 2.3.2 SOCIAL MEDIA PLATFORMS 14 2.3.3 IDENTIFYING CUSTOMER ENGAGEMENT ON FACEBOOK 14 2.4 MOTIVATION FACTORS FOR CUSTOMER ENGAGEMENT ON SOCIAL MEDIA 15 2.4.1. BRAND AFFILIATION 15 2.4.2. CONVERSATION 16 2.4.3 OPPORTUNITY SEEKING 16 2.4.4. ENTERTAINMENT 16 2.4.5. INVESTIGATION 17 3. METHODOLOGY 19 3.1 SAMPLE SELECTION 19 3.2 MEASURES 20 3.3 DEPENDENT VARIABLES 21 3.4 INDEPENDENT VARIABLES 22 3.5 DATA COLLECTION 24 3.6 DATA ANALYSIS 25 4. RESULTS 28 4.1 DESCRIPTIVE STATISTICS 28 4.2 MULTIPLE REGRESSION 29 5. DISCUSSION 32 5.1 RECOMMENDATION 34 6. CONCLUSION 36 REFERENCES 37 APPENDIX A: TABLES 41 APPENDIX B: COMPANY INFORMATION 45
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1. Introduction
Social media platforms such as Instagram, Twitter and Facebook, have become essential in many people’s everyday life to the extent that they might even seem to be indispensable. Kaplan and Haenlein (2010) defined social media as “a group of Internet-based applications
that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content” (p.61). The use of social media brought
with it a considerable amount of changes to the way organizations and individual communicate with each other (Luo, Wang & Hang, 2013). The essence of social media is thus not only applicable to individuals, but also businesses.
Social media is considered one of the best opportunities available for a brand in how it connects with current and potential customers. It allows a deeper connection which in turn results in earned trust (Neti, 2011). Social media is not only important for large international companies, but it is equally important for small and medium sized firms. According to Paniagua & Sapena (2014), social media platforms are a common place for networking, communication and contents sharing and through these platforms many companies try to find marketing and business opportunities. The importance of social media lies in the fact that it is a more direct and timely manner of communication and also in the fact that it involves lower cost, which results in a higher efficiency compared to traditional means of communication (Kaplan & Haenlein, 2010).
The use of social media by companies as part of their marketing strategies is called social media marketing. Currently the majority of research studies on social media marketing focuses on the effects of consumer engagement through social media. Hutter et al. (2013) concluded that engagement with a brand on social leads to positive effects on brand awareness, word of mouth activities, as well as purchase intention. Kim & Ko (2010) found
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that the social media marketing of luxury brands is a significantly effective marketing medium and that it had a positive influence on customer relationship and purchase intention as well.
With most research studies also focusing on the use of social media as an additional marketing tool for already well established brands and companies, little to no light is shed on the use or possibility of social media as the main or sole marketing tool and how to actually get customers to engage on social media. Wolny & Mueller (2013) also pointed to the lack of studies focused on understanding what motivates customers to engage with brands on social media. It is important to study this motivation phenomenon especially in the context of start-ups. Considering the amount of risks and competition, starting a new business can be difficult. According to Witt & Rode (2005) most start-ups encounter problems in the early stages of development when trying to bridge the gap between being a new business and becoming well known in their respective market. In order to bridge this gap, branding should be a priority for start-ups. One of the main problems start-ups faces in their early stages, that lowers their branding efforts, is a limited budget (Abimbola & Vallaster, 2007; Berthon, Ewing & Napoli, 2008). The lack of financial resources of start-ups combined with the low cost and high efficiency of social media marketing, makes social media an ideal marketing tool for start-ups.
It is already known from previous studies that customer engagement has a positive effect on brand awareness, customer relationship and purchase intention; which are important for the success of every business, but even more important in the case of start-ups. What becomes even more important now is, what leads to customer engagement related to brand awareness and relationship (interaction). Therefore, this study is going to focus on the motivations behind customer engagement on social media in the case of fast fashion retail start-ups. The research question developed was the following:
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What are the motivations behind customer engagement on social media for branding in fast fashion retail start-ups?
For the purpose of this study an empirical study, in the form of content analysis will be conducted to answer our main research question. The fast fashion retail setting has been chosen as the research context, because most studies related to the use of social media marketing were done with well-established luxury fashion brands (Kim & Ko, 2010; Kim & Ko, 2012; Ng, 2014; Phan, Thomas & Heine, 2011). But the aim of this study is to research the other end of the spectrum which are fast fashion retail startups. Additional reasons for choosing the fast fashion retail segment as the setting for this study are (1) because it is important to know customers’ characteristics and motivations to develop effective marketing strategies and (2) the fast fashion segment is growing and will affect the fashion industry as a whole and. This forecasted growth of the fast fashion segment point to a possibility of new firms jumping on the opportunity of starting a new business in this specific market
This thesis is structured as follows; first the literature review will explain the main concept and previous studies and findings related to them, second is the methodology which gives in details how this study was conducted, followed by the results chapter and to finalize, the discussion and conclusion chapters.
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2. Literature Review
In this section the concepts of fast fashion retail, startups, branding and consumer engagement and motivation factors for customer engagement are presented, what has been studied and their findings individually and then how they relate to each other for this study. 2.2. Fast Fashion Retail
The luxury segment of the fashion industry has long been held on a pedestal. This can be seen on the amount of studies done related to luxury fashion brands (Kim & Ko, 2010; Kim & Ko, 2012; Ng, 2014; Phan, Thomas & Heine, 2011). But the opposite of the luxury segment which is the mass segment, also called fast fashion, should be important as well in studies related to consumer behavior, more specifically consumer engagement on social media in this case.
The latest fashion creations from runway shows that were considered exclusive in the past are now available in other segments of the market in weeks (Masson et al. 2007). This phenomenon is called “fast fashion”. Joy et al. (2012) explained that fast fashion is imitating current luxury trends with lower cost clothing. Fast fashion is gaining a considerable amount of “importance” because the consumers market is “fragmented” related to consumption patterns. As consumers are becoming more savvy and demanding when it comes to fashion, this is “forcing” fashion retailers to “provide” the right product at the right time and quickly (Bhardwaj & Fairhurst, 2010). In an industry that is changing at such a rapid pace, fast fashion is one of the most effective strategy to compete with in the fast changing fashion world (Choi et al. 2010).
As already mentioned briefly in the introduction the importance of further studies related to the fast fashion segment and consumers’ behavior towards it is two-fold. First because fast fashion will keep affecting the fashion apparel industry and will have an effect on how people purchase and react to trends. And second because it is important to have
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knowledge of the customers’ characteristics and motivation so retailers can be more effective in developing marketing strategies to safeguard their performance in the market (Bhardwaj & Fairhurst, 2010).
2.2 Branding in the start-up context
Branding is seen as the process that links the image and the identity of a brand with each other. Identity is perceived as the company’s internal part of the brand whereas image relates to the identity projection to the external stakeholders (Witt & Rode, 2005). The importance of having a brand is because it is an efficient way to communicate with, not only customers, but also other stakeholders (Rao, Agarwal, & Dahlhoff; 2004). By creating a distinctive brand image containing attributes of the product including brand personality, name, design and values, an entrepreneur is able to build a strong brand (Boyle, 2003).
In order for a business to be considered a startup, it must meet three criteria. These three criteria are “new”, “active” and “independent” (Luger & Koo, 2005). New refers to newly created firms excluding the ones that were created by a change in name, ownership, location or legal status. Active emphasizes that a firm should not only be new but also
engaged in the trading of goods and services. The active criterion is important considering the presence of high amounts of “paper” firms. Independent refers to the firms standing on its own as opposed to be a branch or a subsidiary from another firm. Putting these three criteria together, Luger & Koo (2005) defined a startup as:
“a business entity which did not exist before during a given time period (new), which starts hiring at least one paid employee during the given time period (active), and which is neither a subsidiary nor a branch of an existing firm (independent)”
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Creating a brand and implementing branding strategies is often seen as a complex task in start-ups. Not only do they have a limited amount of resources, but a lack of reputation and customer base as well (Boyle, 2003). This leads to the tendency of start-ups to give little consideration to the benefits of having a brand or the criteria that must be met to create a “strong” brand (Krake, 2005). Before implementing branding strategies, a strong brand should be built in order to reduces risks and activate engagement between customers and the brand (Abimbola & Vallaster, 2007). This is also known as brand equity building.
2.2.1 Brand equity building
One the most important aspects in order to get your name and products on the market when starting a business is building the brand equity. Brand equity is defined as “the marketing
effects or outcomes that accrue to a product with its brand name compared with those that would accrue if the same product did not have that brand name” (Torres & Tribo, 2011,
p.1089). If brand equity building is done right, it can bring a lot of benefits. Some of these benefits are customer loyalty, larger margins, favorable response of customers to price changes and higher marketing communication effectiveness (Keller, 2001).
Brand equity can be studied from two perspectives. The first one is the financial perspective and the second one is the customer perspective, also called customer-based brand equity (Lassar, Mittal & Sharma, 1995). The financial perspective of brand equity refers to the financial asset value that the brand creates to the business. This financial perspective measures the outcome of the customer-based brand equity. Since the focus of this study is on customer engagement and start-ups, the customer-based brand equity perspective will be discussed further.
11 2.2.2 Customer-based brand equity
According to Blumrodt, Bryson & Flanagan (2012), customer based brand equity is the result of the effect of brand knowledge on consumer response to the brand’s marketing. Keller (1993) gives the following definition for customer based brand equity:
“the differential effect of brand knowledge on consumer response to the marketing of the brand. That is, customer-based brand equity involves consumers' reactions to an element of the marketing mix for the brand in comparison with their reactions to the same marketing mix element attributed to a fictitiously named or unnamed version of the product or service. Customer-based brand equity occurs when the consumer is familiar with the brand and holds some favorable, strong, and unique brand associations in memory” (p.2). Brand knowledge
consists of two components - brand awareness and brand image.
According to Keller (2001) there are four (4) steps to be followed in order to build strong brand when using the customer-based brand equity model. These four steps are (1) forming the right brand identity, (2) developing the right brand meaning, (3) evoke the desired brand responses and (4) produce the desired brand relationships with customers. Just like the first component of brand knowledge is brand awareness, none of these steps can be completed without creating brand awareness. Therefore, brand awareness is the first step towards building brand equity (Huang & Sarigollu, 2012).
Because brand awareness needs to be created before continuing with the other stages and considering the purpose of this study in relation to start-ups, only the creation of brand awareness as part of equity building is considered for this study.
2.2.3 Brand awareness
The foundation for building customer-based brand equity, starts with brand awareness (Huang & Sarigollu, 2012). The importance of brand awareness lies in the fact that it is key
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in the customer’s decision making process when considering the purchase of an item (Keller, 1993; Macdonald & Sharp, 2000). According to Keller & Lehmann (2003) brand awareness can be defined as the degree to which a customer is able to recognize and recall a brand and identify the products and services related with the brand. The two main components of brand awareness are thus brand recognition and brand recall. Huang & Sarigollu (2012) explain brand recall as the consumer’s ability to recall a brand during decision making process before purchase without the supply of relevant information. Brand recognition indicates the consumer’s ability to recognize a brand prior to making a purchase.
In order to create brand awareness, customer engagement is necessary. Because customer engagement is what leads to brand awareness. Therefore, start-ups should have knowledge of the motivations leading to customer engagement. In this case, motivations for customer engagement with regards to social media. In the next section, the concept of customer engagement is explained in more details.
2.3 Customer engagement
Customer engagement, sometimes also referred to as consumer engagement, is defined as “the intensity of an individual’s participation in and connection with an organization’s
offerings and/or organizational activities, which either the customer or the organization initiate” (Vivek, Beatty & Morgan, 2012, p.127). The goals driving the pursuit of customer
engagement are not always related to sales. Some of these goals can be creating brand awareness or establishing communities (Vinerean, Opreana & Tichindelean, 2014). According to Sashi (2012), social media and its interactivity makes it easier to establish long lasting relationships between buyers and sellers. Long lasting relationships between customers and a brands are important for the customer-based brand equity aspect of the branding cycle.
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It is clear now, that the concepts of brand awareness and customer engagement do not stand on their own. In the next section, the relationship between these concepts is illustrated.
2.3.1. Relationship between brand awareness and customer engagement
From the previous sections, the main pattern recognized is that in order to create brand awareness customers need to be engaged first. Thus acquiring customer engagement is a precedent in the creation of brand awareness. But before a customer is engaged, some kind of motivation/incentive is needed. This process is illustrated in Figure 1.
Figure 1. The three key concepts
What figure 1 illustrates is a summary of the concepts already mentioned and how they relate to each other. Before actually engaging with a brand, the customers need to have some kind of motivation. This motivation will eventually lead to actual engagement with the brand, which will lead to the creation and/or growth of brand awareness. It is important to know how these concepts relate to each other, but it is also important to know how to identify customer engagement on social media and what factors influences motivation. Since each social media platform is different, first a platform for this study needed to be chosen in order to determine how customer engagement is measured and analyzed for that specific social media platform.
Motivation EngagementCustomer Customer-Based Brand Equity (brand awarness)
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2.3.2 Social Media platforms
Instagram, Twitter and Facebook are all known social media platforms, but conducting this study on each platform simultaneously seemed unfeasible. The assumption was made that the largest social media platform would yield the best results. According to Hughes et al. (2012) Facebook is the largest social media platform, therefore Facebook was chosen for this study. In the next section, how to identify customer engagement on Facebook will be explained
2.3.3 Identifying customer engagement on Facebook
In addition to knowing what customer engagement is and what motivates it, it is equally important to know how to measure it. Sabate et al. (2014) identified three overall ways customers can interact with a brand’s social media marketing messages in the case of Facebook. First is by liking a post, second by commenting on a post and lastly by actually sharing the post. Dhaoui (2014) took these forms of interaction a little further and developed four different constructs for each. The first construct is endorsement. The endorsements of a content on Facebook relates to users “liking” the content published on the brand’s page. By doing this, they illustrate their approval of the content. The second construct is feedback. Feedback refers to users commenting on a published content on the Facebook page of a brand. By doing so they are not only providing the brand with feedback, but are also sharing it with other community members. The third construct in this case is “conversation”. This refers to either conversation with or among Facebook users. Conversation can be seen when users reply to a comment, this in turn will create an engaging conversation and the comment itself turns into a source of engagement. Finally, we have the fourth construct which is recommendation. Recommendation entails the sharing of marketing content with friends on Facebook. Thus how many shares a content receives, measures the recommendation aspect. How to actually measure these four constructs will be further explained in the
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“Methodology” chapter. In the following section the factors behind motivation for customer engagement on social media will be examined and hypothesis developed.
2.4 Motivation factors for customer engagement on social media
According to Enginkaya & Yilmaz (2014) in order for marketers to develop better strategies it is important to understand what motivates customers to interact with brands and/or other customers on social media. But it is also important to know how customer engagement works. As noted by Sashi (2012) customer engagement on social media starts with connection and is followed by interaction.
Enginkaya & Yilmaz (2014) developed a scale of five (5) different motivation aspects that can lead to customer engagement, they are (1) brand affiliation, (2) conversation, (3) opportunity seeking, (4) entertainment and (5) investigation. Each of these factors was found to be important to drive customers’ motivation to engage with brands on social media. In the following sub-sections each motivation are be explained and hypothesis are developed for each factors in relation to their possible effect on customer engagement.
2.4.1. Brand Affiliation
Brand affiliation represents customers’ motivation to engage with a brand on social media based on lifestyle compatibility, possession desires, preferences and promotion intention. According to Enginkaya & Yilmaz (2014), brand affiliation ranked as number 4 when it came to the five motivations for customers to engage with brand on social medial. Customers are more likely to engage with brands that are congruent with their lifestyles or brands that they contemplate to buy in the future, but cannot afford at the moment. Additionally, they also engage with brands they consume and/or purchase often and finally they also indicated that
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their engagement with a brand on social media is due that their satisfaction or dissatisfaction will influence their friends. Based on this, the following hypothesis is developed:
H1: Brand Affiliation has a positive effect on customer engagement 2.4.2. Conversation
Conversation reflects the role of social media on customers’ need to communicate with the brand and other customers. Conversation turned out to be the second most important reason that customers engage with brands on social media (Enginkaya & Yilmaz, 2014). Customers find it convenient to address their complaints and suggestions to brands on social media. The ability to communicate immediately without the hurdle of space and time. Finally getting in contact with brands is easier through social media. Therefore, the following hypothesis is made:
H2: Conversation has positive effect on customer engagement 2.4.3 Opportunity Seeking
Opportunity seeking reflects that in order for customers to follow a brand on social media, it must be perceived as beneficial to them (Enginkaya & Yilmaz, 2014). Considering the relative new or unknown nature of start-ups, benefits might not be important for motivation. Opportunity seeking was the highest motivation driver when it comes to engagement on social media. Customers are more likely to engage if the promotions and discount campaigns proposed by the brand has financial benefits for them. By following a brand on social media they are able to stay informed on discounts and promotions without having to visit a physical store. Finally, by following brands on social media they are also able to stay informed about new offerings. Therefore, the next hypothesis was developed:
H3: Opportunity Seeking has a positive effect on customer engagement. 2.4.4. Entertainment
Entertainment represents when a customer’s motivation is based on them finding the content on the brand’s social media to be amusing and fun. Entertainment ranked number five, meaning that it was the least important motivator among the other ones (Enginkaya &
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Yilmaz, 2014). Customers indicated to liking influential and creative contents on a brand’s page. These type of contents also provides them with an opportunity to have fun on social media. Finally, customers also stated that entertaining content posted by a brand has a positive influence on their attitudes towards the company’s image. But despite these positive observations, entertainment doesn’t seem to be as important as the other factors. Based on this, the following hypothesis was developed:
H4: Entertainment has no effect on customer engagement 2.4.5. Investigation
Investigation reflects the role of social media on customers’ pursuit for trustworthy information of the brand and the products it offers. According to Enginkaya & Yilmaz (2014), investigation was the 3rd most important factor behind motivation. One reason for this was that customers believe that the information related to the product that they can collect on social media is relatively reliable. The second reason for this is that social media is considered a reliable information source because it is able to create a transparent integration between brands and customers. Therefore, the following hypothesis was developed:
H5: Investigation has a positive effect on customer engagement.
A summary of all the 5 motivation factors can be found in Table 1 in appendix and the conceptual model is illustrated next in Figure 2.
18 Figure 2. The conceptual model Brand Affiliation Conversation Opportunity
Seeking EngagementCustomer
Endorsement Feedback Conversation Recommendation Entertainment Investigation
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3. Methodology
The purpose of this study was to analyze actual behavior related to customer engagement and the motivation factors that underlies this engagement. Following the research method used by Dhaoui (2014), for this study a quantitative content analysis was conducted of a sample of Facebook brand pages of Dutch fast fashion retail startups. Content analysis is defined as “an
approach to the analysis of documents and texts that seeks to quantify content in terms of predetermined categories and in a systematic and replicable manner” (Bryman & Bell, 2007,
p. 304).
Based on a series of interviews conducted with customer based on their engagement with brands on social media Enginkaya & Yilmaz (2014) managed to identify five motivation factors that, according to them, were able to explain engagement on social media. These five motivation factors as mentioned previously already are brand affiliation, conversation, opportunity seeking, entertainment and investigation.
The present research study took the previous study a step further by analyzing if the motivation factors are in line with actual behavior related to customer engagement. The content analysis approach was used to analyze the characteristics of the social media marketing messages, or “posts” as called on Facebook. The analysis of the characteristics of the social media marketing messages was a two-fold approach, first the motivation factor related to the message was identified and then the customer engagement was measured.
3.1 Sample selection
Since this study had a focus on companies with specific characteristics, but the population was unknown we opted for “non-probability sampling”. Saunder & Lewis (2012) defines non-probability sampling as “a variety of sampling techniques for selecting a sample when
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the population, you cannot select your sample from this population at random” (p. 134). The
first characteristic required to be considered for the sample was to be a fast fashion retailer, the opposite of a luxury fashion retailer. The second characteristic was to be a startup. In order to be considered a start up in this sample the companies must not be older than 5 years (established in 2012 and up). Finally, the companies must be Dutch. The reason for this last criteria was to make the study local and also considering that the European retail market is one of the largest retail markets in the world (Masson et al. 2007). Although “having a Facebook page” should have been a criterion, it was excluded since the search for this sample is done on Facebook and companies without a Facebook page will automatically not be found. The sample size for this study was set to 10, mimicking the same sample size of the research done by Dhaoui (2014). Before starting the sample selection, there was prior knowledge of one company that met these criteria. This company was “Most Wanted”. In order to find additional companies to complete the sample the following steps were followed. First the Facebook page of this company was “liked”. After this action, Facebook instantly presents a small list of other pages that are similar to the one that was originally liked. The majority of the pages presented were also fashion retailers. For each of the pages suggested more information was searched for in order to see if they met the list of criteria. Each company page that met the criteria was liked to find more suggestions in order to find more companies. These actions were repeated until the sample size of 10 was reached.
3.2 Measures
As mentioned previously, actual engagement on Facebook can be in the form of liking a post, comment on a post or sharing the post (Sabate et al. 2014). But as described by Dhaoui (2014) there are four specific constructs which are endorsement, feedback, conversation and
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recommendation. Based on these four construct the following measurements and their corresponding notations will be taken into consideration for the purpose of this study:
• Fb, refers to the amount of Facebook users who like the Facebook page of the brand • Pb is the amount of post published by the brand’s Facebook page throughout a period • plikes refers to the number of users who likes a contents published by the brand on its
Facebook page
• pshares in this case is the total amount of times a published content was shared by the Facebook users
• CPp refers to amounts of comments that a post receives
• RCc refers to the amount of community replies to comment on a post. • BRCc refers to amount of comments the brand itself made on a comment.
• Clikes are the amount of likes a comment on a post by the brand gets by the users • rlikes refers to the number of users on Facebook who like a reply to comment on a
post.
As explained by Dhaoui (2014) these measurements represents the rich data available to collect on the Facebook page of any brand.
3.3 Dependent Variables
Dependent variables are considered the behavior that is being studied because of the assumption that it is the cause of some other variable (Chadwick et al. 1984). The 9 metrics mentioned in the previous section are used to calculate customer engagement related to the constructs endorsement, feedback, conversation and recommendation. In this case, customer’s engagement rates will be calculated to enable comparison between brands whose Facebook brand communities differs in size (Dhaoui, 2014). These four
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customer engagement rates are also the dependent variables for this study. For the purpose of this study the customer engagement rates are calculated as follows:
• Endorsement rate. The endorsement rate is calculated by dividing the total number of likes for a post on the brand’s page by the size of the community:
• Feedback rate: The feedback rate is calculated by dividing the total number of comments and replies to comments for a post on the brand’s page by the size of the community:
• Conversation rate. The conversation rate is calculated by dividing the total number of replies to comments on a post of a brand’s page by the size of the community:
• Recommendation rate. The recommendation rate is calculated by dividing the total number of shares for a post on the brand’s page by the size of the community:
3.4 Independent Variables
Independent variables are defined as “those factors that explain or predict the dependent
variable” (Chadwick et al. 1984, p.44). For the purpose of this study the independent
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motivation factors identified by Enginkaya & Yilmaz (2014). Although these motivation factors are the results of an interview-based study they will be translated to content measures by following the approach by Dhaoui (2014). For each post analyzed a motivation factor was identified and assigned to this post, hereby grouping all posts collected into a five-scale category. As mentioned before the five motivation factors are (1) brand affiliation, (2) conversation, (3) opportunity seeking, (4) entertainment and (5) entertainment. In the literature review all these five motivation factors have been defined and based on these definitions the content of each post was categorized. In order to identify in which category a post belongs, the “items” section in Table 1 was consulted. Based on the different statements given related to the motivation factor and the definitions already mentioned in the literature review, the content of each post gathered was analyzed and a category is given. For example, if the content of a post entails a sale that is currently going on, it checks 2 of the 3 items related to “opportunity seeking” and it is in line with the definition as well, thus this post was coded as “opportunity seeking”. This process was repeated again with every post gathered.
Since this study was done for the first time, the possibility of one post belonging to multiple categories is not considered for this study. Each post is assigned only one category which is the one most similar to the content of the post. Considering the newness of this study, reliability regarding the coding of the content of each post is an important aspect as well. Reliability is defined by Zikmund (2003) as “the degree to which measures are free
from error and therefore yield consistent results” (p. 300). To establish reliability with the
coding of the posts’ content, a second person was approach to test the reliability. The results of the reliability test are presented at the end of the “Data Collection” chapter.
24 3.5 Data Collection
For the data collection of this study, Facepager was used to collect data related to public interaction on the Facebook page of the 10 companies belonging to the sample. Facepager is a software that lets you collect the same data as the Graph API tool, but is more user friendly since it involves less coding. From the 10 companies, the data collected covers a 2-month period of interaction dating from March 1st to April 30th 2017. Facepager granted access to most aspects of public posts on Facebook, this included their comments, likes and shares just like Graph API. (Dhaoui, 2014).
Unfortunately, not all the data needed in order to calculate the dependent variables for this study could be collected. Due to privacy policies from Graph API, it was not possible to collect information on the amount of replies to comments for each post. Without this data it was not possible to calculate the conversation rate. The decision was made to keep feedback rate and calculate this with only the number of comments, therefore giving us only a partial feedback rate for the posts that might have actually had replies to comments. Conversation rate was excluded completely. The following data was collected from each page of the 10 companies: (1) Page likes, (2) posts from March 1st to April 30th 2017, the numbers of (3) likes, (4) comments and (5) shares for each post.
The 10 companies used in this sample were: Tequila Fashion, Reinders, Malifisent, Yaella Fashion, ModeJunkies, Lofty Manner, Most Wanted, Dinmar Fashion Store, Elise Store and Mode Straatje. All the information that could be found on these companies are reported back in Appendix B.
Before analyzing the data collected, some variables were recoded and some were added. The first variable to be recoded was the post contents. As explained in the “Independent Variables” chapter, each post was given a motivator factor based on the content
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of the post. This was done with a scale from 1 to 5; 1 was Brand Affiliation, 2 was Conversation, 3 was Opportunity Seeking, 4 was Entertainment and 5 was Investigation. Since this study was done for the first time it was important to test the reliability of how the content posts were coded. The reliability index used to calculate the reliability of the coding was P0. As explained by Scott (1955) this reliability index is simple the percentage of cases
on which coders agree, out of the total amount of cases. For this purpose, a second coder was given a list of 25 content posts to code. These posts have already been coded by the main researcher, but the second coder was not aware of the results. After comparing the results of the main researcher and the second coder, 23 out of the 25 content posts were coded the same. This resulted in a P0 of 92%, making the coding of this study reliable.
Next, the dependent variables were calculated as explained in the “Dependent
Variables” chapter. This calculation generated 3 additional variables, which were labeled
Endorsement, Feedback and Recommendation. In addition to this, an overall “customer engagement” rate was also added which was done by calculated the mean of the already calculated endorsement, feedback and recommendation rates.
3.6 Data Analysis
Analysis of the collected data was twofold. First descriptive statistics were collected and in the second part the hypotheses were tested. Statistical Package for the Social Science (SPSS) was used for both the descriptive statistics and the statistical analysis regarding hypothesis testing.
Descriptive statistics were used to develop a general overview of the data collected. This general overview consisted of the amount of posts, the total number of likes, shares and comments. Also what type of post were collected and how the posts were categorized related
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to the motivation factors. The lowest and highest number of likes, shares and comments the posts received. The result of each one of these variables is reported in the Results chapter.
As for the statistical analysis in order to test the 5 hypotheses that were developed, a multiple regression analysis was conducted to see if each of the five motivation factors had an effect on customer engagement. Multiple regression analysis is defined by Zikmund (2003) as “an analysis of association in which the effects of two or more independent
variables on a single interval-scaled or ratio-scaled dependent variable are investigated simultaneously” (p. 576). In order to conduct the multiple regression analysis, the 5 scale
categorical variable “motivation factor” was converted in order to get two or more independent variables. This was done by creating 5 new variables labeled “Brand Affiliation”, “Conversation”, “Opportunity Seeking”, “Entertainment” and “Investigation”. Each on of these variables were coded with a 0 (No) if the post being analyzed was not categorized as that motivation factor and with a 1 (Yes) if the post was categorized as that motivation factor. Thus if a post was categorized as “Opportunity Seeking”, for this case opportunity seeking was assigned a 1 (for “Yes”) and the other 4 variables received a 0 (for “No”)
After the first multiple regression test was done the variable “Opportunity Seeking” was excluded from the multiple regression because of the value of its collinearity (table 9, Appendix A). The correlation table shows that the highest correlations are between (1) Opportunity seeking and Investigation .654), and (2) Entertainment and Investigation (-.633). Although a correlation below .7 is considered to be out of the danger zone (Zikmund, 2003), these two correlations were taken as danger zone as they might be the reason for the exclusion of “opportunity seeking” previously mentioned. For an overview of all correlations, table 6 in Appendix A can be consulted.
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In order to be able to test the third hypothesis related to opportunity seeking, the choice was made to not run the regression analysis with all three variables (considering their correlations) in order to find the p-value for opportunity seeking. Therefore, to test this hypothesis, only 2 independent variables were inserted at the time. The first test was done with “opportunity seeking” and “conversation” as the independent variables. The second test was done with “opportunity seeking” and “entertainment”. Finally, the third test was done with opportunity seeking and investigation as the independent variables. Each test resulted in a Sig. value lower than .05, therefore only one result and table was chosen to be included in the results chapter and the rest can be found in Appendix A. The results of each test mentioned in this chapter is presented next in the Results chapter.
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4. Results
This chapter gives and overview of the results of both the descriptive statistics of the data collected and the results of the statistical analysis conducted to test the hypotheses. If not included with the text, the tables that are mentioned can be found in Appendix A.
4.1 Descriptive Statistics
A total of 840 posts were gathered from the Facebook page of 10 dutch fast fashion retailers. From these 840 posts, 98.2% were pictures, 0.8% were videos and 0.6% were links, 0.1% was status update and 0.2% was an event (Table 2). These post accumulated a total of 110571 likes, 12771 comments and 1760 shares (Table 3). A total of 11 post received The lowest number of likes, which is 0 accounting for 1.3% of the total posts and the highest amount of likes a single post received was 5053, which accounts for 0.1% of the total amount of posts.
As for comments, a total of 497 post received 0 comments which accounts for 59.2% of the total and highest amount of comments received was 1604 by one post which accounts for 0.1% of the total amount of posts. A total of 481, 57.3%, of the posts received the lowest number of shares possible which is 0 and the highest number of shares registered was 127 shares which was for only 1 post and it accounted for 0.1% of the total amount of posts.
As for the assigned motivation factors, 77.9% (654) of the posts turned out to be related to investigation, 10.2% (86) was related to entertainment, 10.8% (91) was related to opportunity seeking and only 1.1% (9) was related to conversation (Table 4). None of the posts gathered and analyzed were related to brand affiliation. Another important aspect to report is the amount of page likes each company’s Facebook page had. The number of page likes each company had was the following:
o Tequila Fashion: 26.779 page likes o Reinders: 19.646 page likes
29 o Yaella Fashion 5198 likes o Mode Junkies: 25.847 likes o Lofty Manner: 28.464 likes o Most Wanted: 170.000 likes o Dinmar Fashion Store: 2804 likes o Elise Store: 88.171 likes
o Mode Straatje: 11.827 likes This information is also summarized in table 5.
4.2 Multiple Regression
The total dataset of 840 posts (N=840) has been used in order to conduct a multiple regression analysis where the dependent variable is customer engagement, while the independent variables were the five motivation factors (brand affiliation, conversation, opportunity seeking, entertainment and investigation). A non-significant regression equation was found (F(3, 836)= 1.654 , p .175) with an R2 of .006. These values are presented in Table 1 and Table 2 below.
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In the descriptive statistics chapter, was mentioned that none of the content posts that were gathered and analyzed could be categorized as brand affiliation. Therefore, the multiple regression analysis was conducted once more without brand affiliation as an independent variable. The results were the same as the one mentioned previously. Thus even without brand affiliation in the equation, a non-significant regression equation was found with the same values. Both tests yielded the same result because SPSS automatically removed “Brand Affiliation” as a variable due to missing correlations (Table 6, Appendix A). Based on this, H1 was discarded and only 4 hypothesis remained to be analyzed. Next Hypothesis 2, Hypothesis 3, Hypothesis 4 and Hypothesis 5 were tested.
Hypothesis 2 stated the following: “Conversation has a positive effect on customer
engagement”. With a Sig. value of .173, at the .05 level of significance, we conclude that
conversation has no significant effect on customer engagement. Therefore, H2 is rejected. Hypothesis 3 stated that: “Opportunity seeking has a positive effect on customer
engagement”. With a Sig. value of .049, at the .05 level of significance, we conclude that
opportunity seeking has a significant effect on customer engagement. Therefore, H3 is accepted. The results are presented below. Additional results of this analysis using different independent variables can be found in table 7 and table 8 in Appendix A.
Table 2. ANOVA
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Hypothesis 4 stated the following: “Entertainment has no effect on customer
engagement”. With a Sig. value of .071, at the .05 level of significance, we conclude that
entertainment has no significant effect on customer engagement. Therefore, H4 is accepted. The final hypothesis, H5, was, “Investigation has a positive effect on customer
engagement”. With a Sig. value of .053, at the .05 level of significance, we conclude that
investigation has no significant effect on customer engagement. Therefore, H5 is rejected. The results for H2, H4 and H5 are presented in Table 4 below
Table 3. Multiple Reggresion "opportunity seeking" Table 4. Multiple Regression excluding "opportunity seeking"
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5. Discussion
Results showed that the motivation factor “conversation” had no significant effect on customer engagement. This is a big contrast compared to the study by Enginkaya & Yilmaz (2014), where conversation turned out to be the second most important reason given by customers on why they engage with brands on social media. One explanation for this difference in results could be what was measured. In this study the unit of analysis was posts on Facebook and customer engagement related to these posts. The study by Enginkaya & Yilmaz (2014) was more of an overall assessment on the motivations behind why customers engage with brands on social media. Thus, the answer was not limited to only posts.
As for “opportunity seeking” the results showed that it has a significant effect on customer engagement. This result is in line with the results of the study by Enginkaya & Yilmaz (2014), where they found that opportunity seeking was the highest motivation driver when it comes to the reason why customers engage with a brand on social media. In addition to opportunity seeking being the highest motivation driver, another explanation could be that opportunity seeking is one of the motivation factors that can be clearly measured in a post on Facebook. As stated by Enginkaya & Yilmaz (2014) customers are more likely to engage with a brand on social media if the promotions and discount campaigns proposed by the brand has financial benefits for them. In this study, the posts coded as “opportunity seeking” were all either related to a sale the brand was having or a giveaway where the customers could win free items.
Results showed that “entertainment” has no significant effect on customer engagement, therefore H4 was accepted. An explanation for this result is that entertainment as a motivation was the least important among the other motivation factors (Enginkaya & Yilmaz, 2014). Another explanation could be that entertaining content posted by a brand
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influences their attitudes towards the company’s image positively. This influence is impossible to measure in the context of a Facebook post and the engagement towards it.
As for “investigation” results showed that investigation has no significant effect on customer engagement (even though the p-value was close to being significant). This result is in contrast with the findings of Enginkaya & Yilmaz (2014) where “investigation” was ranked as the third most important motivation factor for customer engagement on social media. Making it more likely for customers to engage with a post on a brand’s Facebook page if the content is of an informative nature and as long as it is perceived as reliable.
As for the absence of brand affiliations in the gathered data, one explanation could be that brand affiliation cannot be measured with posts and customer engagement towards these posts. Which means that brand affiliation could be measured or analyzed with other aspects of a brands’ Facebook page or it is a factor that only be measure from a customer perspective. As indicated in Table 1, Appendix A, brand affiliation is (one of) the main reason(s) why people follow brands on social media.
To answer the main research question which is “What are the motivations behind
customer engagement on social media for branding in fast fashion retail start-ups?” can be
argued that based on the results presented above, only “opportunity seeking” has a significant effect on actual customer engagement in the terms of liking, sharing and commenting on a post published on a brand’s Facebook page.
As mentioned in the beginning, customer engagement is necessary in order to establish brand awareness. Establishing brand awareness is important for start-ups who wish to bridge the gap between being new and becoming a well-known business. In order to bridge this gap, startups should have knowledge of what motivates customers to engage with them on social media. Since the majority of the motivation factors used as the foundation for this study had no significant effect on customer engagement, what actually motivates
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customers can be considered a mystery still. In practice, only “opportunity seeking” turned out to have a significant effect on customer engagement. But only this motivation factor as a guideline for startups is not enough considering that the need for customer engagement is not only related to sales but also the creation of brand awareness and communities (Vinerean, Opreana & Tichindelean, 2014). Considering this and the definition of brand awareness given by Keller & Lehmann (2003) which is “the degree to which a customer is able to recognize
and recall a brand and identify the products and services related to the brand” leads to the
assumption that analyzing customer engagement based solely on the public’s interaction with posts might not be enough. If we take the company Most Wanted for example, at the time of the data collection and analysis it had a total of 170.000 page likes (number of people who follow the Facebook page), but the highest amount of likes a single post received was 5053 and the lowest was 19. These numbers already give an impression that the number of actual engagement is only a small fraction of the total amount of page likes the brand’s Facebook page received. Thus, that a person does not engage with posts of the brand on their facebook page, does not automatically mean that they cannot recognize and/or recall the brand.
5.1 Recommendation
As for recommendation for further research studies, it is important to point out that this study and the results were limited to only customer engagement towards posts on the Facebook page of fast fashion retail startups. Reacting to posts is one of the various ways customers are able to engage with brands on social media. Thus the fact, that a motivation factor had no significant effect on customer engagement related to a post, does not mean that it is not a valid motivation factor in other aspects of a brand’s Facebook page. Another aspect to take into consideration is the fact that date for this study was gathered from the outside. Future research should be done in collaboration with companies chosen in the sample. By doing this
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data that might be only be accessible as part of the company’s page analytics can be accessible for future studies as well. As the page owner you can collect a richer amount of data about your page and posts publishes, for example the total reach of the post, how many people have clicked on your post etc. These data will project a more in depth analysis of the page and it customer engagement, compared to the data that can be only accessed from the outside.
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6. Conclusion
This study started with the aim to help start-ups understand what motivates customers to engage with them on social media in order to create brand awareness as part of a successful brand building. The results of this study fell short of closing this gap, since compared to previous study, only one out of the five motivation factors studied as predictor for customer engagement had a significant effect on actual customer engagement.
These results raised more questions related to motivations behind customer engagement on social media in the case of start-ups. These questions were related to additional factors that might drive motivation and also additional ways to measure customer engagement. The approach to study customer engagement on social media based on the engagement with content posts alone, might not have been sufficient in order to be able to answer the main research question. Even though this study fell short to answer the main research question, it is still important for the survival of start-ups to be able to bridge the gap between being new and becoming well known.
Based on this it is recommended to have additional studies on this topic done in the future. Future studies should focus more on gathering data from the companies directly instead of using third party tools to gather date from the outside. Analytics reports produced by a company’s Facebook page are likely to be richer when it comes to information and might be able to give guidelines on the many different ways that customer engagement can be analyzed and measured on social media.
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Appendix A: Tables
Table 5. Interview based motivation factors for customer engagement Table 6. Type of post42 Table 7. Sum of likes, comments and shares Table 8. Motivation Factors Table 9. Page Likes
43 Table 10. Correlations Table 7: Multiple Regression with 2 IV Table 8: Multiple Regression with 2 IV
44 Table 9. Excluded Variable "opportunity seeking"
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Appendix B: Company Information
Tequila Fashion
Tequila fashion was founded at the beginning of 2016, as told by the customer service when asked. They describe themselves as an online shop for fashion lovers with the must haves for your closet and lifestyle. All this at super affordable prices. Source: www.tequilafashion.nl
Reinders
“Reinders is a dutch fashion label owned & created by the twin sisters Julie & Marie Reinders. We just started 2 years ago with our first collection, since then everything has changed. Because we have a different mind of fashion, Reinders becomes a huge success in the Netherlands. Reinders is known by the knitwear styles.
Reinders fills the gap between the high end and high-street fashion labels. The power of the brand lies in offering high end designs and luxurious materials with affordable prices, combined with a range of beautiful fits and elegant silhouettes.
with the outspoken styles and recognizable looks creates Reinders a strong image.” Source: www.reinders-jm.com/about-us
Yaella Fashion
Although no description of this company was provided on the Facebook page or the website of the webshop. From the year at the bottom of the website, we established that the company was founded in 2015. Source: www.yaellafashion.nl
Mode Junkies
Mode Junkies opened on November 2, 2015. The company describes that it stands for inspiration, own style and affordable. They want to show that fashion doesn’t have to be expensive and they want to inspire you to develop your own style.
Source: www.facebook.com/pg/Modejunkies/about/?ref=page_internal
Lofty Manner
As of 2012 the Dutch Michael Vinke has been full time busy with Lofty Manner. Lofty Manner is is a female clothing brand with the main goal to offer its customers high fashion collection at high street prices (affordable). They want to offer customers unique items, selective distribution and the feeling of a boutique brand. Source: www.facebook.com/LoftyManner/
Most Wanted
“Such overwhelming choice of clothing on the existing fashion webshops and we could not find what we were looking for. Therefore, we started with the Most Wanted boutique shop in 2014. The idea behind the shop and boutique? Items according to the latest trends, classy yet cool and then also for a nice price. Our inspiration we get from international fashion
magazines, the IT girls of the moment and of course the famous fashion bloggers / vloggers.” Source: www.mostwantednl.nl
