The following study investigates the influence of traditional design stimuli, applied to a brand post, on the consumer's engagement rate on Instagram.
Consumer engagement thereby represents the effectiveness of a brand post and is defined by the ratio of the number of likes
of a brand post and the number of followers of the brand. Aiming at analyzing the effectiveness of traditional design stimuli on Instagram, the author gathers 450 Instagram brand posts from five different product categories which are subsequently
assessed and coded.
The researcher then conducts a regression analysis as this allows to evaluate the influence of the traditional visual design stimuli on the consumer's engagement rate. Whereas novel & cognitive demanding stimuli are not found to influence the engagement rate for a brand post, certain physically intensive & prominent stimuli as well as some affective & emotional stimuli have a significant influence.
The present study further investigates the moderating effect of brand knowledge on the magnitude of the stimuli's influence on consumer engagement rate. The results indicate that brand knowledge has a moderating effect on certain stimuli. For all other stimuli, the influence on the engagement rate does not change for different levels of brand knowledge.
The results further show that design stimuli applied in brand posts on Instagram differ in their impact on the engagement rate,
depending on the product category shown in the brand post. These findings can be used by managers to exploit the benefits of social media marketing on Instagram.
Table of Contents
List of Figures
List of Tables
List of Abbreviations
List of Symbols
List of Appendices
1 Introduction
2 Theoretical Background and Literature Review
2.1 Instagram as Social Media Communication Medium
2.2 Framework of Information Processing from Advertisements
2.3 Enhancing Ad Processing with Traditional Design Stimuli
2.3.1 Enhancing Motivation of Ad Processing
2.3.2 Enhancing Opportunity and Ability of Ad Processing
2.4 Consumer Behavior in the Context of Social Media
3 Conceptual Model and Developoment of Hypotheses
3.1 Conceptual Model
3.2 Effectiveness of Design Stimuli
3.2.1 Effectiveness of Physically Intensive & Prominent Stimuli
3.2.2 Effectiveness of Novel & Cognitive Stimuli
3.2.3 Effectiveness of Affective & Emotional Stimuli
3.3 Moderating Influence of Brand Knowledge
4 Research Design
4.1 Operationalization of Variables
4.2 Data Collection and Sample Characteristics
4.3 Methodology
5 Data Analysis and Results
5.1 Effectiveness of Stimuli
5.2 Differentiated View on Product Categories
5.3 Moderating Effect of Brand Knowledge
6 Summary and Concluding Aspects
6.1 Discussion of Results
6.2 Managerial Implications
6.3 Limitations and Future Research
References
Appendix
Executive Summary
As social media campaigns have become a popular and promising marketing instrument, marketers are highly interested in creating effective brand posts to exploit this medium’s brand building potential. This refers to increasing brand awareness and loyalty, fostering direct interactions with the consumer and triggering purchase intentions. Due to the challenges that evolved through new media, such as information overload and, as a result, divided consumer attention towards marketing messages, the need of effective brand posts becomes even more important. A vast amount of literature has investigated design stimuli for classic communication mediums regarding the attention to an ad or the attention to a brand. The investigated traditional stimuli can be roughly divided into physically intensive & prominent stimuli, novel & cognitive demanding stimuli, and affective & emotional stimuli. However, little is known about their influence on brand post effectiveness in social media. Thus, the following study aims at closing this gap by investigating the influence of those traditional design stimuli, applied to a brand post, on the consumer’s engagement rate on Instagram. Consumer engagement thereby represents the effectiveness of a brand post and is defined by the ratio of the number of likes of a brand post and the number of followers of the brand. Aiming at analyzing the effectiveness of traditional design stimuli on Instagram, the author gathers 450 Instagram brand posts from five different product categories which are subsequently assessed and coded. The researcher then conducts a regression analysis as this allows to evaluate the influence of the traditional visual design stimuli on the consumer’s engagement rate. Whereas novel & cognitive demanding stimuli are not found to influence the engagement rate for a brand post, certain physically intensive & prominent stimuli as well as some affective & emotional stimuli have a significant influence. The present study further investigates the moderating effect of brand knowledge on the magnitude of the stimuli’s influence on consumer engagement rate. The results indicate that brand knowledge has a moderating effect on certain stimuli. For all other stimuli, the influence on the engagement rate does not change for different levels of brand knowledge. The results further show that design stimuli applied in brand posts on Instagram differ in their impact on the engagement rate, depending on the product category shown in the brand post. These findings can be used by managers to exploit the benefits of social media marketing on Instagram.
List of Figures
Figure 1: Brand Post on Instagram
Figure 2: Ad Processing Framework
Figure 3: Conceptual Model
Figure 4: Interaction Effect Brand Knowledge and Iconic Buildings
List of Tables
Table 1: Design Elements Increasing the Motivation of Ad Processing
Table 2: Literature Overview and Research Gap
Table 3: Operationalization of Variables
Table 4: Average Number of Likes, Brand Fans, Engagement Rate [in%]
Table 5: Relative Frequency of Stimuli in Brand Posts [in %]
Table 6: Coefficients of Regression among all Product Categories
Table 7: Results Hypotheses without Moderation
Table 8: Significant Coefficients Regression for Different Product Categories
Table 9: Coefficients of Regression in Moderation Model among Product Categories
Table 10: Results Hypotheses for Moderation-
List of Abbreviations
Abbildung in dieser Leseprobe nicht enthalten
List of Symbols
Abbildung in dieser Leseprobe nicht enthalten
List of Appendices
Appendix A: Brand Post Instagram
Appendix B: Operationalization of Variables
Appendix C: Descriptive Overview
Appendix D: Initial Regression Change of R², F-statistic and Coefficients
Appendix E: First Regression Scatterplot & Partial Plots
Appendix F: Correlation IV and DV Engagement Rate
Appendix G: First Regression R² and F-statistic
Appendix H: First Regression Expected Value of Error Term
Appendix I: First Regression Histogram, P-P Plot and KS- test
Appendix J: Second Regression Histogram, P-P Plot and KS-Test
Appendix K: Second Regression, Scatterplot Standardized Predicted Value and Studentized Residual, Original Data Plots, Partial Regression Plots
Appendix L: Second Regression Chi-Square-Test
Appendix M: Second Regression Correlation Table
Appendix N: Alternating Exclusion Face, Sexiness, Celebrity Endorser
Appendix O: Final Regression Assumptions
Appendix P: Final Regression Heteroscedasticity
Appendix Q: Values for Outlier Test Mean +/- 4*Std. Deviation
Appendix R: Boxplot Potential Outlier
Appendix S: Final Regression R²
Appendix T: Final Regression F-statistic
Appendix U: Accessories Regression Model Fit and Assumptions
Appendix V: Personal Care Regression Model Fit and Assumptions
Appendix W: Fashion Wear Regression Model Fit and Assumptions
Appendix X: Food Regression Model Fit and Assumptions
Appendix Y: Alcoholic Drinks Regression Model Fit and Assumptions
Appendix Z: Regression Checking Linearity Moderator Brand Knowledge
Appendix AA: Regression checking R² Change for Moderation
Appendix BB: Moderation Regression Assumptions Including Interaction
Appendix CC: Interaction Brand Knowledge and Celebrity Endorser Visualization
Appendix DD: Interaction Brand Knowledge and Camera FPV Visualization
Appendix EE: Interaction Brand Knowledge and Face Visualization
Appendix FF: Interaction Brand Knowledge and Iconic Buildings Visualization
Appendix GG: Pictures without Products but with Iconic Buildings and Nature
Appendix HH: Camera Perspective FPV Alcoholic Drinks
Appendix II: Kapten and Son Facebook vs. Instagram Post
1 Introduction
Marketers have a broad portfolio of traditional well researched design stimuli at their disposal to create effective traditional print or outdoor communication campaigns (Batra and Keller 2016, p. 122; MacInnis, Moorman, and Jaworski 1991; Rossiter and Percy 1985). However, for the creation of marketing campaigns on social media, marketers cannot draw on well-established experiences regarding effective design stimuli as social media is a relatively new communication channel (Zhang and Mao 2016, p. 155). Nevertheless, social media marketing is an important and valuable marketing approach since it provides new opportunities to directly engage with the consumer, build the brand and eventually foster sales (Gensler et al. 2013, p. 246; Kumar et al. 2016, p. 7; Lamberton and Stephen 2016, p. 159; Muniz and O'Guinn 2001). Consequently, companies strive to complement traditional campaigns with effective marketing strategies on social media networks (Batra and Keller 2016, p. 122; De Vries, Gensler, and Leeflang 2017, p. 1; Kaplan and Haenlein 2010, p. 59; Kumar et al. 2016; Lamberton and Stephen 2016, p. 164). As empirical research has shown, companies have started to shift their marketing budgets to social media channels to exploit the above-mentioned opportunities. This development implicates that social media marketing has become a popular marketing instrument which has been adopted by various firms in different industries (Akpinar and Berger 2017; De Vries, Gensler, and Leeflang 2012; Gensler et al. 2013; Keller 2009).
One particular social network intensely used by companies is Instagram, a photo and video sharing network application (app). Its popularity is displayed in the rising number of registered advertisers on Instagram which doubled to two million from October 2016 to September 2017 (App 2017; Instagram 2017a; TechCrunch 2017). By implementing marketing strategies on Instagram, companies simultaneously try to take advantage of the fact that especially the target group of young people aged between 14 and 29 are intensely active on this social network (Seven One Media 2017). The number of active users on Instagram is growing faster than ever and climbed up to 800 million in September 2017 (GfK Media 2017; Instagram 2017b; Meedia 2017; Seven One Media 2017). Additionally, Instagram shows a high engagement rate of consumers (Track Maven 2016) and has found to be a source of inspiration for users regarding new products (Instagram 2018b; Kobilke 2017, pp. 10–14). Due to this inspiration induced by a brand post, 75% of Instagram users state that they acted on the respective post, e.g., liking or commenting it (Brecht 2018; Instagram 2017c). Consequently, by creating these brand posts, companies strive to elicit reactions from consumers and get in contact with them (De Vries, Gensler, and Leeflang 2012). However, it can be observed that some posts are earning a lot of likes and comments, while others are almost being uncommented. This indicates that the understanding of how to effectively design marketing messages on social media is still limited. In the case of Instagram, the visual experience is assumed to be an important factor to evoke many likes and comments (Digitalwaves 2017). Thus, the design of the picture shown in a brand post seems to be critical to arouse the consumers interest and to make the consumer engage with the post. Therefore, it is critical to understand which components of a picture lead to an engagement of consumers with a brand post. Traditional advertising literature states that physically intensive & prominent stimuli, novel & cognitive demanding stimuli, and affective & emotional stimuli can be used to design effective ads (MacInnis, Moorman, and Jaworski 1991). It is assumed that these stimuli are also applicable in the social media environment. Hence, this paper aims to empirically investigate the effect of traditional design stimuli used on a picture in brand posts on the consumer engagement rate on Instagram . By addressing this question, this work contributes to advertising literature in the context of social media. While traditional advertising literature conducts research applying different stimuli relating to attention to ad or attention to brand, little is known about the effect of traditional design cues on consumer engagement on Instagram (Janiszewski 1998; MacInnis, Moorman, and Jaworski 1991; Zhang, Wedel, and Pieters 2009, p. 670). In summary, the challenges of a firm’s post are firstly to activate the consumers attention and secondly to motivate the user to interact with the picture (De Vries, Gensler, and Leeflang 2012, p. 84).
To address the research question properly, this paper deals with findings of effective print advertising literature as well as consumer engagement in the social media context. Additionally, Instagram and its mechanisms will be presented. Afterwards, the hypothesis and the development of the conceptual framework will follow. The study design and the analysis are described. Finally, the results are discussed and implications as well as limitations and future research are stated.
2 Theoretical Background and Literature Review
To investigate the effect of different design stimuli used within an Instagram brand post, it clearly is important to understand the social network application Instagram and its mechanism. Therefore, a brief introduction to Instagram will follow. Moreover, classical advertising processing frameworks and design stimuli which are known to increase the attention to ad and brand will be defined. Subsequently, consumer engagement within the social media environment will be defined.
2.1 Instagram as Social Media Communication Medium
Instagram was launched in October 2010 as a mobile social network application and acquired one million users by the end of the same year (Instagram 2010). Today Instagram is one of the leading social networks and counts 800 million active users including two million brand accounts (Statista 2017; TechCrunch 2017). Thus, users are either consumers or firms which represent their brands on Instagram. The name “Instagram” is a word blend of the words “instant camera” and “telegram” (Lang 2014). It therefore reflects the purpose and function of this app which is the sharing of visual content from a mobile device. As a social network application it allows every user to create a personal account, to edit self-created visual content such as pictures and videos, and to share it with other users (Kaplan and Haenlein 2010, p. 63). Hence, Instagram emphasizes the visual experience of the users. Even though different product types and topics are present on Instagram, the most successful topics are beauty, fashion, sports and food (Reiz 2017).
To understand Instagram’s functionality, the main features will be explained next. As for most social network applications, the profile is also the core element of Instagram (Trusov, Bucklin, and Pauwels 2009, p. 92). Every consumer or company can create and share content and change account information on their own Instagram profile. Posts that are shared from the own account will be visible on the profile later. With an active account, one can add other users such as friends, acquaintances, unknown users or companies and brands to his online social network. Through this action, the user allows the app to integrate the posts from the friend’s, acquaintances’, personally unknown users’, or brand’s account in his own newsfeed. From that point on, one can potentially see all content which is being posted from the other accounts. This process is one of the main mechanism of the app as it connects the users to each other and enables the exchange of and the interaction with the shared visual content. A network is formed. This is basically providing the definition of the term “social media network” (Kaplan and Haenlein 2010, pp. 63–64). As users can connect with every Instagram profile, consumers can also directly get in touch with brands and companies through their brand accounts. Thus, Instagram also enables the creation of online brand communities, which can be used to foster consumer brand relationships (Kumar et al. 2016, pp. 7–8; Muniz and O'Guinn 2001, p. 412; Wirtz et al. 2013). The next important element of Instagram is the personalized newsfeed. It is a never-ending sequence of pictures and videos which are shared by the users’ network. The posts do not strictly appear in a chronological order. It is stated the Instagram algorithm considers e.g., which posts the user interacted with the most in the past or which posts are liked most by his network (here and in the following, Kobilke 2017, p. 38). Thus, the posts are ranked by time and probable relevancy for the user. In addition to regular (brand) posts, the newsfeed includes paid ads which appear based on the user’s interests (Instagram 2018e; here and in the following, Kobilke 2017). These ads look very similar to regular posts but are marked with the supplement “sponsored”. Contrary to a regular post, paid ads will not be visible on the brand’s profile. Another feature are Instagram stories. They are snapshots in form of photos or videos and are visible for 24 hours. Instagram live can be used to record and broadcast a 60 second live video.
Companies can benefit by actively applying the above-mentioned features on Instagram as their usage provides advantages that social media marketing has in general. These are opportunities to directly engage with the consumer, build the brand and eventually foster sales (Gensler et al. 2013, p. 246; Kumar et al. 2016, p. 7, 2016, p. 21; Lamberton and Stephen 2016, p. 159; Muniz and O'Guinn 2001). The fact that Instagram is one of the leading social networks and that its growth is faster than ever seems to further support the relevance and impact of this medium (Instagram 2017b; Meedia 2017). Hence, the reach of a campaign and the brand awareness could be increased using Instagram. Furthermore, most of Instagram’s users are aged between 14 and 29 and therefore constitute a young target group with high economic potential (here and in the following, GfK Media 2017; GfK Media and Communication Research 2017; Seven One Media 2017). Companies can reach them via this channel while their attention to other communication channels decreases. Against this background, targeting can be conducted more precisely by using Instagram as the characteristics of the relatively homogeneous target group regarding age are rather similar. Thus, the specifics of market segment could be considered in the marketing strategy. In addition, 80% of users are following at least one brand on Instagram (App 2017). Instagram’s users therefore seem to have a high affinity for brands which is a favorable environment for new marketing activities. Moreover, Instagram’s users seems to engage relatively well with the posted content (TrackMaven 2016). Instagram’s relative strong impact on users seems to be additionally supported by the fact that 75% of Instagram users state that they took action because they were inspired by a brand post on Instagram (Instagram 2017c; Kobilke 2017, p. 12). 60% are learning about new products on Instagram (Instagram 2018b).
Taking the former into account, it seems reasonable that marketers plan on launching an Instagram campaign and using firm-generated-content (FGC) to get in contact with their consumers. Against this background, it seems advantageous that the brand posts of the campaign are effective and benefit the brand to eventually enhance the company’s performance (Bruhn 2010, p. 506; Kumar et al. 2016, p. 21; Percy and Rossiter 1992, p. 263; Pieters and Wedel 2007, p. 224). However, the effectiveness of a brand post as part of the campaign is influenced by a variety of determinants. As suggested by advertising literature, differences in effectiveness occur especially due to: (a) the involvement of the receiver, (b) the receiver’s knowledge, (c) the used modality of influencing design elements of the marketing-message, and (d) the number of repetitions (Bruhn 2010, pp. 506–522; Kroeber-Riel and Esch 2015, p. 213; MacInnis and Jaworski 1989; MacInnis, Moorman, and Jaworski 1991; Zielske 1959).
For Instagram, the influencing determinants are assumed to be as follows: (a) The concept of involvement is very complex and can be defined with regard to e.g., the product category, the brand or related to personal (cognitive or affective) or situational determinants (Kapferer and Laurent 1985, p. 52; Park and Young 1986, pp. 11–12; Petty and Cacioppo 1986; Vakratsas and Ambler 1999, pp. 32-34; Vaughn 1980; Zaichkowski 1985). On the one hand, involvement could be defined regarding the product type which is advertised. Classical literature and researchers such as Rossiter and Percy (1985) for instance claim that the consumer probably has a lower product involvement for body soap than for a car (Rossiter and Percy 1985, pp. 514–515). This holds if product involvement is operationalized with the perceived risk of the product purchase (Percy and Rossiter 1992, p. 267). As the financial risk of a soap purchase is lower than that of a car purchase, involvement for the soap is lower as the potentially wrong decision “buying the wrong product” seems not that detrimental. On the other hand, involvement can be defined regarding the attention given to the ad material due to personal relevance or importance (Park and Young 1986, pp. 11–12). In the case of Instagram, the situational attention or involvement may be rather low, since consumers often use social media while doing other things simultaneously, for instance while watching TV, thus their attention is shared (Batra and Keller 2016, p. 122). This phenomenon is also called second streaming (Nielsen 2017, pp. 20–22).
(b) The receiver’s knowledge can be interpreted as brand knowledge (MacInnis and Jaworski 1989, p. 7; MacInnis, Moorman, and Jaworski 1991, p. 43). It is defined as the storage of characterizing brand-related information in the consumer’s memory (Keller 2003, p. 596). Brand knowledge refers to all thoughts, emotions, perceptions, images and experiences that are associated with the brand (Keller 2009, p. 143). It is also closely connected to the concept of brand familiarity (Campbell and Keller 2003, p. 293). The higher the familiarity the more information in the form of knowledge is already present in the consumer’s mind which can be used for evaluating the ad (Keller 1993, pp. 4–8). Consequently, it is assumed that consumers on Instagram who are confronted with posts from well-known brands, have rather high brand knowledge while the opposite is expected for less known brands.
(c) Furthermore, the used modalities of design elements are suggested to influence the ad’s effectiveness (MacInnis, Moorman, and Jaworski 1991). However, the effects of different visual design elements on ad effectiveness in the Instagram environment have not been investigated yet and therefore provide the topic of this research. De Vries, Gensler, and Leeflang (2012) conducted research on the effectiveness of brand post characteristics on Facebook (De Vries, Gensler, and Leeflang 2012; Pletikosa Cvijikj and Michahelles 2013). As Instagram is a video and photo sharing application, visual content seems more relevant than text. Therefore, the effectiveness of certain visual stimuli is subject of this work.
(d) The effectiveness of an ad is additionally influenced by the number of ad repetitions (Campbell and Keller 2003; Zielske 1959, p. 242). Despite its importance regarding the ad’s effectiveness, the repetition is not further considered. Thus, this paper investigates the effects of different design elements used on a picture in a brand post on the consumer’s behavior in a condition with rather low situational involvement and different levels of brand knowledge.
Aiming at creating an effective campaign on Instagram the marketer should consider all Instagram features, such as live-videos, stories and brand posts, as they differ in their durability and retrievability and thus in their effectiveness. Orchestrating these different features might evoke the most favorable results. However, stories, live videos, paid ads and posted videos from a brand account are excluded from present research as this is beyond the scope of this work. Instead, it specifically focuses on brand posts shared from a brand account and the extent of reactions it evokes. Consequently, this paper serves as a guideline to effectively design brand posts and represents the starting point for launching an Instagram campaign (Appendix A).
A brand post consists of the following components (figure 1): the profile’s name, sometimes an additional information such as the location, the rectangular area containing the visual component and a field often containing text and keywords in form of so-called hashtags. Those hashtags ideally tag and describe the post with the topics visualized in the picture. Later these hashtags will be considered by Instagram and function as keywords when answering a search request. Interactions regarding a post on Instagram can occur in different ways. Consumers can e.g., publicly like and comment on the picture, privately save it to their own collection or send the post via the Instagram chat directly to other users.
Figure 1: Brand Post on Instagram
Abbildung in dieser Leseprobe nicht enthalten
Source: Instagram (2017) Desktop Browser.
Instagram itself emphasizes the benefits of presenting a brand visually and recommends visual story telling about a brand (Gensler et al. 2013; Instagram 2018d). Referring to the advantages that brand storytelling and the interaction through liking or commenting of the firm’s generated brand post can have, it is suggested that a company assures the brand post’s ability to attract attention cause reactions (Gensler et al. 2013; Kumar et al. 2016, p. 9). To answer the question how to enhance the brand post’s respectively an ad’s effectiveness in raising attention, the next section will outline how individuals process information of ads.
2.2 Framework of Information Processing from Advertisements
Reported by Daniel Starch (1966) research on print ad effectiveness began in the 1900s (Finn 1988, p. 168; Vakratsas and Ambler 1999). One of the first advertising models was the AIDA model (Attention à Interest à Desire à Action) which is being used until today (Ambler 2000, p. 299; Keller and Lehmann 2006, p. 745; Strong 1925, p. 75; Vakratsas and Ambler 1999). During the last millennium, a plethora of literature on advertising effectiveness as well as different ad processing models evolved based upon this model (MacInnis, Moorman, and Jaworski 1991; Petty and Cacioppo 1986; Rossiter and Percy 1985; Vakratsas and Ambler 1999, 1999). These models scientifically examine different study objectives such as affective responses to ads, attitude towards the ad or attitude towards the brand (MacInnis and Jaworski 1989; Petty and Cacioppo 1986; Rossiter and Percy 1985; Vakratsas and Ambler 1999; Vaughn 1980).
One of the most cited and further developed models regarding information processing is the initially social-psychological, dual process Elaboration Likelihood Model (ELM) (Cho 1999; Pasadeos, Phelps, and Edison 2008, p. 789; Petty and Cacioppo 1986; Petty, Cacioppo, and Schuhmann 1983). It describes two different ways how individuals process persuasive messages, hence ads, and further states the thereupon effects on the consumer’s attitude (here and in the following, Petty and Cacioppo 1986). Attitudes can be defined as “[…] general evaluations people hold regarding themselves, other people, objects and issues. These general evaluations can be based on a variety of behavioral, affective, and cognitive processes.” (Petty and Cacioppo 1986, p. 127). Basically, the ELM states that human thinking or the attitude formation processes has two ways of processing persuasive information (Petty and Cacioppo 1986, p. 191). One way is through a superior and intellectual more complex route and the other way is an intellectual almost effortless, intuitive way of processing. So, there is a “think” and a “feel” route (Vakratsas and Ambler 1999, p. 32). Messages processed via the central route are assessed based on arguments and former beliefs, whereas the peripheral route evaluates the message based on peripheral cues such as music and color (here and in the following, Petty and Cacioppo 1986, pp. 191–192). The likelihood for central route processing, thus the effort being put in the processing, depends on a person’s level of ability and motivation. Ability is inhibited by distraction and enhanced by repetition of the message (here and in the following, Petty and Cacioppo 1986, p. 141). Motivation is the personal relevance the message has for the individual (Greenwald and Leavitt 1984; Petty and Cacioppo 1986, p. 144). If ability and motivation are high, the elaboration likelihood is rather high and the information processing via the central route will occur (here and in the following, Cho 1999, p. 34; Petty and Cacioppo 1986). Information processing via the central route is requiring more cognitive resources and is rather complex, as the subsequent change or confirmation of attitude of this evaluation process is based on (the quality of) arguments. Additionally, the changes in attitude resulting from the central route are strong and permanent. Controversy, missing motivation or ability thus low elaboration likelihood, leads to processing via the peripheral route. In this case elaboration is performed based on intuitive cues and superficialities such as music or visuals. The change in attitude might not follow or is rather weak.
Figure 2: Ad Processing Framework
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own illustration adapted from MacInnis and Jaworski (1989) and Kroeber-Riel and Esch (2015).
MacInnis and Jaworski (1989) present a model outlining the information processing from advertisements which is based on other persuasion or attitude formation modes such as the ELM, brand processing by Mitchell (1980) and the four level-audience involvement by Greenwald and Leavitt (1984) (Greenwald and Leavitt 1984; MacInnis and Jaworski 1989, pp. 15–16; Vakratsas and Ambler 1999, p. 32). It is also one of the most cited works regarding information processing (Pasadeos, Phelps, and Edison 2008, p. 791). MacInnis’ and Jaworski’s integrative framework consists out of several phases which build up on each other (Figure 2, Box Advertising Focus). It discusses the motivation, ability and opportunity of the consumer, the processing of information as well as the consequences such as final brand attitude (here and in the following, MacInnis and Jaworski 1989). Due to this successive organization of effects, the model is referred to as hierarchical model (Vakratsas and Ambler 1999, p. 32).
The framework of information processing, respectively the attitude formation procedure, starts with the needs of the consumer as illustrated in figure 2 (here and in the following, MacInnis and Jaworski 1989, pp. 2–15). The authors state that even though these needs are classified differently by various researchers, they agree that needs enhance the motivation to process the brand information presented in the ad. MacInnis and Jaworski (1989) distinguish utilitarian and expressive needs. Utilitarian needs are satisfied when the product eliminates or prevents problems whereas expressive needs are served if the product provides social or aesthetic value (MacInnis and Jaworski 1989, p. 2). The utilitarian needs definition is in line with McGuire (1976), Park and Young (1986), and Rossiter and Percy (1985) (McGuire 1976, p.315; Park and Young 1986, p. 12; Rossiter and Percy 1985, pp. 514–515). Whereas the definition of utilitarian needs is easily accessible, the definition of expressive needs is ambiguous. On the one hand, expressive needs describe the need to convey the person’s self-image, emotions, or role position to the external world respectively towards group members (Park and Young 1986, p. 12). On the other hand, they indicate the aspiration to consume products for their mental or sensory stimulation (here and in the following MacInnis and Jaworski 1989, p. 3). Both types of needs either arise from the consumer himself or may be triggered by certain elements of the ad (Rossiter and Percy 1985, p. 512). Such an element could simply be the product category which may stimulate the kind of need presented in the ad (Rossiter and Percy 1985, p. 512; Vaughn 1980). Consequently, MacInnis and Jaworski (1998) state that utilitarian (expressive) advertising appeals thereby stimulate the corresponding utilitarian (expressive) needs of the consumer. Thus, the appeal used in the ad links the brand to those needs (Rossiter and Percy 1985, p. 512). Those needs directly influence the motivation to process information. The term motivation is more broadly than the term involvement, which is often used in other models (here and in the following, MacInnis and Jaworski 1989, p.4). MacInnis and Jaworski (1989) specify motivation as the aspiration to evaluate the brand information given in the ad. Motivation influences the relationship between ad exposure with the ads design stimuli and the processing. Eventually, motivation indirectly determines the potential change in attitude towards the ad and thereby the effectiveness of an ad. An individual engaged in a lively conversation, for instance, might not focus completely on the ad he is exposed to. Thus, he has a lower motivation to process the ad, resulting in low attention and mental capacity to process brand information (here and in the following, MacInnis and Jaworski 1989). This motivation, however, can be enhanced by certain design stimuli (MacInnis, Moorman, and Jaworski 1991). The degree of motivation is further influenced by the consumer’s ability and opportunity to process brand information. Ability thereby means the person’s competence to interpret the presented information. Lack of opportunity refers to situational factors which hinder processing such as lack of time or distraction. Both circumstances, too low or too high ability could limit processing motivation. Thus, all three personal or situational circumstances “MAO = Motivation – Ability – Opportunity” influence the processing of the brand information depicted in the ad.
Within the actual processing phase, attention and processing capacity determine the attitude formation (MacInnis and Jaworski 1989, pp. 4–6). Attention is defined as “[…] general distribution of mental activity to the tasks being performed by the individual” and determines what and how long something receives the individual’s focus (MacInnis and Jaworski 1989, p. 5). Next to attention, the processing capacity, which is the amount of working memory directed to stimuli, is the second factor influencing the processing procedure. Depending on the intensity of attention and mental capacity, the authors define six different levels of brand processing (MacInnis and Jaworski 1989, p. 4). These differences of the levels are based upon the intensity of insight about the brand (MacInnis and Jaworski 1989, p. 5). The evaluation of brand information results in emotional and/or cognitive responses (here and in the following, MacInnis and Jaworski 1989). Emotional responses are feelings activated by the ad. Cognitive responses are thoughts which might be judgmental. The authors distinguish the responses further and link these various types of responses to certain levels of processing and explain their effect on brand attitude. Thus, these emotional or cognitive responses directly influence the brand attitude formation process which results in a specific brand attitude. Based on the former, persuasive communication, can be claimed as effective, if it evokes a change or confirmation of attitude (MacKenzie, Lutz, and Belch 1986; Petty and Cacioppo 1986, p. 125; Vakratsas and Ambler 1999, p. 35).
The presented advertising processing models and their effect chains are very similar to a general model proposed by Kroeber-Riel and Esch (2015) (Kroeber-Riel and Esch 2015, pp. 251–258; Meffert, Burmann, and Kirchgeorg 2012, pp. 743–746). Whereas the ELM and hierarchy of effects models often terminate with brand attitude, Kroeber-Riel and Esch (2015) additionally explicitly include the consumer’s behavior as a succeeding step (Kroeber-Riel and Esch 2015, pp. 255–257). Consumer behavior in general is understood as the completeness of consumer’s decisions in terms of acquiring, consuming and dispositioning goods, services, experiences and ideas by decision-making units over time (Jacoby 1976, p.332). Furthermore, Kroeber-Riel and Esch (2015) state, similar to earlier studies, that there are four pathways to run through the advertising process model depending on the type of the ad appeal (emotional /hedonic or informational /utilitarian) and the level of involvement (amount of paid attention to the ad) (Kroeber-Riel and Esch 2015, pp. 255–257; Rossiter and Percy 1985). Combinations of informational and emotional ads with low or high involvement are possible. As these determinants are also integrated in traditional models by relevant authors who critically analyze strategies to create effective advertising (Rossiter and Percy 1985; Rossiter, Percy, and Donovan 1991; Vaughn 1980) the interpretation of a four-way-path-model by Kroeber-Riel and Esch (2015) is supported. The understanding of information processing in this work is therefore an extended version of the model form MacInnis and Jaworski (figure 2).
Even though research has criticized hierarchy models, they can still serve the purpose of understanding advertising effectiveness and are therefore considered suitable to serve as frame for this work (Smith, Chen, and Yang 2008; Zhang and Mao 2016, p. 156). In summary, brand attitude and consumer’s behavior are changing depending on the consumers' motivation, opportunity, and ability levels which influence the processing of information in the ad (MacInnis, Moorman, and Jaworski 1991). Motivation, ability, and opportunity levels can be enhanced by the design of the ad (MacInnis and Jaworski 1989, p. 33; MacInnis, Moorman, and Jaworski 1991, p. 33). This implicates that different ad stimuli and creative strategies can cause certain reactions (MacInnis, Moorman, and Jaworski 1991; Zhang and Mao 2016, p. 156).
2.3 Enhancing Ad Processing with Traditional Design Stimuli
The following part will outline which factors are classified by literature to be able to enhance motivation, ability and opportunity in ad processing. Based on this systematization the focus of the following chapter and thus the selection of the executional cues for the analysis is conducted. Findings from traditional marketing literature mainly regarding print advertising are considered as it seems likely that those findings are transferrable on pictures which are posted online.
2.3.1 Enhancing Motivation of Ad Processing
The level of motivation can be enhanced by using specific executional design cues in an ad which in turn influences the consumer’s attention and attitude to the ad (Kroeber-Riel and Esch 2015, pp. 262–274; MacInnis, Moorman, and Jaworski 1991, pp. 32–33; Meyers-Levy and Peracchio 1995; Petty, Cacioppo, and Schuhmann 1983, pp. 135–136; Schindler 1986). Table 1 presents ad design stimuli for traditional media which are known to increase the motivation to process ads, thus the ad’s effectiveness regarding attention to the ad. The overviews of the cited sources also consider design elements of ads which are applicable to communication messages for tv or radio spots. Since this paper focuses on an evaluation of a single picture on Instagram, only those executional cues which are applicable to a non-moving picture will be considered. The design stimuli are claimed to be effective as they rely on different social technologies which lead to an increase of activation (Berlyne 1960; Kroeber-Riel 1979; Kroeber-Riel and Gröppel-Klein 2013, pp. 80–81). They are often classified in three groups (Berlyne 1960; Bruhn 2010, p. 502; Kroeber-Riel and Gröppel-Klein 2013, p. 81; MacInnis, Moorman, and Jaworski 1991, p. 36). These are: (1) physically intensive & prominent stimuli, (2) novel & cognitive demanding stimuli, and (3) affective & emotional stimuli. These stimuli influence the strength of the ad to attract the consumers’ attention and the thereupon information processing. The cited authors additionally remark that the mentioned cues are not exhaustive and might be adapted.
When researchers started to investigate these design cues on print ad effectiveness regarding attention to ad, hence the motivation to process, studies were often only experimental. Due to the technology of eye-tracking later studies are able to conduct research more empirically which supports earlier findings (Percy and Rossiter 1983; Pieters, Warlop, and Wedel 2002, p. 777). The eye-tracking approach is applicable as consumers’ visual attention to ads can be investigated reliable by the consumer’s eye movements because the viewing direction implicates the focus of attention (Krugman et al. 1994, pp. 49–50; Rosbergen, Pieters, and Wedel 1997; Spoehr and Lehmkuhle 1982, p. 163 and p. 177).
Table 1: Design Elements Increasing the Motivation of Ad Processing
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own illustration adapted from (Bruhn 2010; Kroeber-Riel and Gröppel-Klein 2013; MacInnis, Moorman, and Jaworski 1991).
The first type of stimuli, the physically intensive & prominent stimuli, comprise ad size, pictures, picture size, coloring, and the use of celebrity endorsers. They are claimed to support the ad to stand out and increase its salience (MacInnis, Moorman, and Jaworski 1991, p. 35). Physically intensive stimuli are known to cause knee-jerk reactions, thus causing almost automatic responses or attention (Itti and Koch 2001, p. 1; Kroeber-Riel and Gröppel-Klein 2013, p. 81).
Research on print ads examined an ad’s effectiveness by manipulating the overall size of the ads as well as the size of the different ad components (Hanssens and Weitz 1980; Janiszewski 1998; Lohse 1997; Pieters and Wedel 2004; Pieters, Wedel, and Zhang 2007). Regarding the latter, one should know that a print ad exists out of the following basic components: the brand, mostly in form of the logo, a pictorial and text elements (Pieters and Wedel 2004, p. 37). Research found that the overall size of the ad positively effects the attention to the ad as this increases the ad’s salience (Finn 1988, p. 175; Hanssens and Weitz 1980, p. 305; Lohse 1997, p. 71). As well as the increase of the overall ad, an increase in surface size of ad elements is expected to lead to a higher perceptual salience and therefore increases the attention devoted to it. However, the relative bigger ad element may decrease the attention to other elements due to the consumer’s limited attentional resources (Janiszewski 1998, p. 300; Kahneman 1973, pp. 7–15; Pieters and Wedel 2004, p. 36). Hence, there might be a trade-off regarding attention among ad elements within the ad, while the level of total attention to the ad stays the same.
Contrary to this phenomenon, it was investigated if the additional attention to the relatively bigger ad element can be transferred to other ad elements and results in an incremental attention to the whole ad (here and in the following, Pieters and Wedel 2004, p. 45). Such attention transfer is possible; however, it was found that this does not hold for all ad elements. Capturing incremental attention towards the whole ad was just found to be achievable by increasing the size of the text elements as this increases the overall attention toward the ad more than it decreases the attention to the other ad elements (e.g., the pictorial or the brand) (Pieters and Wedel 2004, p. 46). Pieters and Wedel (2004) also found that the attention captured by the brand is advantageous regarding guiding, transferring endogenous attention, the consumer’s attention through the ad. When attention has been drawn to the brand, it links attention more strongly to picture and text elements as when attention was initially drawn to picture or text elements (here and in the following, Pieters and Wedel 2004, p. 48). However, the total incremental attention is lower than for increasing text size.
The component “picture” within the ad is superior compared to the other ad elements with regard to attention, elaboration and memory of the ad (Kroeber-Riel 1979, p. 247; Paivio 1971; Percy and Rossiter 1983, p. 20; Pieters, Warlop, and Wedel 2002, p. 774; Pieters and Wedel 2004, p. 47; Pieters and Wedel 2007, p. 231). Some researchers state that the increasing picture size ceteris paribus (c.p.) (when all other circumstances are held constant) could even create incremental attention to the whole ad, while other researchers agree that the picture does have a strong impact on attention, but regardless of its relative size to other ad elements (MacInnis, Moorman, and Jaworski 1991, p. 35; Pieters and Wedel 2004, p. 47). The superior effect of pictures is often explained by means of Paivio's dual-coding theory. It states that the processing of pictures generally results in a visual and verbal statement (Clark and Paivio 1991; Paivio 1971; Rossiter 1982, p. 101; Spoehr and Lehmkuhle 1982, p. 203). This is superior compared to the processing of words as they are less likely to evoke visualizations (Paivio 1971; Rossiter 1982, p.101; Spoehr and Lehmkuhle 1982, p. 203). This supports the importance and strength a picture has in raising attention and conveying information within an ad.
Next to rough design characteristics as ad size, studies investigated specific picture characteristics as they have direct effects on attention to the ad and brand (Finn 1988; Meyers-Levy and Peracchio 1995; Schindler 1986). Finn (1988) found that the color and illustration size are significantly affecting attention to ad and brand (Finn 1988, p. 175). This is in line with other research stating that color and size support the ad’s salience, captures attention and increase the consumers motivation for processing the ad (Janiszewski 1998, p. 291; MacInnis, Moorman, and Jaworski 1991, pp. 35–36). As the influence of size was already discussed, a closer look will be taken on the use of color. In general, color is a powerful stimulus to attract attention (MacInnis, Moorman, and Jaworski 1991, p. 36; Meyers-Levy and Peracchio 1995, p. 121; Percy and Rossiter 1983, p. 20; Schindler 1986). Color in ads was investigated in relation to attention, memory and emotion (Panigyrakis and Kyrousi 2013, p. 237). In the early stages of advertising research color in ads was often noted as constraint regarding the costs. Printing colored ads in magazines was more expensive than black and white printing and moreover not that reliable in terms of colorfast (Hanssens and Weitz 1980, p. 304; Schindler 1986, p. 76). At the time, when not all ads were colored, the color and specific combinations of color enhanced the contrast to the other ads and made the colored ad stand out which results in higher attention from consumers (Janiszewski 1998, p. 291; MacInnis, Moorman, and Jaworski 1991, pp. 35–36; Schindler 1986, p. 70). More specifically, perception research indicates that vibrant colors can be used to make the details in the picture appear more prominent as they are able to highlight various color nuances and textures of the depicted product (here and in the following, Brockman and Brockmann 1991; Itti and Koch 2001; Lee et al. 2014, p. 1016; Rossiter 1982, p. 102). Such pictures seem more realistic and make it easier for the consumers to relate to the picture. Black and white imagery in contrast, leads attention to global form and shape (Lee et al. 2014, p. 1027). In addition to the strength of enhancing attention, colored ads or pictures are superior compared to black and white pictures regarding recall and recognition, thus memory of the ad (Lee et al. 2014; Wichmann, Sharpe, and Gegenfurtner 2002, p. 509). Furthermore, the use of color in the ad, compared to black and white ads, increases the probability of persuading a person with low processing motivation (Meyers-Levy and Peracchio 1995, p. 122). However, there are findings stating that when the processing of the ad requires high processing demand, black and white ads outperform colored ads regarding recall of specific product attributes and ad claim (Meyers-Levy and Peracchio 1995, p. 126). Percy and Rossiter (1983) found that the use of color compared to black and white ads positively influence the overall affect towards the advertised brand. Moreover, they state that color in ads compared to the same black and white ad can evoke specific effects upon consumers beliefs (Percy and Rossiter 1983, p. 18). They concluded that color favors an affective type of processing which influences emotional response. Hence, color evokes certain emotions in general and specific colors are also said to create specific feelings or excitement. Muted colors for example stand for coziness and relaxation (Meyers-Levy and Peracchio 1995). Some authors even group specific color combinations and assign feelings to them e.g., dark red and brown for love (Küthe and Küthe 2002, p. 148). However, the topic of coloring is characterized by inconsistency in findings (Panigyrakis and Kyrousi 2013, p. 244).
The use of celebrity endorsers as a spokesman can enhance the attention to the ad and thus motivation to process the ad (Agrawal and Kamakura 1995, p. 56; MacInnis, Moorman, and Jaworski 1991, p. 36; Vakratsas and Ambler 1999, p. 32). A spokesmen is most advantageous for the ad’s effectiveness if it fits to the product which is being promoted (Kamins 1990, p. 9; Kamins and Gupta 1994, p. 583). An attractive celebrity increases the effectiveness of an ad and furthermore would especially work in favor for a beauty brand (Baker and Churchill 1977). The use of celebrities is prevalent in advertising and can also enhance the product recall and brand awareness (Agrawal and Kamakura 1995; Baker and Churchill 1977; Petty, Cacioppo, and Schuhmann 1983, p. 143; Rosenthal and Brito 2017, p. 382).
The second type of stimuli, novel & cognitive demanding stimuli are also claimed to increase the processing motivation of consumers regarding ads (Ang, Lee, and Leong 2007, p. 221; Berlyne 1970; MacInnis, Moorman, and Jaworski 1991). Novelty can appear in different forms and can enhance ad recall (MacInnis, Moorman, and Jaworski 1991, p. 35). Considering print ads, a new angle for taking the picture may be a novel stimulus. Research found for example that the product or person in the picture seems strong and potent when a low upward looking camera angle is used (Kraft 1987). Contrary, the object is found to be perceived as weak when the picture uses a high, downward looking angle (Kraft 1987, p. 305). However, these distinct results were not able to replicate in a later study. The high, downward looking camera angle was able to convey weakness as well as naturalness and thus presents inconclusive findings (Peracchio and Meyers-Levy 2005, p. 39). Nevertheless, the unusual use of a camera angle might influence the processing of the ad and thus the attitude following from this (MacInnis, Moorman, and Jaworski 1991, p. 36). Research also suggests that ad originality can be used as a novel stimulus and raise the attention as well as the memory of the ad with the brand (Pieters, Warlop, and Wedel 2002, p.774-777; Reinhartz and Saffert 2013). Increased levels of ad originality or creativity promote attention to the brand in ads and in a second step even raise the brand memorization (Reinhartz and Saffert 2013). However, as ad originality or ad creativity are rather broad terms, the question arises how to transfer this in specific executional cues (Pieters, Warlop, and Wedel 2002, p. 767).
Visual complexity of an ad is a stimulus addressing the consumer’s cognitive responses and is known to increase the consumers attention as well as the picture’s memory and ad’s liking (Cox and Cox 1988, p. 115; Fleming and Sheikhian 1972, p. 438; MacInnis, Moorman, and Jaworski 1991, p. 36). Berlyne (1960) for instance states that visual complexity depends on the number of distinguishable elements in the picture, the dissimilarity between elements, and the degree to which several elements are responded to as separate (vs. as a unit) (Berlyne 1960, pp. 38–39). Ads with more elaborate designs regarding patterns, contours, and objects are also more complex (Pieters, Wedel, and Batra 2010, p. 50). The use of higher complexity strives and succeeds to increase both the consumer’s attention span and attention level towards the ad (Pieters, Wedel, and Batra 2010, p. 48).
The third group are the affective & emotional stimuli. Here, the usage of schemes as well as metaphors is known to evoke associations and feelings, and therefore influences the effectiveness of advertising as these cognitive and emotional responses ideally increase processing (Kao et al. 2017, p. 474; MacInnis, Moorman, and Jaworski 1991, p. 37; McQuarrie and Mick 1999, 2003, 2003, p. 586; Toncar and Munch 2001). Decoding abilities facilitating the interpretation of schemes e.g., sexiness can be deeply rooted in the human nature and are then caused biologically (Kroeber-Riel and Esch 2015, p. 264; Zajonc 1984, p. 122). Meanings or the ability to interpret other schemes can also be shaped by social and cultural environment due to conditioning (Allen and Madden 1985, p. 301; Forceville 2017; Olson and Fazio 2001; Sweldens, van Osselaer, and Janiszewski 2010). Next to schemes, the use of metaphors constitute a way of conveying the ad’s message and to trigger ad processing (MacInnis, Moorman, and Jaworski 1991; Ward and Gaidis 1990). Even if processing ads with metaphors may take longer due to the higher requirement of mental resources, it is suggested to use them as the evaluation process can be more deeply which causes a better memorization (Ward and Gaidis 1990, p. 640). Visual types of metaphors are superior in effects compared to verbal figures (McQuarrie and Mick 2003, p. 586).
The classical scheme of childlike characteristics is triggering biological activation or reactions (Forceville 2017, p. 29; Kroeber-Riel and Esch 2015, p. 264).Childlike characteristics are depicted by features which are typical for a young face, thus a larger forehead and skull, whereas a bigger jaw and neck is typically associated with a more mature appearance (Spoehr and Lehmkuhle 1982, p. 191). Faces of any age can be used in advertising to attract attention (Bakhshi, Shamma, and Gilbert 2014; Min et al. 2017). The use of women, the shape of figures which are similar to the shape of the human body, or sex appeals in ads, are also addressing biological responses and are known to create more attention to the ad (Baker and Churchill 1977; Mittal and Lassar 2000) and is more effective in terms of recall (Dahl, Sengupta, and Vohs 2009, p. 215; Hanssens and Weitz 1980, p. 305; Kroeber-Riel and Esch 2015, pp. 369–373). However, literature also states that the consumer’s attitude towards sexy ads could be negative due to ethical objectionability (Mittal and Lassar 2000, p. 124). Yet, this effect depends on the sexual liberalism of the target audience (Mittal and Lassar 2000, p. 124).
Nature, beautiful landscapes or animals can also be subsumed under the use of schemes and metaphors and their usage thereby also causes higher attention to the ad and certain emotions (Forceville 2017; Kroeber-Riel and Gröppel-Klein 2013, p. 81; Spears and Germain 2007). Furthermore, iconic buildings which are well known can be used as schemes to attract attention and to evoke certain emotions (Kroeber-Riel and Gröppel-Klein 2013, p. 81). Emotions are able to influence beliefs about the brand as well as attitude towards the ad and brand (Batra and Ray 1986, pp. 245–246; Edell and Burke 1987, p. 430). Therefore, feelings evoked from the ad are influencing the ad’s effectiveness (Aaker, Stayman, and Hagerty 1986; Henthrone, LaTour, and Natarajan 1993). The effect of emotions on brand evaluations depends mainly on changes in brand attitude, does not depend on the product involvement and is more likely for hedonic products (Pham, Geuens, and Pelsmacker 2013, pp. 392–393). Positive and “warm” ad-evoked feelings increase ad liking and purchase intention (Aaker, Stayman, and Hagerty 1986, p. 378; Couwenberg et al. 2017, p. 356). Henthrone et al.(1993) state that fear appeals, on the other hand, can cause negative effects on attention and attitude towards the ad, if the level of fear exceeds a certain threshold and activates anxiety (Henthrone, LaTour, and Natarajan 1993, pp. 62-67). Moreover, it is suggested that humor attracts attention to ads (MacInnis, Moorman, and Jaworski 1991, p. 39; Weinberger and Gulas 1992, pp. 56–57).
2.3.2 Enhancing Opportunity and Ability of Ad Processing
The level of opportunity to process the ad is influenced by situational or ad inherent conditions (Batra and Keller 2016, p. 130). If the circumstances provide enough time to process the information and do not impede the processing, the level of opportunity is rather high (MacInnis and Jaworski 1989, p. 7). Research found that the ad’s placement or repetition can enhance attention to the ad and therefore increases the opportunity to process the ad (Finn 1988, p. 172; Hanssens and Weitz 1980, p. 296; MacInnis, Moorman, and Jaworski 1991, p. 36). Research findings for print ads suggest that the position of the ad on the right-hand side and at the front of the magazine is advantageous compared to left-hand side placement at the end of the magazine (Finn 1988, p. 172). Referring explicitly to competitive attention situations of print ads (Janiszewski 1998) states that ads surrounding the focus ad are increasing the competition for attention and thus will decrease the amount of time the consumer spends fixating and analyzing the focus ad. The surrounding ads receive some of the consumer’s attention and distract him, which causes lower memory for information in the focal area (Janiszewski 1998, p. 297).
If the consumer is repeatedly exposed to the advertising message the opportunity to process the information in the ad increases because the consumer has more chances to evaluate the information (Berlyne 1970; Campbell and Keller 2003; MacInnis, Moorman, and Jaworski 1991, p. 38; Mayer and Illmann 2000, p. 458). Thus, repetition can increase the ad’s effectiveness. This is the case, because repetition increases remembering and therefore brand awareness (Keller 1993, p. 3; Zielske 1959, p. 242). Zielske investigated repetition effects with an experiment by distributing 13 ad exposures differently over the year (here and in the following, Zielske 1959). He found that people will forget quickly, if they are not exposed to the ad continuously. Showing the ad in a four-week term resulted in relatively high brand awareness throughout the year. The maximum number of people who were reached by the ad and maximum level of brand awareness level was achievable with 13 exposures in 13 weeks. However, the duration of the peak level of awareness was relatively short due to the missing repetition throughout the year which leads to remembering (Zielske 1959, pp. 242-243). Moreover, there are wear out effects if the consumer is exposed to the message repeatedly (Berlyne 1970; Campbell and Keller 2003, pp. 292–293; Cox and Cox 1988; Vakratsas and Ambler 1999, pp. 31–32). Hence, the marginal positive effect of ad repetition diminishes with increasing number of repetitions whereby the effect is smaller or slower for emotional and complex ads than informational ads (MacInnis, Moorman, and Jaworski 1991, p. 37). The consumer allocates less attention to the ad because he is already aware of the content presented in the ad (Calder and Sternthal 1980, p. 173; Pieters, Rosbergen, and Wedel 1999, p. 424).
Ability to process information means in this context, the capacity to interpret brand information in the ad (MacInnis and Jaworski 1989, pp. 6–7). Consequently, ability can be interpreted as the level of brand knowledge (Batra and Keller 2016, p. 130; Keller 1993, pp. 2-8; 2003). In order to heighten the ability to process the brand information in the ad, the presence of brand or product category knowledge is advantageous as this provides the consumer with associations and decoding ability due to knowledge structures stored in his mind (Batra and Keller 2016, p. 130; Keller 1993; MacInnis, Moorman, and Jaworski 1991, p. 34).
This chapter presented design characteristics that are used to create an effective ad in terms of attitude towards the ad and attitude towards the brand. In general, traditional advertising literature states that an ad is effective, if it is able to attract and maintain the consumers attention and if it causes a positive attitude toward the brand (Pieters, Warlop, and Wedel 2002, p. 766). Thus, advertising literature often focuses on the consumer’s attitude.
2.4 Consumer Behavior in the Context of Social Media
After introducing Instagram, ad processing models, as well as traditional design stimuli, this part will define consumer’s behavior in the context of social media. Compared to marketing literature which deals with offline strategies and traditional executional design stimuli, recent advertising literature copes extensively with online digital communication strategies (Batra and Keller 2016; Hennig-Thurau et al. 2010; Lamberton and Stephen 2016, p. 146; Zhang and Mao 2016, p. 156). Considering the information processing framework presented in chapter 2.2, it is assumed that the basic principle of ad processing still holds true with social media. Thus, advertising can be claimed effective when the ad is able to cause the consumer to think and feel about the item in the ad, prior to acting afterwards (Batra and Keller 2016, p. 131; Zhang and Mao 2016, pp. 156–157). Because social media campaigns provide additional brand touchpoints for the consumer they can be used for different brand building purposes such as raising awareness and recall and thus to build strong brands in a modern marketing communication environment (Ashley and Tuten 2015; Keller 2009, p. 148). In addition to traditional measures of ad effectiveness, such as attitude towards the ad or brand, social media advertising applies new effectiveness measures such as numbers of likes, shares, or comments (Akpinar and Berger 2017, p. 319; De Vries, Gensler, and Leeflang 2012; Olney, Holbrook, and Batra 1991, p. 440). By applying likes and comments as effectiveness measures, the consumer’s visible and direct behavior towards the branded communication material is considered.
“New media are websites and other digital communication and information channels in which active consumers engage in behaviors that can be consumed by others both in real time and long afterwards regardless of their spatial location.” (Hennig-Thurau et al. 2010, p. 312). New media can therefore be described with the keywords: digital, pro-active consumer, visible, real-time and memory, ubiquitous and networks (Hennig-Thurau et al. 2010, p. 312). The latter term “network” thereby suggests that the consumer’s pro-active behavior is mostly occurring within social media networks (Hennig-Thurau et al. 2010, p. 312). New media research since 2010 therefore copes with topics related to social networks, user-generated-content (UGC), word-of-mouth (WoM) and virality (Batra and Keller 2016, pp. 126–127; Lamberton and Stephen 2016, p. 153). All phenomena are driven by the increasing relevance of the internet in consumers’ lives, which caused a dramatic change in the media and marketing landscape, because users become active online and engage with content (Berger and Milkman 2012; Hennig-Thurau et al. 2010; Wirtz et al. 2013).
Brodie et al. (2011) state that customer (consumer) engagement (CE) is a specific type of customer behavior and is conceptually based on customer relationship marketing and the service dominant logic (Brodie et al. 2011, p. 259; Vargo and Lusch 2008). CE is the degree to which a person connects or participates with a firm’s offerings or organizational activities e.g. a brand post in a social network (Vivek, Beatty, and Morgan 2012). This interaction can be initiated by the individual or the organization whereby the individual is either a current or potential customer (Vivek, Beatty, and Morgan 2012, p. 133). Hence, customer engagement demonstrates behavior that is beyond purchase and is driven by motivational triggers (van Doorn et al. 2010, p. 254).
Consumer motivation is therefore not only relevant in terms of information processing, it is also a critical determinant for consumer’s behavior in the new media environment (Hoffmann and Novak 2012; MacInnis, Moorman, and Jaworski 1991; Zhang and Mao 2016, p. 156; Zhu and Chen 2015). Regarding social media, Hoffman and Novak (2012) identified four main motivations justifying why people use social media. These are connecting, creating, consumption and control (4Cs) (here and in the following, Hoffmann and Novak 2012, p. 4). These findings align content-wise with studies which derived “socializing, entertainment, self-status seeking and information” as motivators (Enginkaya and Yılmaz 2014, p. 219; Heinonen 2011, pp. 359–363; Park, Kee, and Valenzuela 2009, p. 731) Thus, people are motivated to use social media to get in contact and interact with others. They share experiences with friends or just manage their own social networks (Heinonen 2011, p. 361). Within these social networks users can create (i.e. post) and consume (i.e. watch, read) content which is either consumer or firm generated (Kumar et al. 2016, p. 9). Users also retrieve product specific information or share their experiences, preferences, reviews or ratings and opinions with other individuals (Babić Rosario et al. 2016, p. 297; Heinonen 2011, p. 360; Hennig-Thurau et al. 2004, p. 39; Muniz and O'Guinn 2001). Such behavior is defined as online word-of-mouth, because the act of traditional word of mouth (WoM), thus the interpersonal act of exchanging informal information about products or services face-to-face and offline, now occurs online (Babić Rosario et al. 2016; Hennig-Thurau et al. 2004, p. 39; Westbrook 1987, p. 261). With the rise of online WoM, advice from other individuals in social networks is becoming increasingly important for consumers’ purchase decision process (Gopinath, Thomas, and Krishnamurthi 2014, p. 241; Heller Baird and Parasnis 2011, pp. 34–35; Hennig-Thurau, Wiertz, and Feldhaus 2015; Hill, Provost, and Volinsky 2006). Hence, consumers use the internet as a tool to consume and create information and even base purchase decisions upon this information (Babić Rosario et al. 2016; Iyengar, van den Bulte, and Valente 2011). Furthermore, users are able to present an ideal self-concepts of themselves in these social networks as they are able to control the settings and the content of their profile (Hoffmann and Novak 2012, p. 5). Only the content which shapes the ideal self-image is presented. “Self-articulation and self-promotion”, “becoming inspired & looking for encouragement”, or “simply entertaining oneself” are behavioral manifestations that strive to satisfy the motivation or need to be entertainment by social media (Heinonen 2011, p. 360). The four main motivations and goals are not mutually exclusive, often two goals are pursued simultaneously, i.e. “connect-consume”, “connect-create” (Hoffman, Novak, and Stein 2011, p. 29; Hoffmann and Novak 2012, pp. 21–22). While these motives are rather general, brand-related drivers and motives classify why people engage with brands online (Wirtz et al. 2013). Consumers engage with brands online because they are aiming to integrate the brand’s image into their self-identity (here and in the following, Wirtz et al. 2013, p. 230). The brand’s image, so the associations or perceived brand character traits, are aimed to spill over from the brand onto the self (Balachander and Ghose Sanjoy 2003; Keller 1993, 2003). The motivation of brand identification is therefore related with the general desire to “present oneself in the right light”. A closely connected motivation is the identification with the brand’s symbolic function (Wirtz et al. 2013, p. 230).
Against this background, it becomes clear, that there are many reasons why and how people act within social media. Appling this knowledge appropriately, companies can specifically develop strategies to address these motives and at the same time profit as they can pursue the brand building as well as financial goals (Heinonen 2011, p. 361; Wirtz et al. 2013; Zhu and Chen 2015, p. 336). Based on consumers’ motivations, social media marketing should actively facilitate the interaction among consumers, build online brand communities and should facilitate the consumer-firm relationship via social networking sites (Brodie et al. 2013, p. 107; Heinonen 2011, p. 362; Muniz and O'Guinn 2001).
Social media enables users to interact with friends professionally or simply on a social basis (Kaplan and Haenlein 2010, pp. 63–64; Trusov, Bucklin, and Pauwels 2009, p. 92). Consumers can not only become friends with other consumers, they can also connect with a brand via the brand account and, from that point on, are called brand fans. These fans can then share their excitement about the brand and are united by their shared enthusiasm for the brand (De Vries, Gensler, and Leeflang 2012, p. 84; Kozinets 1999, p. 254). An online brand community is created. Classically, a brand community is defined as “ […] a specialized, non-geographically bound community, based on a structured set of social relationships among admirers of a brand.” (Muniz and O'Guinn 2001, p. 412). Online brand communities basically follow this definition but might differ in characteristics of brand orientation, internet use, as well as funding and governance (Wirtz et al. 2013, p. 225). This means for instance, that the brand does not have to be the only focus of the online brand community, it can also be complemented by a wider shared interest (Wirtz et al. 2013, pp. 225-226).
Online brand communities on social networks can be used to foster both the interaction and relationship between the consumer and the company, as well as the provision of social benefits for the fans (Bagozzi and Dholakia 2002; McAlexander, Schouten, and Koenig 2002; Muniz and O'Guinn 2001; Wirtz et al. 2013). Within social media networks such as Facebook and Instagram consumers engage with content by liking or commenting on the firm’s brand post (McAlexander, Schouten, and Koenig 2002, p. 51; Muniz and O'Guinn 2001, p. 412). Hence, liking and commenting on a picture on Instagram or Facebook is defined as consumer engagement in the social media environment. The consumer connected with the content which was posted by the firm. His action has not necessarily a relation to purchase as he might already possess the product or might not even have the intention to buy such a product in the next time, but he likes the picture thus his behavior is beyond purchase. Additionally, his behavior is driven by motivation. This is in line with the definition in literature (Brodie et al. 2013; van Doorn et al. 2010; Vivek, Beatty, and Morgan 2012).
To summarize, consumer engagement with firm generated content in social media is e.g. a “like ” underneath a brand post and can result in higher commitment, loyalty as well as higher purchase intention and sales (Hutter et al. 2013, p. 347; Kumar et al. 2016, p. 7; Wirtz et al. 2013, p. 234). Thus, a like is a measure of ad effectiveness in social meida. It is further suggested that consumer engagement enhances customer satisfaction, and empowerment, connection, emotional bonding and trust (Brodie et al. 2013, p. 111). This shows the importance of this topic and this very work to identify which stimuli work in raising the engagement rate as a first step to reach the goals.
Table 2 gives an overview of most literature cited above and shows the research gap which is investigated in this paper.
Table 2: Literature Overview and Research Gap
Abbildung in dieser Leseprobe nicht enthalten
Source: Own illustration based on cited authors.
3 Conceptual Model and Developoment of Hypotheses
The former chapter presents the procedure of ad processing and certain design stimuli which are known to enhance ad processing. They influence the intensity of motivation, ability and opportunity of the ad evaluation process which may eventually lead to a change of attitude towards the ad and towards the brand (MacInnis, Moorman, and Jaworski 1991). Moreover, the cited papers claim that social media activities are appropriate to foster customer engagement and loyalty as well as to raise brand awareness and ultimately increase sales (Ashley and Tuten 2015; De Vries, Gensler, and Leeflang 2012; Keller 2009, p. 147; Kumar et al. 2016, p. 7). In the following, this work combines the outlined research streams from the previous chapter and hypothesizes that specific traditional visual design stimuli used within a brand post have an influence on the consumer’s engagement rate on Instagram. The proposed hypotheses will focus on stimuli which have been found to raise the consumer’s ad processing motivation.
3.1 Conceptual Model
Derived from preceding literature the conceptual model is presented in figure 3. The influence of the different design stimuli as independent variables (IV) is measured on the dependent variable consumer engagement rate (DV). The definition of consumer engagement on Instagram was conceptually derived in chapter 2.4. In this work consumer engagement is furthermore operationalized as engagement rate, indicated by the ratio of number of likes and number of followers. The model additionally incorporates a moderator brand knowledge and its effect on the magnitude of the causal influence of the design stimuli on the consumer engagement rate. The design stimuli are depicted in three groups, namely physically intensive & prominent stimuli, novel & cognitive demanding stimuli and affective & emotional stimuli. The model is completed by three control variables. Unobserved properties of product categories might lead to differences in customer engagement (De Vries, Gensler, and Leeflang 2012). Hence, this study controls for the product category by integrating different brands from different product categories. Additionally, it is being controlled for the number of days the message has been online. The longer the picture is online, the higher the possibility that someone engages with the picture. As former studies proved the influence of the post’s interactivity, this work controls for this, too (De Vries, Gensler, and Leeflang 2012). These are variables that account for certain influences that are not captured by the hypotheses. Their inclusion accounts for alternative explanations of the engagement rate, reduces the statistical noise and thus increases the statistical power of the model (Becker 2016, p. 274).
Figure 3: Conceptual Model
Abbildung in dieser Leseprobe nicht enthalten
Source: Authors own illustration.
3.2 Effectiveness of Design Stimuli
3.2.1 Effectiveness of Physically Intensive & Prominent Stimuli
One way to enhance the salience of a brand post is using physically intensive and prominent stimuli. The overview in Table 1 in chapter 2.3.1 shows that the use of pictures, the size of pictures, the size of the ad, coloring and celebrity endorsers are known to raise the attention to the ad, thus the motivation to process the ad (MacInnis, Moorman, and Jaworski 1991). Capturing attention is a prerequisite for engagement with a post (De Vries, Gensler, and Leeflang 2012, p. 84). Processing can only occur, if the post is initially recognized and receives attention. As a brand post on Instagram almost always includes a picture, and the size of the posted visual content cannot be varied, the implementation of the stimuli size of picture and size of ad in this study first does not appear to work properly. The manipulative stimulus of the size-effects, however, can be transferred onto an essential element within the picture, the product. Thus, these design stimuli serve to derive a new stimulus which is hypothesized to influence the engagement rate. Based on the former, this paper will investigate the influence of the size of the product within the picture on the engagement rate. If the varying size of the ad or the picture inherent in the ad increases attention to the ad, the size of the product within a picture may also influence the engagement rate (Pieters and Wedel 2004, pp. 47–48). As bigger ads are superior compared to smaller ads, it is assumed that the growing size of the branded product will evoke more attention, thus increases the salience and therefore evokes a higher engagement rate (Finn 1988; Lohse 1997, p. 71; MacInnis, Moorman, and Jaworski 1991, pp. 35–36; Pieters and Wedel 2004, p. 48). Not all brand posts depict a product. It is expected that brand posts showing a product cause higher engagement rates than posts without products. Positive or. any associations with the brand are expected to be available faster if the consumer is confronted with a visualization of the product (Keller 1993).
Traditional literature states that black and white ads are adequate for the presentation of information whereas colors are able to elicit emotions (Rossiter 1982, 1982, p. 102). Color can increase the perceived attractiveness of the ad and under low involvement situations consumers seem to be persuaded more by ads that use color (Meyers-Levy and Peracchio 1995, pp. 121–122, p. 135). In similar vein, Kroeber-Riel (1993) state that the use of colors is critical for optimal ad design as specific colors seem to evoke certain feelings (here and in the following, Kroeber-Riel 1993, pp. 144–145). Truth is for instance associated with white, blue and gold (Kroeber-Riel 1993, p. 145). The other way around, certain colors are associated with certain meaning (Küthe and Küthe 2002, pp. 90–91). Blue is associated with width, eternity on a semantic level and with harmony and friendliness on a metaphorical level (Küthe and Küthe 2002, p. 90 and p. 108). Blue and green are claimed to enhance pleasure and are often declared as cool colors (Kroeber-Riel 1993, p. 102; Schindler 1986, p. 70). Yet, these associations and effects should be considered with respect to the cultural background of the target audience (Kroeber-Riel 1993, p. 102). Red is associated with activity or danger on the sematic level and zest for life, sexuality, and phantasy on the metaphoric level (Küthe and Küthe 2002, p. 90). Furthermore, red and yellow are called warm colors and are claimed to be emotionally and physically arousing (Bellizzi and Hite 1992, p. 348; Kroeber-Riel 1993, p. 102; Schindler 1986, p. 70). The higher state of arousal in response to red is inherently arousing to the human mind and not conditioned as other color reactions patterns (Bellizzi and Hite 1992, p. 348). While it is argued that red is best suitable to attract attention, others state that blue is superior for that purpose (Bellizzi and Hite 1992, p. 357; Lohse 1997, p. 71; Panigyrakis and Kyrousi 2013). Color is also found to distract from other information in the ad and to hinder processing (Meyers-Levy and Peracchio 1995, p. 122). An Instagram post is aiming to be recognized, therefore coloring which lead to a high level of salience and attracting attention seem to be advantageous. Due to the vast amount of research, it seems reasonable that coloring can influence the engagement of a post by evoking attention as well as emotions and a thereupon resulting reaction (MacInnis, Moorman, and Jaworski 1991, p. 36; Panigyrakis and Kyrousi 2013). In similar vein, it is expected that the usage of light, here interpreted as warm light, displayed as sunsets, light bulbs or fairy lights leads to higher engagement.
Referring to MacInnis, Moorman, and Jaworski (1991) celebrity endorsers also fall into the category of physically intensive & prominent stimuli. This stimulus is expected to lead to higher engagement as celebrities or influencers, as they are called on Instagram, are able to enhance positive brand-related responses and emotions (Kamins 1990; Keel and Nataraajan 2012; MacInnis, Moorman, and Jaworski 1991). Users might like the picture regardless of the product only because they have positive associations with the prominent person on the picture or because they strive to transfer the celebrities associations onto their self by engaging with the post (Balachander and Ghose Sanjoy 2003; Keller 2003, p. 595). Attractiveness of the celebrity can foster this effect (Baker and Churchill 1977, p. 553; Kamins and Gupta 1994).
To summarize, even if the consumer’s situational involvement and the processing motivation may be low, physically intensive and prominent stimuli are expected to work in terms of attracting attention and causing engagement. The user may be processing with low mental effort but due to the stimuli’s strength and power to cause knee-jerk reactions, it is assumed that the engagement is influenced by these stimuli (Itti, Rees, and Tsotsos 2005, p. 1; Kroeber-Riel 1979, p. 244).
H1 : (a) The product size, (b) the visibility of a product, (c) coloring, (d) warm light, and (e) a celebrity endorser used as visual design stimuli within a brand post positively influence the consumer engagement rate on Instagram.
3.2.2 Effectiveness of Novel & Cognitive Stimuli
Another way to enhance the salience of a brand post is to deploy novel and cognitive demanding stimuli (Berlyne 1960, 1970; MacInnis, Moorman, and Jaworski 1991, p. 36). Novel and complex stimuli lead to prolonged attention towards the ad and likability (Ang, Lee, and Leong 2007, p. 221; Fleming and Sheikhian 1972, pp. 438–439; MacInnis, Moorman, and Jaworski 1991, p. 36; Pieters, Wedel, and Batra 2010, p. 55). As receiving attention is the first obstacle a brand post on Instagram must overcome, it seems likely that a post containing novel or cognitive stimuli will also induce the engagement rate (De Vries, Gensler, and Leeflang 2012, p. 84; Pieters, Wedel, and Batra 2010, p. 55). The prolonged time of attention towards the post and the thereupon higher processing could e.g., also raise the level of self-identification, if the post provides suitable stimuli (MacInnis and Jaworski 1989, p. 13; Pieters, Wedel, and Batra 2010, p. 55; Wirtz et al. 2013, p. 230). This is advantageous as this can lead to positive emotions towards the post and trigger engagement (Reed 2004, p. 293). Self-identification with communication material can additionally be enhanced by using realistic pictures rather than abstract images or drawings (Rossiter 1982, p. 102).
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