How to engage with customers on Twitter? The effect of image
congruity on online consumer participation.
An investigation into the fast-moving consumer goods industry
Name Emma Elisabeth Vloeimans
Student number 10876693
Program MSc Business Administration
Track Marketing
Faculty Faculty of Economics and Business Administration Institution Amsterdam Business School, University of Amsterdam
Supervisor Mw. Dr. H.H. Lee
Date of submission June 29, 2015
Statement of originality
This document is written by Student Emma Elisabeth Vloeimans 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.
ABSTRACT
Study - The current study investigated whether image congruity – a fit between a brand’s associations and displayed brand personality on social media – has a significant influence on the level of consumer participation. Additionally, which brand personality led to the highest level of consumer participation is investigated as well.
Method - Twenty-seven fast-moving consumer goods brands were analyzed online, leading to 722 usable tweets in a period of three weeks. Tweets were coded into one out of five brand personality dimensions (sincerity, excitement, sophistication, competence and ruggedness), based on Aaker’s (1997) brand personality framework. The variables under investigation (total consumer participation, number of retweets, number of favorites and number of responses per tweet) were analyzed by conducting separate univariate ANOVA tests.
Findings - The findings indicate that image congruity does not necessarily lead to improved consumer participation. Furthermore, individual brand personalities can be used to reach different goals.
Conclusion - Rather than spending additional time and money to accomplish online image congruity via matched brand personality and brand associations, marketers should look at the goal of their individual messages. An exciting brand personality evokes the highest overall participation and the highest number of retweets, while a sophisticated personality yields the highest number of favorites and responses. Additionally, a sincere brand personality leads to the overall lowest scores of consumer participation.
Keywords. Twitter, Brand Personality, Marketing, Social Media, Twitter, Brand Associations, Brand Participation, Brand Communications, Image Congruity
TABLE OF CONTENTS
ABSTRACT ... 3
CHAPTER 1 – INTRODUCTION ... 6
CHAPTER 2 – THEORETICAL BACKGROUND ... 10
2.1ONLINE BRANDING ... 10
2.2ONLINE BRANDING STRATEGIES ... 11
2.3BRAND PERSONALITY ... 17
2.4BRAND ASSOCIATIONS AND THE FORMATION OF BRAND PERSONALITY ... 23
2.5FIT BETWEEN ASSOCIATIONS AND BRAND PERSONALITY ... 25
CHAPTER 3 – METHODOLOGY ... 27
3.1PARTICIPANTS AND PROCEDURE ... 27
3.2DESCRIPTIVE MEASURES ... 33 3.3DATA ANALYSIS ... 35 3.4SECOND CODER ... 36 CHAPTER 4 - RESULTS ... 37 4.1PRELIMINARY TESTS ... 37 4.2HYPOTHESIS TESTING ... 41 CHAPTER 5 – DISCUSSION ... 53 5.1DISCUSSION OF RESULTS ... 53 5.2THEORETICAL IMPLICATIONS ... 62 5.3MANAGERIAL IMPLICATIONS ... 63
5.4LIMITATIONS AND FUTURE RESEARCH ... 64
CHAPTER 6 – CONCLUSION ... 66 REFERENCES ... 66 APPENDICES ... 74 APPENDIX I ... 74 APPENDIX II ... 74 APPENDIX III ... 75 APPENDIX IV ... 76 APPENDIX V ... 78 APPENDIX VI ... 79
Chapter 1 – INTRODUCTION
Social media have become a very important environment for brands to operate in. Different forms of social media (e.g. Twitter, Facebook, LinkedIn) enable brands to reach enormous numbers of customers, which would not have been possible before the social media era (Taylor, Celuch & Goodwin, 2004). This shift to online marketing has led to an increasing demand for information transparency, meaning that consumers ask brands to be entirely open about everything that is going on within the company (Yan, 2011).
Since information is easily spread around the web, dissatisfied customers gained more attention as well (Kaplan & Haenlein, 2010). Due to these developments, relationship marketing has become more important than ever before. Maintaining online relationships with customers is a top-priority nowadays, because of the huge impact of these relationships on the success of a brand. To carry out online relationship marketing, brands should be able to reach customers directly, which is possible by using social media (Morgan-Thomas & Veloutsou, 2013).
However, it is hard to evaluate direct gains from efforts on social media. Therefore, message effectiveness has become an important concept, achievable via image congruity. A message is effective when it is aligned with the brand’s values and when it taps into the consumers’ needs (Dillard, Shen & Vail, 2007; Maehle & Supphellen, 2011). A brand’s image is built around associations consumers hold for the brand, which can be “anything
linked to the brand in memory” (Aaker, 1991, p. 109). The image of the brand consists of the
overlap between the different associations consumers hold for a brand. Brand personality is part of these associations and can best be described as the human characteristics attributed to a brand by its customers (Aaker, 1997).
From a marketer’s perspective, brand personality forms the ideal tool to tie consumers to the brand. Brands are able to give direction to how consumers perceive their brand
personality via their communication tools (Kwon & Sung, 2011), tailor-made adverts, or by using a certain tone of voice. Past research suggests that brand personality increases consumer preferences, causes emotional attachment to the brand, makes the brand a trustworthy partner in the consumer-brand relationship and make consumers more loyal (Aaker, 1997). Having a brand personality makes lasting relationships with consumers more likely to occur. Social media platforms help brands in establishing these personalities. For example, Twitter is often used as a way to show the more human-like side of the brand, which results in consumers assigning personalities to the brand and treating the brand as a human-like partner in their relationship with it (Kwon & Sung, 2011).
Associations evoked by a brand need to be consistent with each other, to create a strong brand image and a lasting personality. Image incongruity is expected to lead to a decrease in consumer-brand participation (Farquhar, 1989; Punyatoya, 2011). The match-up hypothesis, derived from image congruity studies, emphasizes that the message’s content should be congruent with the endorser’s image and the message it spreads. This message can be translated to the case of brand personality display and the desired image the brand wants to communicate. This implies that content, tone of voice and other facets that lead to brand personality should match the desired outcome of the message (Dillard et al., 2007; Maehle & Supphellen, 2011).
In this sense, the brand’s communication tools are regarded as a chance to strengthen the brand associations the consumer currently holds for the brand. Inconsistency of the brand’s image decreases the trustworthiness for the brand’s communication (Sjödin & Törn, 2006). Regardless of the evidence of the effectiveness of image congruity, it has never been researched in combination with online brand personality. A well-defined brand personality can lead to consumer preference for the brand, increase in use, emotional attachment and sustainable differentiation from competitors (Singuaw, Matilla and Austin, 1999). To achieve
this state, the brand’s personality should be “robust, desirable and consistent” (Singuaw et al., 1999, p. 49).
Starbucks’ online marketing strategy forms an interesting example. The brand carries out a consistent brand personality on several social media platforms, such as Twitter and Facebook. Since online, the brand has been regarded as a sincere and honest personality, which is in line with their brand values. In only seven years, Starbucks has been regarded as one of the most engaging brands online, having nearly 36 million followers on Facebook and nearly 9 million followers on Twitter today (Gembarski, n.d.).
Based on prior literature and practical examples, it is expected that fit between a brand’s perceived and displayed brand leads to improved message effectiveness and therefore to a higher level of consumer participation. To investigate this, the study is built around the following research question: What is the effect of the fit between online brand personality
display and online brand associations on consumer participation?
This research makes several important contributions. Both theoretical contributions and managerial implications are twofold. The theoretical contributions involve the setting of the research and the issue of online image congruity. First, the success of the brand personality technique has not yet been researched on social media. To that end, this study extends the current knowledge on brand personality techniques into the field of social media. Differences in results for this setting are expected due to the velocity of messages spread around the web, and the different ways in which consumers engage with a brand in an online environment. The second contribution involves whether image congruity improves the effectiveness of a social media message, and so, leads to online consumer engagement. Image congruity is long held to be effective for the brand’s image (Sjödin & Törn, 2006), but has not yet been researched in an online setting.
The managerial implications of this research are twofold as well. First, brands often incorporate some kind of brand personality in their communications, but there is little empirical evidence which one works best. The findings often stem from (offline) advertisements or many different product categories. The outcomes of the current research aim to provide guidance to successfully positioning a brand on social media, based on a brand’s current brand associations and consumer engagement. Second, the use of social media to engage in direct conversations with customers becomes a bigger concern every day. Marketers have the tools to shape their marketing communications according to their online target group, meaning that they are able to approach consumers more personally. This can be very valuable because it ties consumers to the brand. The findings of the current paper aspire to show which brand personality is regarded as most valuable and suitable to gain the highest level of consumer participation. The combination of brand personality and a Twitter environment has not been researched before, while Twitter is the medium via which brands and consumers can interact on a direct basis (Hennig-Thurau, Malthouse, Friege, Gensler, Lobschat, Rangaswamy & Skiera, 2010).
The next chapter provides an overview of past literature and states the developed hypotheses. In different sections, social media strategies, user participation and brand associations will be discussed. In the method section you will find an explanation of the way in which the data for further investigation has been collected. After the methodology follows the chapter in which results are displayed and explained, after which the discussion and conclusion will discuss the overall research and outcomes.
Chapter 2 – THEORETICAL BACKGROUND
2.1 Online branding
The role of the online brand environment has changed significantly over the past years. Brands start to increasingly incorporate social media in their marketing strategies, to make sure they do not miss any opportunity to reach (potential) customers and to track customer opinions about their brands. The fact that consumers pass on information to each other makes the individual user even more valuable. Without social media it would not be possible to reach as many consumers directly as it is today (Kim & Ko, 2012).
Social media occur in many different forms. These types of media consist of communities, blogs, e-mail, forums and social networking sites. To accomplish company-wide goals, stick to the mission and vision statements and carry out the brands’ values, the elements of the promotion mix should be streamlined and steadily communicated (Mangold & Faulds, 2009; Smith et al., 2012). Moreover, social media usage should be embedded in the firm’s marketing strategy and can have a major influence in how individuals perceive brands.
Brands continuously seek for online interactions with customers, to achieve long term relationships, personalized via direct online messaging (Brodie et al., 2011). Social media empower companies to send messages to their customers and to have direct conversations with them. Hence, social media facilitate the means by which customers can engage in direct conversations with each other. These consumer-to-consumer conversations have a tremendous impact on brands, because of the enormous reach of online word-of-mouth, meaning that consumers pass on brand-related information to each other. Social media have become a very important part of the marketing promotion mix, and contains both traditional marketing techniques, in which brands are talking to consumers, and emerging ways of
spreading word-of-mouth. Brands are not capable of having full control over the content of such conversations (Mangold & Faulds, 2009).
Hence, past research has shown the importance of online branding; it helps companies to improve the understanding of their customers and to gain better insights in their perceptions towards the brand. Clear communication from the brand’s side leads to more useful feedback from the customer base, which in the end could cause enhanced message effectiveness (Ibeh, Luo & Dinnie, 2005).
2.2 Online branding strategies
So far, literature has suggested that brands should use social media to place content that is fresh, up-to-date and frequent, to arouse consumer participation (Ashley & Tuten, 2015).
Past literature on traditional forms of marketing and communication (Duncan & Moriarty, 1998) has already recognized that speaking to customers is as important as listening to them. When executed, interactive relationships between brands and consumers start to develop. This leads to increased value per individual consumer and increased consumer retention. Therefore, communication is key in developing and maintaining relationships.
The authors (Duncan & Moriarty, 1998) hold marketing responsible for the perceptions and associations consumer have about the brand and state these are important for maintaining relationships, even more than actual qualifications are. Different forms of communication are used to maintain interaction with stakeholders, such as consumers. Furthermore, traditional media are still very useful to create brand awareness, while new types of media (such as social media) are more useful for creating a brand’s image (Bruhn, Schoenmueller & Schäfer, 2012).
More recent research (Madhavaram, Badrinarayanan & McDonald, 2005) concluded that marketing communications form the voice of the brand and are therefore the ultimate tools to engage in conversations with customers. A combination of traditional and new media are propagated in current research; traditional media is still very useful to create brand awareness, while new types of media (such as social media) are more useful for creating a brand’s image (Bruhn, Schoenmueller & Schäfer, 2012).
Some online branding strategies are more brand-central than others. For example, functional/informational strategies lead to functional messages, which are processed in a rational way, while emotional/transformational strategies lead to psychological processing. The goal of a functional strategy is to enhance a consumer’s brand knowledge, which leads to increased emotional attachment to the brand (Ashley & Tuten, 2015).
Additionally, Motameni and Nordstrom (2014) have a more practical view on online and social media branding strategies. They state that, for example, firms could successfully carry out a strategy in which they continuously keep consumers aware of the benefits their products or services provide. This can be conducted via coupons, discounts and other promotional devices. New customers could be targeted on basis of emphasizing the brand’s value proposition and so, showing what the brand has to offer. This strategy also works well for consumers who are in an unstable relationship with a brand. The aim of this strategy is to create new consumers, retain current ones, and to inform, educate and stimulate the customers regarding the brand. Another brand-centered strategy is about ‘securing competitive comparison’, in which brands tend to compare themselves or their offering to competition to make the brand look more attractive compared to other brands.
Different studies are pointed towards combining the reach of both the consumer’s and the brand’s network. For example, Larson and Watson (2011) witness the existence of word-of-mouth advertising as an online branding strategy. This strategy has a focus on
consumer-to-consumer interaction, which is pivotal in social media contexts. Firms could either let consumers fully decide the content of the online messages or they could shape their consumers’ opinions and expressions by developing online communities via existing social media platforms, such as Twitter or Facebook. The authors further argue that a persuasion strategy is commonly used. Consumers gained power to engage in the firm’s conversations and so strive to get their ways. This increases the brand’s power to persuade their consumers in high numbers, since consumers are able to persuade each other in favor of the brand as well.
Another way to make use of customers’ reach is by triggering customer collaboration, in which consumers are creators of the firm’s value. This implies that firms use co-creation of their consumers as a social media strategy to actively attach consumers to the brand. Ashley & Tuten (2015) note that by focusing on an emotional/transformational strategy, consumers process a brand’s content in a psychological way. This forms a different focus on collaborating with consumers, namely by letting them develop emotional attachment to the brand via psychological processing of the brand’s messages.
At last, Okazaki mentioned the development of an online brand personality, via a brand’s online communication forms. Amongst others, this personification of a brand aimed to connect with customers and to position a brand’s product. The author found that it is possible to extract what kinds of personality companies aim to display on their websites. The findings indicate that the websites show little, but consistent associations between the intended brand personalities, adapted to different audiences they target with different messages. However, the study did not investigate the success of the displayed personalities in combination with consumer participation; it solely focused on website of multinational companies, which incorporated different messages for different audiences.
As the summary in table 1 on the next page shows, the overall goals of online branding strategies have a focus on attaching customers to the brand and enhancing the overall brand’s image. This can either be done via the brand’s communications or by letting consumers influence each other, by stimulating consumer-to-consumer interaction. The latter makes brand-related content more reliable in the eyes of the consumers, which shows that consumer generated content outperforms traditional marketer-initiated messages in many cases (Heinonen, 2011).
Nevertheless, brand personality is not yet explored in a social media setting. Brand personality, it is expected to be an important part of a brand’s online branding strategy, while its offline success has been widely acknowledged (Aaker, 1997; Low & Lamb, 2000).
2.2.1 Consumer participation
Consumer participation on social media is very important because it contributes to the marketing content of a brand. Consumers’ presence on social media can lead to three types of behavior: consumption, participation and contribution. Consumption regards merely reading and consuming the brand’s content in an online environment. Participation involves social interaction and includes engaging with the brand’s content, by, for example, responding to it. Production of content concerns active creation of content by consumers and is the most active form of binding consumers to the brand. Letting consumers engage with the brand in an online environment is very valuable because of the reach each individual user has. One tweet spread on the web can reach millions of people, making electronic word-of-mouth much more influential than traditional word-of-mouth (Heinonen, 2011).
The current study focuses on consumer participation, which can occur in three forms on Twitter; consumers can retweet the brand-initiated content, they can hit the star-formed button and thereby ‘favorite’ the brand’s message or respond to the brand’s message. Retweeting a tweet expands the reach of the message tremendously. A retweet appears on the homepages of the retweeter’s followers, who have the ability of retweeting the tweet as well. The star-formed ‘favorite’ button is merely a function to save a certain tweet. Users can access their favorited tweets any time when they visit their profile. Responding to a tweet is the most active form of participation, since it entails more than just a single mouse click. By responding to someone’s tweet, a conversation can be started (www.twitter.com). Translated to brands, retweets create awareness of the tweet’s content, favorites cause the brand to stay in people’s mind and responses to tweets foster direct interaction with consumers.
On average, a brand-initiated tweet is not very likely to go viral, meaning that a tweet becomes retweeted many times and widely spread around the web. Rather, retweet behavior is based on individual willingness and personal preferences (Zhang, Jansen & Chowdhurry,
2010). Therefore, it is very valuable to discover whether there are brand personality-related reasons that could possibly explain retweeting and other participation behavior.
2.3 Brand personality
Brands are able to display a certain form of human personality in their expressions. Brand personality is explained as the human traits displayed on a brand. It serves as the factor on which consumers differentiate brands from each other and helps consumers to understand what needs are being fulfilled by the brand; a very important marketing practice (Sung & Kim, 2010). One of the initiators of brand personality as we know the concept today is Jennifer Aaker. In her paper (Aaker, 1997) she described the “Big 5” dimensions of brand personality and draws conclusions about the effect of brand personality on consumer behavior. The Big 5 brand personality dimensions are “sincerity, excitement, sophistication,
competence and ruggedness” (Aaker, 1997, p. 347), which are derived from a 42-item brand
personality scale. She noticed that the Big 5 human personality traits (openness, conscientiousness, extroversion, agreeableness and neuroticism) were not readily applicable to brands. The results of her study show that only three out of five traits match the Big 5 human personality traits: competence, excitement and sincerity respectively match with conscientiousness, extraversion and agreeableness. The other two traits are not related to human characteristics. Appendix I provides an overview of the brand personality dimensions as developed by Aaker (1997), which are used for this research.
2.3.1 Brand personality dimensions
Sincerity is typified as the personality that is genuine, authentic and down-to-earth (Aaker,
1997). It can play a major role in displaying online brand personality. On the diffuse web, sincerity is an important factor for users to be associated with a brand and is closely related to confidence (Okazaki, 2006). Furthermore, it can be related to friendliness, honesty and sentimentality (Müller & Chandon, 2003). Consumers find it very important that brands are
acting honestly and trustworthy on social media (Kaplan and Haenlein, 2010). A sincere brand personality is expected to be a reliable partner in the (online) brand-customer relationship, which could deepen the attachment to a brand. However, when transgression takes place - situations in which promises are not kept or the brand suddenly behaves in an unexpected manner - the relationship is likely deeply harmed and hard to recover to the original state, especially for sincere brands as relationship partners. Relationships with exciting brands suffer less from these situations, because an exciting brand’s actions are less predictable. Transgressions within relationships between brands and consumers are likely to occur on the web, since content cannot be hidden and is spread around the world within seconds (Aaker, Fournier & Brasel, 2004).
For example, KLM - a very reliable and authentic company - posted an ambiguous tweet after an important soccer match during the world cup games. The Netherlands defeated Mexico, after which KLM tweeted “Adios amigos! #NEDMEX”. Despite that KLM removed this tweet several minutes after posting it, the tweet was soon picked up by Mexican football fans and they did not appreciate the message. A ‘KLM gate’ quickly evolved and many Twitter users called up for boycotting the airline company (Eigenraam, 2014). Because of the major ups and downs that are likely to take place within a relationship between a sincere brand and its consumers, this relationship is expected to be very unpredictable because of all brand-related information on the web. Therefore, a sincere brand personality is not expected to show any consisting patterns in terms of consumer participation.
Excitement is characterized by being adventurous, daring, young, cool, unique and
spirited (Okazaki, 2006). According to past research (Berger & Milkman, 2012; Chen & Berger, 2013), people want to be interesting on the web and therefore, do not want to share or be associated with boring content. Kaplan and Haenlein (2010) also note that excitement is one of the basic premises for consumers to participate with a brand in many cases.
Excitement is related to advertising style and endorsers, which means there is a role for brand personality display in executing an exciting personality (Maehle et al., 2011). Berger and Milkman (2012) found that highly arousing, positive, or useful content was mostly spread. This finding can be explained by the fact that individuals like to show others both that they have knowledge about where to find interesting content and their willingness to help others. Content has to come alive and needs to suit the audience (Kaplan & Haenlein, 2010). Other research (Okazaki, 2006) suggests that excitement is positively related to online connectedness in the consumer-brand interaction atmosphere. At last, excitement is found to be the most important personality that is able to differentiate brands from others (Singuaw et al., 1999). Therefore:
H1: Brand personality dimension excitement leads to the highest level of consumer
participation.
As stated in the previous section, the number of retweets, favorites and responses together form overall level of consumer participation. The hypothesis will therefore be tested for every level of engagement separately, to check whether there exist notable differences between the different forms of participation.
Sophistication is related to glamour, romance, appearance and femininity (Müller &
Chandon, 2003). In popular business magazines, sophistication is assumed to be an important determinant of the most valuable brands (Okazaki, 2006). It is important for customers because of social identity-related reasons, such as comparison to reference groups and identity development, while competence, for example, is more dominantly related to utilitarian aspects (Maehle et al., 2011). Because of the identity-related nature of this brand personality dimension, it is not expected that a sophisticated brand will lead to extreme levels
of consumer participation in an online environment. Despite the fact that people want to express themselves online, sophistication is often related to real-life applications; for example a wealthy and attractive man driving a Rolls Royce is assumed to be even wealthier than without the car. This also holds for opposite situations: when a less wealthy-looking person drives an expensive car, it is perceived as less attractive in the eyes of others (Das, Vermeulen, Laagland & Postma, 2010). These links between sophisticated brands and its owners are hardly applicable in online environments, where people are often not entirely traceable based on their user profiles. Therefore, sophistication is not expected to lead to impressive consumer participation compared to other brand personality dimensions. On top of this, Batra and Homer (2004) note that perceiving a brand as classy and sophisticated requires deliberate processing of the brand by consumers, which is generally not the case for brand communications.
Ruggedness stands for tough, western, outdoorsy and masculine (Aaker, 1997). It is
said to be typical for the Western culture and not applicable to more Eastern cultures (Lin, 2010), as it is related to a kind of American individualism. Ruggedness is suggested to have a positive effect on the perceived quality of a brand (Hayes, Alford, Silver & York, 2006). Furthermore, ruggedness is related to trust in a consumer-brand relationship, but does not evoke feelings of positive emotions towards the brand. People tend to associate rugged brand personalities with rugged circumstances, therefore hoping that the related products perform their utilitarian function well (Sung & Kim, 2010).
Besides its utilitarian value, the ruggedness dimension of a brand is regularly derived from product attributes and the product category. A classical example is the brand Harley Davidson. The design and speed of the motorcycle define the level of ruggedness. The product category is highly associated with masculinity (Maehle & Supphellen, 2011). Both sophistication and ruggedness are identity-based brand personalities. Both personality
dimensions are not expected to lead to notable consumer participation in an online environment, because they are both more directed towards real-life situations.
Competence is about intelligence, ability, reliability, success (Aaker, 1997), security,
technical competences, success, leadership capabilities and confidence (Fennis & Pruyn, 2007). It clearly differs from excitement, since it includes showing how competent and capable a brand is, instead of entertaining. Competence is about determination and patience (Lin, 2010). It is typically created by a consumer’s own experience, advertising style and worth-of-mouth and to utilitarian aspects of the brand, such as value for money (Maehle et al., 2011). Furthermore, Okazaki (2006) states that the competence dimension is the least relevant in online brand personality development. Freling and Forbes (2005) confirm this statement for the product category under investigation; for low involvement products (the authors use bottles of water as an example) other brand personality dimensions may work better than competence, because most brands in low-involvement categories are perceived as being equally competent. Based on this line of reasoning, competence is not expected to lead to high levels of consumer participation. This leads to the following hypothesis:
H2: Brand personality dimension competence leads to the lowest level of consumer
participation.
2.3.2 Brand personality communication
Traditionally brand personality was used to depict differences between product brands. Since competition got fiercer during the last decades, brand personality has evolved to the symbolic use of a brand; meaning that brand personality functions to differentiate a brand not only based on product features and utilitarian use, but on the personality a brand presents (Singuaw et al., 1999). Marketers should be aware of the brand personality they depict, since some brand personalities are more powerful than others. In principle, every relation to a
positive personality is sufficient, but does not set a brand apart from competition per se. For example, competence is seen as a basic requirement and will not be a distinguishing feature, while an exciting brand personality might do so. Therefore, not every brand personality is expected to be evenly useful for online brand personality display (Freling & Forbes, 2005).
Brand personality is not developed one-dimensionally; it is both based on how consumers perceive the brand and it can be analyzed from the brand’s side, by looking at the brands communicative executions. Companies should be aware that the brand personality they carry out is part of the communication strategy and therefore should be well considered (Ankomah Opoku, Abratt, Benixen & Pitt, 2007). In this case, brand personality can be described as the human characteristics associated with a brand by its consumers (Aaker, 1997) and brand personality display involves how the firm intends to communicate brand personality.
Past research has shown that companies display their brands’ personalities in several ways. One way in which to display ruggedness, for example, is by emphasizing the adventurous part of the brand/product, while showing ability, development and stability shows a competent brand personality dimension. To communicate sincerity, brands usually focus on friendliness, trustfulness, family-oriented content, honesty and cheerfulness. Sophistication may be emphasized by content related to heritage of the brand, an idealized depiction of daily life or luxurious settings. It is clear that brands have tried to incorporate a brand personality into their communication strategy to enhance their brand’s positioning compared to competition (Pitt, Opoku, Hultman, Abratt & Spyropoulou, 2007). Several studies (Ankomah Opoku et al, 2007; Pitt et al., 2007; Opoku et al., 2006) have found that brands depict a brand personality via their websites. However, in some cases it was not clear which type of brand personality brands were trying to execute. Sometimes different messages at one website were conflicting according to tone of voice or overall brand personality. The
success of a single message on a brand’s website depends on the way in which the brand succeeds in capturing a single type of brand personality (Opoku, Abratt & Pitt, 2006). Furthermore, a brand’s personality is gradually developed via the entire marketing mix, such as price, product details, communication and advertising. Overall, a brand’s communication is said to be the direct and most important tool to display brand personality (Maehle et al., 2011).
Another view on brand personality was developed by Okazaki (2006). In his research, online brand personality display is categorized according to functional and expressive stimuli, where the former tends to focus on factual information and knowledge gathering and the latter on evoking emotions. He has found that online communication containing descriptive and informational content is more likely related to functional stimuli, while communication that focuses on emotional aspects is more likely related to expressive stimuli. This shows that the way of communicating a message to the customers is able to determine the inferred brand personality. In the end, an important goal of depicting a brand personality is that it will lead to more effective brand communications (Freling & Forbes, 2005).
2.4 Brand associations and the formation of brand personality
Brand associations contain anything that consumers link to the brand in memory (Aaker, 1991). Therefore, they form the basis for a perceived brand personality. Consumers assign personality dimensions to brands in two major ways: via direct and indirect ways. The direct approach states that the characteristics of entities associated with the brand are directly transferred to the brand itself, such as the CEO and the company’s employees (Maehle et al., 2011). This can be linked to the online branding strategy of assigning spokesperson(s) or spokes character(s) to the brand; it leads to consumers assigning the person’s or character’s personality traits to the brand (Ashley & Tuten, 2015).
On the contrary, the indirect approach states that people usually perceive a certain personality to a brand based on the observation of the brand’s behavior, therefore its entire marketing mix. This implies that the brand personality gets more meaningful over time. To illustrate this, certain skin creams can exclusively be bought at the pharmacy. For a consumer, the pharmacist is an intelligent person and this may form a sign of a competent brand; the pharmacy is viewed as reliable, responsible and dependable. Often, the price of such a skin cream is slightly higher than those available at the regular drug store. These elements and associations make the consumer feel confident buying the product and make the consumer assign a brand personality to the brand based not only on product features itself (Maehle et al., 2011).
In this view, both direct and indirect ways of assigning personalities to brands are based on associations consumers hold for the brand. This shows the importance of marketing communication in the development of a brand personality; every experience with the brand has the possibility for the customer to develop brand associations, which contribute to the relationship between the brand and the customer (Smith et al., 2012). In the end, brand associations form a brand personality at the consumer side. This personality can form an important point of differentiation compared to competition (Aaker, 1997; Low & Lamb, 2000).
This reasoning implies that brand managers should be aware of associations they create in the minds of the consumer. As Wee (2004, p. 321) stated: “Successful brands were
those that created a strong brand personality by encouraging customers to perceive the attributes to which they aspire as being strongly associated with the brand”. Thus, companies
should be careful with the kind of associations they evoke. Since brand personality has two sides – on the one hand it is based on the associations consumers hold for the brand, on the other hand it stems from the expressions of the brand towards a certain brand personality -
employing the communication in the direction of a certain type of brand personality, brands are able to influence the associations consumers hold for the brand.
2.5 Fit between associations and brand personality
Concerning the dynamic process of brand personality development (Johar et al., 2005) it is expected that consumers react more favorably to a brand that spreads a consistent message. As previously stated, brands develop an intended brand personality via their communication tools. Furthermore, consumers assign a brand personality based on associations they hold for the brand, i.e. anything they have linked to the brand in memory.
Past research (Keller & Lehman, 2003) has found that consistency of the marketing program is an important predictor of the success of a brand and the level of brand awareness in the consumers’ minds. Congruence of marketing tools is therefore an important factor, which indicates brands should have an overall clear and congruent image, consisting of some kind of personality and associations. In line with this, Bottomley and Doyle (2006) mark that advertisements that were perceived as congruent with the brand were found more appropriate and led to easier processing. Their study focused on the symbolic use of brands, of which brand personality is part.
Not only the messages should be aligned with a brand’s values, one brand’s different messages have to be uniform as well. Brands should therefore achieve a form of congruity concerning their expressions; they should simply be in line with each other, since they often serve to reduce confusion and to be more transparent towards customers (Kaplan and Haenlein, 2010). Keller (2009) clearly supports the necessity of message alignment as well: to attract customers, the brand’s expressions should spread a consistent message and in terms of content and tone of voice. Alignment of message content makes the marketing execution more effective and efficient. Notwithstanding, tailored online messages to individual
customers can be useful as well. The tone of voice and the kind of content should be similar when creating and maintaining a robust brand personality.
At last, Maehle and Supphellen (2011) conclude that the match-up hypothesis - which states that celebrity endorsement should be congruent with the inferred product personality - is applicable to other types of stimuli in combination with the communication of a brand. Therefore, they state that there should be a match (in this research presented as ‘fit’ and ‘image congruity’) between the brand personality and the brand’s intended message, depicted by this brand personality.
The type of fit that is important here is thus fit between the displayed brand personality by the brand itself and the associations from which customers infer a brand’s personality. Earlier research already suggested these findings. Till (1998) noted that the use of a celebrity endorser (a way of depicting a brand personality) should fit with the brand’s image, e.g. a glamorous and stylish celebrity should feature a sophisticated brand to trigger more positive consumers responses.
The importance of fit was also confirmed by Wee (2004), who stated that companies should have a clear picture of their aspired brand personality and should strive for coherence across all expressions of the brand. In this sense, brand personality becomes the guiding principle for marketing management and a brand’s future success. Additionally, direct evidence for the need for consistency was found in recent research (Rosgpigliosi & Greener, 2014). The authors found that brand personality consistency is very important and has an impact on the relationship between social media use and brand performance. Therefore, the following hypothesis will be tested:
H3: Fit between online brand associations and brand personality display generates a higher
Chapter 3 – METHODOLOGY
3.1 Participants and procedure
3.1.1 Sample selection
This research is applied to brands in industries that experience low-involvement purchase situations: the fast-moving consumer goods (FMCG) industry. This category is characterized quickly bought items, low involving purchase processes and fast consumption. Therefore, companies in the FMCG industry find it hard to distinguish themselves. One way to accomplish a state of differentiation is by leveraging the brand as a competitive advantage. For this category, it implies making use of relationship marketing, which can be reached via executing a brand personality and having direct contact with customers. Direct contact reveals the personality and identity of the brand (Leahy, 2011). Consumers process FMCG communications via a so-called peripheral route. This implies that communications for these types of goods rely on peripheral information, such as celebrities, brand endorsers or certain music, instead of product features or sales information. The symbolic use of brands has an impact in processing brand-related information via peripheral cues, since it evokes emotions at the consumer side and is rather about what the product might evoke at their consumers instead of focused on actual product features. Therefore, these brands are expected to benefit most from the symbolic use of brands, and thus, brand personality (Petty & Cacioppo, 1983; Hansen, 2005).
For the current research, the population consists of all FMCG brands that have an English-spoken Twitter account. The sample is derived from the ‘100 top social brands, the FMCG ranking’ (Sponder, 2014), which contains 100 FMCG brands that are present on social media. From this list 27 of these accounts were randomly selected and used for analysis. Based on prior research (Waters & Jamal, 2011) this number is believed to be
sufficient. The sample contains a variety of brands in the fast-moving consumer goods industry.
Official Twitter account names were derived from the brands’ homepages. Per brand Tweets were selected in a time span of three weeks, to yield enough Tweets for investigation. Given the fact that the brands under investigation post several tweets a day, it is expected that an analysis of three weeks is sufficient to draw conclusions on (Waters & Jamal, 2011). A list of the used brands can be found in Appendix II.
3.1.2 The medium
Twitter is a micro blogging platform on which users can spread messages up to 140 characters, a tweet (Java, Song, Finin & Tseng, 2007). Users can follow each other without any permission. By following other users one receives tweets from those users on a homepage. This page differs from person to person; depending on which users someone follows (Zhang, Jansen & Chowdhury, 2011).
If followers like the content of a tweet, they can hit the ‘retweet’ button. This means that their followers receive the tweet on their homepages as well. Another possibility is ‘favoriting’ a tweet, which is commonly used when users like a tweet and want to save it for later, without followers being noticed. At last, users can respond to a tweet, indicating that they send a tweet to the message-initiator, which is placed below the original tweet. Often the ‘@’-sign is used, to mention to whom one is tweeting (Tumasjan, Sprenger, Sandner & Welpe, 2010).
Twitter is very useful for this research, because it is openly approachable, allows for real-time data and has a very high level of brand-related content compared to other social media (Smith et al., 2012). Twitter allows brands to engage in conversations with customers, so it forms a cheap way of reaching a target audience directly (Kaplan & Haenlein, 2010).
Furthermore, Twitter is a very useful tool for conducting this research, since it allows for anthropomorphism; “the psychological process of seeing the human in nonhuman forms and
events” (Kwon & Sung, 2011, p. 5). By being present on social media, brands are able to
improve the anthropomorphization process by their consumers, by assigning a human voice to the brand as part of the marketing and communication strategy.
3.1.3 Procedure
3.1.3.1 Data collection and initial analysis
An initial check is conducted to check whether the selected brands actually contain some kind of brand anthropomorphism. The method of Kwon and Sung (2011) will be used. Their method in which brand anthropomorphism is operationalized is the basis for the first step. Table 2 shows the operationalization of brand anthropomorphism as displayed on Twitter; Appendix III shows an original overview.
Dimensions Operationalization
Human representatives Profile pictures, celebrity endorsers, marketers signatures (conducted manually)
Personal pronouns First-person usage; second-person usage • I, me, mine
• We, us, our, ours • You, your, yours
• They, them, their, theirs Non-verbal cues
(Non-verbal cues continued)
• Abbreviations; ROFL, LOL, WTF • Emoticons; :) :( :p :D
• Repeated punctuation; … !! ?! ?? • Capitalization; CHECK THIS • Sound mimicking; ehm, ehh, grr Imperative verbs (Initiating a relationship) • Follow • Stay tuned • Register • Sign up • Join us • Come by
Table 2. Operationalization of brand anthropomorphism displayed on Twitter (Kwon &
Sung, 2011)
Brand anthropomorphism is coded into four dimensions: human representatives, personal
pronouns, non-verbal cues and imperative verbs. Tweets are coded into two nominal
categories: values can be either ‘0’, indicating the tweet does not contain a certain characteristic or ‘1’, indicating the tweet does contain the particular characteristic of anthropomorphism. This is conducted manually for all participating brands.
After this step, tweets were coded according Aaker’s (1997) brand personality scale;
sincerity, sophistication, excitement, competence and ruggedness. Table 3 provides
Brand personalities Keywords
Sincerity Domestic, honest, genuine, cheerful,
down-to-earth
Sophistication Glamorous, pretentious, charming, romantic
Excitement Daring, up-to-date, imaginative, spirited
Competence Reliable, responsible, dependable,
efficient, successful
Ruggedness Tough, strong, outdoorsy, rugged
Table 3. Aaker’s (1997) brand personality traits and their keywords
Coding will be conducted manually; a second coder coded 10% of the collected tweets to check the reliability of the coding scheme. An overview of the coding scheme can be found in Appendix IV.
The coding scheme was applied as follows: on April 17 Ginsters tweeted the following tweet: “Off to the gym this weekend? Of course you are. #FeedTheMan” (Appendix V shows the original message). The picture incorporated with the tweet contained a gym logo with strong, masculine arms. The tweet is coded as ‘ruggedness’, because it contains masculine, tough and rugged content, telling men should go to the gym during the weekend and need to have proper food. At April 2nd, Extra Gum shared the following tweet: “The only thing better than getting a basket full of treats is getting to share them with your
family!” This tweet is coded as ‘sincere’, because it contains family-related content and has a
cheerful tone of voice.
3.1.3.2 Discovering online brand associations
In this study, brand associations are measured following the methods proposed by Aggarwal et al. (2009), who note that the occurrence of both a certain noun and adjective is a strong sign of subjectivity, which is often used to articulate an opinion. By using a search engine like Google, you can easily scan through a large amount of data. When such combinations of
nouns and adjectives are aggravated among the results, assumptions can be made about the online associations the brand evokes. Earlier research suggests that the use of adjectives in sentences enlarges the subjectivity of that particular sentence. The central underlying assumption is that when there is a strong evidence of co-occurrence of the noun and the adjective, there is assumed to be a positive relationship.
To check the relative co-occurrence of the noun and the selected adjective (which is one of the brand personality dimensions or one of its synonyms), a pointwise mutual information (PMI) algorithm is calculated. This shows whether the brand name is related to the chosen adjective. The PMI algorithm calculates the ratio of the adjective related to the chosen noun. Its simplified version is [count of occurrence noun+adjective/count of occurrence of noun alone]. The percentage of their co-occurrence displays the statistical strength of the association (Aggarwal et al., 2009). For example, the combination of IRN-BRU (noun) with the word ‘sincerity (adjective) generates 301.000 hits. IRN-IRN-BRU itself generates 664.000 hits, which implies a PMI of 45%. The combination of IRN-BRU with the adjective ‘excitement’ leads to a PMI of 5%.
The described method is often used to test the semantic direction of sentences. The steps to discover the associations are as follows:
1) Check the number of hits in Google for the individual brand
2) Check the number of hits in Google for both the brand and each individual personality trait
3) Check the number of hits in Google for a combination of the brand and each individual personality trait synonym1
4) Calculate the PMI for each individual brand for each personality dimension.
3.2 Descriptive measures
3.2.1 Dependent variables
The conducted analysis is based on the dependent variable consumer participation, operationalized via total consumer participation, number of retweets, number of favorites and the number of responses per tweet. These three dependent variables are tested separately and together they make up the overall level of consumer participation. An initial tweet appears at the homepage of its followers. The gathered values derived from the retweets, favorites and responses are numerical and continuous in nature; e.g. the higher the number or retweets, the higher the value of overall participation will be. Consumer participation is analyzed in a time period of approximately two days after the tweets have been tweeted, because, from initial analysis, most responses are expected to take place within the first two days.
3.2.2 Independent variables
For the first two hypotheses brand personality forms the independent variable, whereas fit is the independent variable for the last hypothesis. Fit is explained in the next section.
Brand personality is measured on a scale consisting of five items, i.e. the brand personality dimensions: excitement, sophistication, sincerity, ruggedness and competence. Brand personality is measured on a dichotomous scale, meaning that tweets could either depict a certain brand personality dimension (1) or not depict a brand personality dimension (0). When a tweet contains multiple personalities, the most dominant one is chosen and coded as (1). For example, Tetley’s tweet on April 3rd, during Easter weekend: “Happy Tea-ster!
WATCH our Easter Vine & RT to spread the joy to family & friends! #Tetley #Tea #Easter #happyeaster”. This tweet has been coded as ‘sincere’ because the message is to enjoy a
certain video with friends and family. However, this tweet could also be coded as exciting, since it contains wordplay or as competent, becase on the content is about an actual event.
3.2.3 Coding of fit
During the analysis on Twitter, tweets per brand were coded into brand personalities. This gave an overview of the different personalities displayed per brand. The most dominant personality for each individual brand’s Twitter account was found in this way. For example, HARIBO used brand personality ‘excitement’ in 91% of its tweets, indicating that HARIBO overall displays an exciting brand personality on Twitter. To check whether this matches with its online associations, the association analysis as described in section 3.1.3.2 was carried out first. After developing the associations, brands that had a mean PMI of M+SD or higher for the particular online perceived personality associations, were regarded as highly associated with this brand personality. For example, the overall mean PMI score for an exciting brand personality, based on online associations, 18.2%, with a SD of 19.7%. All brands that scored above the M+SD value were regarded as highly associated with the personality. In case this association was similar to the overall personality displayed on Twitter, a fit is found.
3.2.4 Control variables
Control variables are used to eliminate alternative explanations for the stated hypotheses. The control variables which are taken into account are the total number of brand-initiated tweets within the time period of three weeks, the total number of followers, the total number of favorites by the brand, the number of lists the brand is subscribed to, the anthropomorphism of the brand’s Twitter profile and whether or not a tweet contained a picture.
The number of brand-initiated tweets, followers, favorites and lists were reported on a continuous and numerical scale. A list is a group of Twitter users, which one can create or subscribe to. The list shows tweets for users that are in the list, but it does not have any interactive features (Using Twitter Lists, 2014). Anthropomorphism of the brand’s profile and a picture as part of the content were coded into dichotomous values, ‘1’ indicating the
3.3 Data analysis
Three preliminary analyses were conducted before testing the hypotheses. These analyses were intercoder-reliability (see section 3.4), checking the brand characteristics and conducting a Pearson correlation matrix to check for correlations between the control variables.
First, the mean PMI scores were calculated based on the findings on Google. According to these findings, the mean and standard deviation per brand personality were calculated using Excel (values varied from 0 to 1). After this, a simple analysis was conducted to find out whether brands were highly associated with certain brand personality dimensions. As stated, a brand is highly associated with one of the brand personality dimensions when it has a PMI score similar to or above M + SD. With the remaining brands further analyses were conducted to find whether there is a relationship between fit and consumer participation.
Hypothesis testing was conducted by using univariate ANOVA tests. In the tests for the first two hypotheses, planned contrasts were applied to test whether certain brand personalities on Twitter performed better or worse than others in the sample did (excitement and competence respectively). For the first hypothesis the individual elements of consumer participation (retweets, favorites and responses) were tested for the excitement condition, by applying planned contrasts to find out whether the means of the different brand personalities were significantly different. The same tests were conducted for the second hypothesis, where the contrasts were changed to compare the mean values for brand personality competence against the others. The third hypothesis was also tested by conducting a univariate ANOVA test. The independent variable was changed from ‘Brand Personality’ to ‘Fit’ to find out whether the fit condition had an influence on the level of consumer participation.
3.4 Second coder
A second independent coder was asked to code 10% of the collected tweets, to check reliability of the coding scheme. 76 tweets were randomly assigned to the second coder. The coder had to pick one brand personality per tweet (in some cases Tweets including a picture) and should select the best possible answer. Before conducting the coding, a short introduction about brand personality and its concepts was given. See section 4.1.1 for the results and intercoder-reliability.
Chapter 4 - RESULTS
4.1 Preliminary testsBefore testing the hypotheses, preliminary tests were conducted. Firstly, the intercoder-reliability was calculated. Secondly, brand characteristics were summarized. The last step contained creating a correlation matrix.
4.1.1 Intercoder-reliability
As the coding of both coders could be either similar or different from each other, a percentage is sufficient to depict the intercoder reliability. From the 76 tweets that the second coder has coded, 8 tweets differed from the initial coding conducted by the first coder, leading to an accuracy result of 89.5%. Research on the assessment of intercoder reliability (Lombard, Snyder-Duch & Bracken, 2002) states that values above 90% are assumed to be acceptable in all situations, values between 80-90% are acceptable in most situations. This implies that the coding is reliable and the analysis can be trusted.
4.1.2 Brand characteristics
The analysis of 27 brands led to 722 tweets within a time span of 23 days. However, not every company was active on Twitter with the same frequency. Brands that did not post any content during the time period were removed from the data set. Table 4 gives an overview.
Brand Tweets within period Avg # of RT Avg # favorites Avg # responses Avg # of tweets/ day Percentage prevalent personality Prevalent brand personality IRN-BRU 6 65 81 8 0.26 67% Excitement Volvic 0 0 0 0 0 - HARIBO 11 41 26 3 0.48 91% Excitement Whiskas 11 20 34 2 0.48 55% Competence Pepsi MAX 0 0 0 0 0 - Chicago Town 41 207 39 24 1.78 76% Excitement Ginsters 45 25 6 7 1.96 51% Ruggedness Tetley 26 27 32 10 1.13 42% Excitement Capri Sun 0 0 0 0 0 - Philadelp hia 9 197 649 24 0.39 78% Competence
Birds Eye 5 0,4 0,8 0,4 0.2 60% Competence
Heinz Ketchup 11 14 21 3 0.26 64% Excitement Craveldal e 18 2 2 0,6 0.78 59% Excitement Old El Paso 35 4 7 1 1.52 43% Excitement Mr Kipling 27 8 8 9 1.17 48% Excitement PG Tips 26 10 16 3 1.13 46% Excitement Kenco 4 1 2 1 0.17 75% Competence Pedigree 7 50 81 3 0.30 57% Sincerity Activia 0 0 0 0 0 - McVities 30 2 3 1 1.30 86% Sincerity Fanta 0 0 0 0 0 - Snickers 57 44 111 6 2.48 34% Excitement Warburto ns 276 9 13 2 12 51% Excitement Anchor 27 70 9 3 1.17 59% Excitement Extra Gum 22 1 7 1 0.96 82% Sincerity Young’s 23 3 1 0,39 1 55% Excitement Aunt Bessies 17 1 2 2 0.74 35% Sincerity/ex citement
Warburtons launched a countrywide campaign with Sylvester Stallone on April 11. This led to increased traffic on their Twitter page with many retweets, responses and conversations with consumers, while other brands just posted 10 tweets within the period of analysis. However, it is not expected that this will influence the outcomes. If the tweets are in line with the brand personality according to the found brand associations, then an increase in consumer participation is expected. Three brands did not update their statuses and therefore did not post any tweet within the data collection period. Therefore, these brands are eliminated from the analysis.
Excitement Sophistication Sincerity Ruggedness Competence
% used 65% 0% 13% 4% 17%
Avg # RT 33 0 18 25 55
Avg # fav 27 0 31 6 171
Avg # resp 5 0 2 7 7
Total CP* 65 0 51 38 233
Table 5. Overview of outcomes per brand personality. *Total CP stands for consumer
participation and is the sum of the three cells above.
Table 5 shows the average outcomes per brand personality. The percentages show the relative times a brand personality was predominantly used for a brand on Twitter. It indicates that competence leads to the highest level of consumer participation in the first case. However, additional analysis is necessary to draw conclusions.
4.1.3 Correlation matrix
Scatterplots were used to inspect the distribution of the control variables, to check whether a Pearson correlation was needed to check for correlations between the control variables.
The scatterplots showed a very small correlation between the number of followers and the total number of tweets and the number of favorites and the total number of tweets.
Therefore, a Pearson correlation was conducted to test whether there existed significant correlations between the control variables. The table shows the Pearson correlation matrix for all control variables.
(1) (2) (3)2 (4) (5) (6) (1) Total tweets Correlation Significance (2) Followers Correlation Significance -0.099 0.008 (3) Favorites Correlation Significance 0.674 0.000 0.008 0.828 (4) Anthropomorphism profile Correlation Significance 0.512 0.000 0.245 0.000 0.192 0.000 (5) Lists Correlation Significance 0.084 0.024 -0.225 0.000 -0.151 0.000 -0.456 0.000 (6) Picture Correlation Significance -0.123 0.001 0.227 0.000 -0.156 0.000 -0.116 0.002 0.129 0.001
Table 6. Correlation matrix, displaying the Pearson correlation and the significance levels per
case.
The relationships between all control variables used for the study were investigated using Pearson product-moment correlation coefficient. N = 722 for all cases.
Values between (-)0.50 and (-)1.00 are assumed to indicate a strong correlation (Pallant, 2005). According to the scatterplots, there are small correlations between the total number of tweets and the number of followers. As can be seen in table 5, this relationship is
significant at p<.05. However, the value of r is even below the value of reporting a small correlation, so a relationship between the two independent variables should not be assumed. The second scatterplot that showed some correlation was between the number of favorites and the number of followers. However, since p=.828 no correlation should be assumed.
4.2 Hypothesis testing
Hypothesis testing was done in several steps, as displayed in chapter 4. Each step contained testing a set of hypotheses, as presented below. The overall means and standard deviations per brand personality are listed in table 7.
Excitement Sophistication Sincerity Ruggedness Competence
Retweets M SD 44.471 182.977 37.667 50.930 7.800 32.994 30.216 82.686 21.447 98.082 Favorites M SD 28.926 99.313 141.333 208.959 16.880 85.229 33.000 90.778 41.406 173.997 Responses M SD 6.441 16.426 9.667 11.112 2.048 4.444 5.541 18.413 4.430 15.136 Total CP M SD 79.778 252.561 18.667 262.982 26.687 120.856 68.518 164.224 66.518 270.872
Table 7. Summary of the mean and standard deviations of the dependent variables across the
different conditions (displayed brand personality dimensions).
4.2.1 The main effect of excitement on consumer participation
The first set of hypotheses was tested according to a univariate ANOVA test. At first, the total level of consumer participation was tested; thereafter separate univariate ANOVA tests were run for the different levels of engagement (i.e. retweets, favorites and responses to brand-initiated tweets). The table below provides an overview of the results from the first conducted test, a univariate ANOVA for the different levels of total consumer participation.
Table 8 provides an overview of the most important values of the conducted univariate ANOVA tests for each of the three levels of engagement.
