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OPTIMAL VIRAL MARKETING IN THE FAST MOVING CONSUMER GOODS INDUSTRY MASTER THESIS University of Amsterdam Amsterdam Business School Name: Bram van Eck Student number: 0442887 1st supervisor: drs. ing. A.C.J. Meulemans 2nd supervisor: prof. dr. J.H.J.P. Tettero 1 Word of thanks This is it. After almost 20 years of education, the moment for me is here to close a chapter I always referred to as ‘school’, even when I was already in college for almost 5 years. Living this chapter of my life has been great. I learned a lot during this time. Not only on professional level, I also learned a lot about myself. I would not have been able to graduate for my master Business Studies on my own. I have been supported during this process by multiple people and I would like to thank them for this. To start, I would like to thank my supervisors drs. ing. Meulemans and prof. dr. Tettero for guiding me through my research process. The feedback I got from mr. Meulemans did not always make sense to me in the beginning, but later on I figured out he had (again) pointed out exactly what the weaknesses of my research were and how to improve these. Further, I would like to thank Rogier Baars, a good friend of me who sacrificed his time to help me analyse my data in SPSS, something what would have cost me loads of time if I had to figure SPSS out myself. Next, I would like to thank my parents for all their support during my 20 years of education. I realise not everyone gets an opportunity to study. My parents made this possible for me. Also, I have not always been the ideal student, but they always knew a way to motivate me when needed. Last, I thank Marjolijn Schouten, my girlfriend who sometimes had to cope with a boyfriend who was only with half of his attention at her story, while figuring out his thesis. Thanks for your love and support. Bram van Eck 2 Content Abstract 5 1. Introduction 6 2. Theoretical framework 8 2.1 The basics of viral marketing 8 2.1.1 Introduction in viral marketing 8 2.1.2 Definition of viral marketing 9 2.2 How viral marketing works 10 2.2.1 Viral marketing and word-of-mouth 10 2.2.2 The spreading of viral marketing 11 2.2.3 Customer value 14 2.3 Where viral marketing leads to 16 2.4 Why (not) to use viral marketing 18 2.4.1 Advantages 18 2.4.2 Disadvantages 19 2.5 Email: the most common form of viral marketing 20 2.5.1 Reaction to receiving pass-along email 21 2.5.2 Content of pass-along email 23 2.5.3 Motivations for sending pass-along email 25 2.5.4 Target selection in pass-along email 27 2.6 Success factors and the optimal use of viral marketing 28 2.6.1 Success factors 28 2.2.6 The optimal use of viral marketing 29 3. The fmcg industry and viral marketing in practice 32 3.1 The fast moving consumer goods industry 32 3.2 Trends in the fmcg industry 32 3.3 Viral marketing in practice 33 4. Method 36 4.1 Conceptual model 36 4.2 Research Method 37 4.2.1 Survey 37 4.2.2 Validity and reliability 39 4.2.3 Accounting for survey errors 40 4.3 Operationalization of the variables 40 4.3.1 The independent variables 41 4.3.2 The dependent variables 42 3 4.3.3 The respondent characteristics 43 4.4 The questionnaire 43 4.5 The virals 44 4.6 Method for analysis 45 5. Research results 46 5.1 Sample 46 5.2 Merging the variables 47 5.3 The influence of virals on the dependent variables 48 5.4 The regression analyses 50 5.4.1 Awareness creation 50 5.4.2 Interest creation 51 5.4.3 Purchase decision 51 5.5 Ranking the variables 52 5.5.1 Awareness creation 53 5.5.2 Interest creation 54 5.5.3 Purchase decision 54 5.5.4 Overall 55 6. Discussion 57 6.1 The virals 57 6.2 The independent variables 57 6.2.1 A clear target group 58 6.2.2 A strong, emotional content 58 6.2.3 Plays on current or recent events 58 6.2.4 Incorporation in total marketing strategy 58 6.2.5 Initial sending is to a large target group 59 6.2.6 Actively addressing target group 59 6.2.7 A jump-start is made 59 6.2.8 Influential consumers spread the viral 60 6.3 Respondent characteristics 60 7. Conclusion 62 8. Theoretical contributions and managerial implications 64 8.1 Theoretical contributions 64 8.2 Managerial implications 64 9. Limitations and further research 65 References 67 Appendix A – Questionnaire 70 Appendix B - Regression analysis output in SPSS 83 4 Abstract Viral marketing is a marketing tool growing in use. Many researches have been done so far about different aspects of viral marketing. No academical research so far, to my knowledge, has shown how to use viral marketing optimally. In this research, the variables determining the optimal use are researched by examining the fast moving consumer goods industry. First, by reviewing literature from academical research as well as practice, eight variables are found that determine the optimal use in viral marketing. These eight variables already existed in literature, though scattered and defined differently through different literature. Next, these eight variables are operationalized and examined on their influence on optimal viral marketing by using viral movies and obtaining data by a questionnaire. The data from these questionnaires is analyzed by doing twelve regression analysis in SPSS. These outcomes showed that the eight different variables have different degrees of influence on optimal viral marketing. From this research can be concluded that having a clear target group up front and actively addressing this target group with your viral should be at the base of every viral. Further, making a jump-start and incorporating the viral in the total marketing mix determine are important for making a viral successful. The variables ‘play on current or recent events’, ‘let influential consumers spread the viral’ and ‘make a viral have a strong, emotional content’ have a moderate influence and should be accounted for, but this is not priority in making a viral work. Last, the number of consumers a firm should send the initial sending of a viral to, depends on the effectiveness of a viral. This should be measured by pre-testing. 5 1. Introduction Marketing departments have a decreasing influence within firms. The actual influence of marketing departments nowadays is limited to advertising; relationship management; and segmentation, targeting and positioning. Areas that once were dominated by the marketing department of a firm, like pricing and distribution, are now in the hands of other departments, such like finance and sales. Different studies show that marketing is losing ground within firms (Schultz, 2005; Webster et al. 2005; Verhoef & Leeflang, 2009). Nowadays, only 10 percent of executives time is spent on marketing (Ambler, 2003, p. 62). According to (Verhoef & Leeflang, 2009), accountability and innovativeness are the key antecedents of the marketing department’s influence. The focus of marketing should lie on these aspects to increase marketing influence again. With innovation, (Verhoef & Leeflang, 2009) means innovation in the products or services a company offers, as well as the methods for marketing products or services. Traditional marketing should (partly) be replaced by innovative ways of marketing, also named entrepreneurial marketing (Morris, Schindehutte & LaForge, 2002). The use of internet has increased dramatically over the past decade. A few billion people make use of internet for different purposes. Millions of people use internet to interact with each other online. With this excessive growth of the internet, consumer interconnections are greatly facilitated (Ferguson, 2008, p. 180). Information can be shared easier than ever before by the use of email referrals, online forums of newsgroups and users, as well as customer reviews. This online communication facilitates and leads to both positive and negative word-of-mouth (Phelps et al, 2004). Both the need for marketing to focus on innovation and the dramatic growth of the internet are reasons for viral marketing to exist. Viral marketing is an (relatively) innovative marketing tool which addresses the growth of online communication. Consider the case of Hotmail as an example of one of the first and most successful uses of viral marketing: based on the publicity Hotmail gained, by the use of word-of-mouse (every email sent by a Hotmail user contained a small message at the bottom of the email which convinced people to subscribe for a Hotmail account), one million subscribers in its first six months, doubled this to two million in two months and passed the eleven million in eighteen months. In 2000, Hotmail had over 66 million users with 270,000 new accounts made every day. By this exponential growth, Hotmail has grown faster than any media company in history (Subramani & Rajagopalan, 2003). As stated above, viral marketing fits in the changing (marketing) environment because of its use of internet and the innovative way of marketing. This is why viral marketing is already used by marketing departments. On top of that, the environment now has changed a lot. Since 2008, a financial crisis followed by an economic crisis reigns over the world. This recession has its impact on marketing departments; some firms view recessions as an opportunity to strengthen their business by investing in marketing heavily, but most companies cut back on budgets and wait for the recession to pass 6 (Srinivasan, Rangaswamy & Lilien, 2005). According to Readon (2009), for companies which have less money to spend on marketing, viral marketing will become more important than ever before. This is because viral marketing has some traits (e.g. cheap and may lead to purchase) that are appealing for companies in a recession, as their budgets may shrink and their focus lies more on short-term sales (Chernatony et al., 1991; Axarloglou, 2003). The intensive growth in the use of internet, the need for marketing departments to find new ways to advertise and the economical crisis make viral marketing a very relevant topic to investigate. In the last years, research to the application of viral marketing has started. The expectations of (Readon, 2009) that the economical crisis will make viral marketing more important than ever before, will make viral marketing to be even more researched. Though some research has already occurred, there is no research (to my knowledge) that has pointed out how to use viral marketing optimally. Success factors have been described, but the optimal use is not clear yet. In this research, optimality of the use of viral marketing will be investigated. Because a master’s thesis about the optimal use of viral marketing in general would be very broad and difficult to research, I will focus this research on viral movies in the fast moving consumer goods (fmcg) industry. This industry is best suitable for this research because the fmcg industry makes intensive use of viral marketing; the industry is characterized by heavy competition between many brands. For these brands it is hard to stand out in the clutter, viral marketing is one of the tools used to reach this goal. The focus on viral movies is chosen because this kind of viral marketing is growing rapidly (see below). The goal of this research is to find out what the optimal use of viral marketing is in the fmcg industry. The outcome of this research is relevant for academics because of the better understanding of how to use viral marketing in an optimal way and if there are differences in the use of viral marketing in the fmcg industry. These are both relevant to practitioners as well. The proposed research question for this master’s thesis is: What is the optimal use of viral marketing in the fast moving consumer goods industry? This will be researched as follows. First, a theoretical analysis will be made on the viral marketing topic. How does it work, how is a viral spread and how can viral marketing be used optimally? This theoretical analysis will be covered in chapter 2. When this analysis is made, the fmcg industry in practice will be researched in chapter 3. What are the characteristics of this industry? How is it different from other industries? What are the characteristics of this industry and what are trends for the future? In chapter 4 this method is explained more thoroughly. Further, chapter 5 contains the research results, followed by the analysis in chapter 6. The conclusion will be given in chapter 7. Theoretical contributions and managerial implications will be stated in chapter 8 and limitations of this research will be presented in chapter 9. 7 2. Theoretical framework In this part of the research, the theoretical framework will be outlined. To get a good understanding of how viral marketing works optimally in the fast moving consumer goods industry, we first have to look at the basics of viral marketing; how does viral marketing work, how is it used, what are the advantages and disadvantages. When these issues are defined, we can look at the success factors of viral marketing: how can viral marketing be used optimally? 2.1 The basics of viral marketing In this part, the basics of viral marketing will be reviewed to get a good idea of the concept of viral marketing. This chapter will begin with the basic constructs on which viral marketing is build. After that, the definition of viral marketing will be given. 2.1.1 Introduction in viral marketing Because of the dramatic growth of the internet over the last decade, there has been a shift towards an online world, where people interact and virtually meet with each other. An important phenomenon in this is the use of electronic peer-to-peer referrals (De Bruyn & Lillien, 2008). Where this peer-to-peer referral was mostly face-to-face, there are now a variety of ways in which to refer peer-to-peer electronically. Electronic peer-to-peer communication differs from traditional peer-to-peer communication in important ways (see paragraph 2.2). Some examples are email, forums, communities like hyves and facebook, twitter and comparison websites. All together, online social networks are becoming an important source of information, influencing the use and adoption of services and products (Subramani & Rajagopalan, 2003). Viral marketing is a form of advertising designed to exploit these social networks by encouraging customers to share product information with their relations (De Bruyn & Lillien, 2008). The goal of viral marketing is to use consumer-to-consumer communications instead of company-to-consumer communication, which is used in other types of advertising. Information about a product or service is spread from one consumer to another, without the interference of the company. In this way, a brand message can be spread throughout a network of buyers. This type of advertising can be very useful to target a specific market, has cost advantages, can spread fast and is often more accepted by people because they hear from a product or service through someone they know, in stead of a company (more about the advantages in below). Viral marketing is sometimes seen as a random ground-up phenomenon which is hard to control. However, there are best practices in how to use viral marketing, which marketers can use to trigger interest, increase awareness, lead to adoption, etc. (see for more on this the part of ‘where viral marketing leads to’). 8 In viral marketing, turning customers into a marketing force is crucial (Phelps et al, 2004). Customers spread the message through word-of-mouth (WOM), which means that the promotion of a company or its products and services is done by getting people talking (positively) to each other about the company or its products and services. WOM is seen as very important for a company; when customers talk in negative ways about a company, this is a good predictor of the future of the company (Phelps et al, 2004). 2.1.2 Definition of viral marketing As with a lot of definitions, there is no total agreement about the definition of viral marketing. The first definition of viral marketing was given in 1997, when viral marketing was loosely seen as ‘network enhanced word of mouth’ (Jurvetson, 2000). This is still at the basic of the definitions that appear now. Some see viral marketing as WOM advertising in which consumers tell other consumers about the product or service, while others argue that viral marketing differs from WOM in that the value of the virus to the original consumer is directly related to the number of other users it attracts (Phelps et al, 2004). Further, according to Phelps et al. (2004), the concept describes a way of acquiring new customers by encouraging honest communication among customers. Hill, Provost & Volinsky (2006) state that when firms give explicit incentives to consumers to spread information about a product via word of mouth, it is viral marketing. This definition differs from others in that it states companies give ‘explicit incentives’ to consumers in viral marketing. Another definition is given by Kirby & Mardsen (2005) who state that viral marketing is the promotion of a company or its products and services through a persuasive message designed to spread, typically online, from person to person. This is done by companies by creating branded internet materials or websites that consumers enjoy sharing with their friends, usually by email. Interesting to note here, is that they mention email as the most common form of viral marketing. This is done by Phelps et al. (2004) as well, they use the definition: the process of encouraging honest communication among consumer networks, usually by email. Because of its completeness and best fit within other definitions, the definition by Kirby & Mardsen (2005) is chosen as the definition for this research. Because email is seen as the most common form of viral marketing, the use of email for a viral marketing campaign will be handled separately (see below). Last, I would like to mention viral marketing has different meanings from different perspectives. From a practical perspective, it is a strategy whereby people forward a message to other people on their email lists who will probably like the message. From a marketing perspective, viral marketing is a process in which customers get encouraged to pass along favourable or compelling marketing information they receive in a hypermedia environment (Dobele, Toleman & Beverland, 2005). From a consumers perspective, it is a funny or intriguing message which they like to share with their friends (Hill, Provost & Volinsky, 2006). 9 2.2 How viral marketing works In this part, viral marketing will be further explained. This is done by looking at word-of-mouth (WOM). This concept is explained and differences with electronic WOM are highlighted. In the second part of this paragraph, the spreading of a viral is explained. The last part explains customer value, which is used in the targeting of viral marketing. 2.2.1 Viral marketing and word-of-mouth Viral marketing makes use of WOM, which is defined as: the promotion of a company or its products and services through an initiative conceived and designed to get people talking positively about that company, product or service. Umbrella term for marketing practises which aims to make consumers talk about a brand (Kirby & Mardsen, 2005, p. 181). WOM is informal, as it is from one consumer to another. There, features and uses of products and services are discussed (Kiss & Bichler, 2008). With viral marketing, the company uses the customers in their market to promote a product. When a viral marketing campaign works well, this can be much more cost efficient than with traditional media, where all the promotion has to be done by the company itself (Richardson & Domingos, 2002; Kirby & Mardsen, 2005; Hill, Provost & Volinsky, 2006; Readon, 2009). Another advantage is that people trust and will value recommendations from people they know more than a firm’s recommendation (Richardson & Domingos, 2002; Kirby & Mardsen, 2005; Kiss & Bichler, 2008; De Bruyn & Lillien, 2008). This was proven by (Richardson & Domingos, 2002). In a research conducted by them, it was found that viral marketing resulted in a higher increase in profit than with direct marketing. Because viral marketing is based on WOM, it is important to understand its process of passalong and the mechanisms underlying it. In doing this, a few differences exist between offline and online WOM. Online WOM or eWOM, differs from WOM in these ways: • The scope and scale concerning the influence of a person is expanded. Computer mediation allows people to interact with many people at the same time, because there is no need for faceto-face communication anymore. A person can send an email to all contacts in his address book without much effort per person. In this way, the number of connected others to influence is increased. Further, people communicate more often, because it takes less time to communicate (Subramani & Rajagopalan, 2003). • The way of interacting is not bound to time anymore. Where with WOM two people have to interact synchronously, with eWOM this can be at the same time (instant messaging) or asynchronously, through the use of email (Subramani & Rajagopalan, 2003). • The referrals made are less personal than with WOM. Because eWOM is send to people on great scale, some email may become unsolicited, which leads to people receiving information they do not want (Subramani & Rajagopalan, 2003). 10 • Last, eWOM is much better to measure than WOM. With eWOM, direct feedback on the impact of viral marketing is given, which makes it possible for a marketer to adjust strategy for more influence (De Bruyn & Lillien, 2008). Although this is the case, it is still very difficult to really measure impact, for example it is hard to see what the content of private conversations is like (Kiss & Bichler, 2008). These differences are to keep in mind for the rest of the research. Most literature however, uses these definitions interchangeably, most of the time just referring to WOM. This will be done in this research as well. WOM (and so eWOM) is used for a wide range of industries, products and services. In one industry, the importance of WOM may differ from another industry. WOM has the highest importance when consumers have little expertise, have a high risk in decision making and are deeply involved in the purchasing decision (Subramani & Rajagopalan, 2003). The eWOM process can be either intentional or unintentional. A consumer may choose to promote a brand, product or service because of an explicit incentive (through financial reward for example, done by PayPal to increase use) or because that person really wants to share the benefits of a product with others. Unintentional eWOM is best explained by the example of Hotmail, where each outgoing email sent by a Hotmail user contained a line in the bottom to promote the company and the use of Hotmail (e.g. ‘Get free Hotmail now!’) (De Bruyn & Lillien, 2008). The influence of WOM is reported to be greater than print ads, personal selling, and radio advertising. So if there is a lot of positive WOM about a company or its products or services, this is a good predictor of the success of a company (Jurvetson, 2000). It has to be noted however, that dissatisfaction produces more negative WOM than satisfaction produces positive WOM (Kiss & Bichler, 2008). People have to be triggered to participate in WOM or viral marketing. They reasons why consumers proactively spread the word about brands, products or services are (De Bruyn & Lillien, 2008): • They feel extreme satisfaction or dissatisfaction • They have a lot of commitment to the firm • They have a very long relationship with the firm • They experience the product very novel or/and useful 2.2.2 The spreading of viral marketing Viral marketing makes use of WOM. In this part, the underlying aspects of WOM will be discussed. In the first part, the spreading of a viral marketing will be highlighted. The second part will folow with what makes WOM influential, and which factors influence the impact of WOM. There are different diffusion models that exist for analyzing the spread of viral marketing. These can be divided into two groups (Leskovec, Adamic & Huberman, 2007): 11 1. Threshold model: each node in a network will eventually adapt a product when a certain threshold is met. This happens when all the nodes that have influence on the node researched (one node may have more influence on the researched node than another) collectively send enough positive messages (in all forms) to meet the threshold level of a node to adapt to a product. This threshold level is different for every node (i.e. every individual). 2. Cascade model: every time a node connected to the node researched adopts a brand, product or service, there is a probability or chance the node researched may also adapt. Every time a connected node adapts or states positive information, there is a chance that the node researched may adopt as well. There is a long research history in social sciences on the influence of social networks on innovation and product diffusion (Leskovec, Adamic & Huberman, 2007). The origins of research on the spreading of viral marketing and the influence through the networks come from the research on epidemiology and the spread of diseases over a network (Leskovec, Adamic & Huberman, 2007). Multiple models exist about how a virus spreads. The model that can be compared with the spreading of viral marketing is the SIR (susceptible/infected/recovered) model. In this model, a set of initially infected nodes (the nodes that are infected by the company) correspond to people who are most susceptible to it (the target market). These people then get infected, they purchase the product of a company and then try to infect its neighbours with a purchase of the product by recommending it. This model assumes that a node (i.e. a person) can buy a product only once, and then recovers (Leskovec, Adamic & Huberman, 2007). The reason this model assumes a person recovers after it was infected (instead of with a SIRS model, in which a person becomes susceptible again after recovery), is because the probability of infection decreases rapidly with repeated interaction. So, when a viral is received multiple times by one person, this could backfire by weakening the credibility of the viral as well as the brand, product or service the viral is referring to (Leskovec, Adamic & Huberman, 2007). Though the above model is commonly used, other models that are used for analyzing the spreading of viral marketing exist as well. One of the first and most influential models concerning diffusion was the model of Bass (1969). This model of product diffusion can be used to estimate the number of people who will eventually adopt a product (over time). This model makes use of the rate of adoption as a function of the percentage of the population that has already adopted a product and describes an S-curve in which adoption is slow at first. Then, as more people adopt the product and spread the message, the adoption increases exponentially. Eventually, when the most of the target audience is reached by the viral message, the adoption flattens. This is an effective way to model WOM product diffusion at the population level, but not at the individual level, especially as the Bass model does not divide individuals in different groups of how influential they are (Leskovec, Adamic & Huberman, 2007). Both groups of models discussed above that exist assume that an increasing number of infected contacts or nodes results in an increased likelihood of infection. A commonly used formula for this is: 12 number of accumulated users = [(1 + fan-out * conversion rate) * retention rate]frequency * time (Jurvetson, 2000) in which it is shown that an increased likelihood of infection comes from an increasing number of infected contacts, though this formula also incorporates the retention rate. This model can be used in combination with the S-shaped curve of Bass (1969) to make an appropriate estimation about the number of users or adaptors (Jurvetson, 2000). As we can see from the formula, the ideal viral product is used to communicate with many people, converts a high percentage of them to new users, and has a makes sure a high percentage of those who become users, stay users (Jurvetson, 2000). With every contact of WOM, the chances that a person is persuaded to also become adapted is determined by different factors. Subramani & Rajagopalan (2003) have provided a matrix in which the nature of influence in viral marketing can be determined based on two factors: the role of the influencer and the level of network externalities. First, the role of the influencer can be either passive or active, according to Subramani & Rajagopalan (2003). Second, the level of network externalities refers to the additional benefits that come from broader usage of the product or service being recommended within a user community (see figure 2.1). Figure 2.1. Framework for nature of influence (adapted from Subramani & Rajagopalan, 2003) In this figure, the more active the role of the influencer and the higher the benefits to all users (dependent on user base), the more influence on the receiver of a viral message, which means more chance of the targeted person to be persuaded (Subramani & Rajagopalan, 2003). The researchers also distinguish between normative and informational influence. Normative influence means recipient behaviour is based on the interpretation of the information provided by the influencer as an implied expectation to conform, whereas informational influence is based on an evaluation personally made of the provided information by the influencer. Normative influences weight stronger than informative (Subramani & Rajagopalan, 2003). The research by Leskovec, Adamic & Huberman (2007) identified other factors that determined the level of influence on a recipient of a viral message. In earlier research, it was found that 13 demographic similarity has a positive correlation with WOM influence. Leskovec, Adamic & Huberman (2007) however, found that geographically defined networks of consumers are more useful for predicting influence of WOM than demographic similarity. Further, source expertise, tie strength (how good is the relationship of the influencer on the person being influenced) and perceptual affinity are other factors that determine the nature of influence of a WOM contact (Leskovec, Adamic & Huberman, 2007). 2.2.3 Customer value As stated above, not every WOM contact between two individuals is equally influential. Things like tie strength, source expertise etc. all play a part in this. Another important aspect of WOM are the differences between individuals in the amount of influence they have. Because WOM has a very strong impact on customer opinions and adoption, marketing departments should try to focus on influential customers (Richardson & Domingos, 2002; Domingos, 2003; Kirby & Mardsen, 2005; Kiss & Bichler, 2008; De Bruyn & Lillien, 2008). According to Kirby & Mardsen (2005), mass-media messages do not directly influence the mass market. Instead, mass marketing only influences a small minority of individuals, these are called influencers or opinion leaders. These opinion leaders then influence others through WOM. These others influence their peers, and so on. This is what makes WOM so important (Kirby & Mardsen, 2005), see figure 2.2. Figure 2.2. The influence process (adapted from Kirby & Mardsen, 2005) Kiss & Bichler (2008) have stated also that some customers are more influential than others. They believe that everyone has some kind of network in which every node has approximately the same amount of influence (figure 2.3a: the random network) does not exist anymore. They believe that centrality of a node exists and that this centrality of a node in a network is a way to measure the 14 structural importance of the node. The more central a customer, the more influence it has on other (potential) customers. This is show in figure 2.3b: the scale-free network. Figure 2.3. Random network vs. scale-free network (adapted from Kiss & Bichler, 2008) Customer value is defined as the expected profit from sales to that customer, over the lifetime of the relationship between the customer and the company. Companies are interested in this, because by knowing the customer value of a person, the company can determine how much it is worth spending to acquire a particular customer (Domingos, 2003). With the new insight of some individuals having more influence than others, a new way of determining the value of a customer arises (Richardson & Domingos, 2002; Domingos, 2003). Traditional measures of customer value are based on what customers will buy from the company. However, these measurements ignore the fact that some customers will influence others to buy products as well. So, next to the intrinsic value of a customer, the network value of a customer should be considered too. This can lead to marketing to customers who have a negative intrinsic value, but have a great network value. On the other hand, it can lead to not marketing to customers with a positive intrinsic value, but with a negative network value (this person may give very low product ratings for example) (Richardson & Domingos, 2002; Domingos, 2003). When marketers use this new way of measuring customer value they can search for the most influential customers, where the viral marketing campaign can be addressed to. In this way, the chances of making a viral a success, will increase significantly (Domingos, 2003). The amount of influence a person has in its network is determined by a number of factors. These factors are (Richardson & Domingos, 2002; Subramani & Rajagopalan, 2003): • source expertise • self-confidence • assertiveness • having multiple interests • being an early adopter 15 • being trusted by others • having a large social network • liking the product • social status • having a network that is influential as well With knowing these factors, a company can better determine who to target when starting a marketing campaign. 2.3 Where viral marketing leads to Viral marketing can lead to an increase in awareness, but also to making consumers actually purchase products or services that have been marketed virally. In this section, first an overview will be given based on the awareness, interest, final decision model. After that, a research of (De Bruyn & Lillien, 2008) will be discussed where researchers tested the effect of tie strength, perceptual affinity and demographic similarity on this multi-stage model. The influence of WOM occurs at different stages. There are different multi-stage models designed to describe decision processes. The multi-stage decision making model that is most commonly used consists three stages: awareness, interest and final decision (De Bruyn & Lillien, 2008). These three stages will now be discussed. Awareness is the first stage in the process. In this stage the consumer knows of the existence of a product or service, but does not have either interest in it or enough information to understand its possible benefits that can lead to interest. Viral marketing is a good tool to create awareness for a brand, product or service, mostly because of it is based on WOM from peers (Kirby & Mardsen, 2005; Hill, Provost & Volinsky, 2006; De Bruyn & Lillien, 2008). The second stage is interest. In this stage the consumer is aware of a brand, product or service and develops some interest, which leads to the decision to learn more about it. Awareness is already created, in the interest stage recipients carry out a cost/benefit analysis and ask their selves the question: ‘based on what I already know, is this worth my time to investigate it further?’. Viral marketing can lead to interest. The most important reason for this is that the person that receives a viral message, is targeted by a peer who (most of the times) believes there is something interesting about the brand, product or service for this peer as well (Richardson & Domingos, 2002; Hill, Provost & Volinsky, 2006). The final decision stage is the last one in the process. In this stage, the consumer already has already gathered enough information about the product or service, and now is in the phase where to decide to adapt the product or service, or not. The effects of viral marketing on the final decision stage are stated positive, in most research conducted. For example, Kirby & Mardsen (2005) state that consumers linked to a prior consumer, adopt the product or service at a rate three to five times greater than groups that are targeted by the best targeting practices of a firm’s marketing team. Honda is a good example of this. Their viral marketing campaign lead to more visits of Honda dealers (from 3500 to 16 3700 a month) and the people who visited the dealer would purchase it more often (from 19% to 22%) (Dobele, Toleman & Beverland, 2005; De Bruyn & Lillien, 2008). What has to be noted, is that the above process is hierarchical. Each step in the process is conditional on the positive or favorable outcome of the previous one. This is shown in figure 2.4. In a research of pass-along email they started with sending 1116 people an email. 825 people became aware of the email and its message, 488 show interest and eventually 304 persons made the final decision to complete the survey that was made by the researchers (De Bruyn & Lillien, 2008). Figure 2.4. Multi-stage model of WOM influence (adapted from De Bruyn & Lillien, 2008) De Bruyn & Lillien (2008) discuss that different factors determining WOM influence, have different influences on the three stages proposed above. Although they did not account for all factors that make up the influence of WOM, their research is interesting to mention. They investigated the factors tie strength, perceptual affinity, demographic similarity and source expertise. Their findings are presented in figure 2.5. Their findings conflict with earlier research on these factors of WOM. These differences will not be discussed here, this figure is meant to give an indication that different factors of WOM have different influences in the three stages. Figure 2.5. Different effects of factors of WOM on three stages of influence (adapted from De Bruyn & Lillien, 2008) 17 2.4 Why (not) to use viral marketing For companies to choose for using viral marketing, advantages and disadvantages of this marketing tool have to be clear. What are the advantages and disadvantages of viral marketing in comparison to other types of marketing (e.g. television, radio, internet etc.)? The pros and cons will be reviewed in this section. Potential advantages and disadvantages because of the recession will be reviewed as well. 2.4.1 Advantages Viral marketing has some great advantages which will be discussed here. Using viral marketing in the right way can make a huge benefit for companies. Because of the changing environment, new technologies have emerged. Among these, the intensive use and speed of the internet has made that people want to be more and more entertained on the web. The internet is a big (relatively) new medium which offers a lot of opportunity for marketing. Traditional marketing falls short on this. Viral marketing does not (Dobele, Toleman & Beverland, 2005). The use of viral marketing is relatively cheap, compared to using traditional marketing tools. This is because viral marketing uses the customer to promote a product. Using word-of-mouth advertising leverages the customers to carry out the spreading of the message of a firm. This is costless for a company. Because of the use of the networks used, the company only has to lit the fire. Once lit, the fire will spread itself (Jurvetson, 2000; Richardson & Domingos, 2002; Dobele, Toleman & Beverland, 2005). Viral marketing is better accepted by consumers than other kinds of media, because viral marketing makes use of social networks of people. The advertising comes from a friend instead of the company itself. People have learned to tune out a lot of standard marketing (spam), but people typically trust and act on recommendations from friends. Much more than on a company which tries to sell products (Jurvetson, 2000; Richardson & Domingos, 2002; Dobele, Toleman & Beverland, 2005; Hill, Provost & Volinsky, 2006; Leskovec, Adamic & Huberman, 2007). Consumers who have communicated with prior customers are more likely to become customers, as Hill, Provost & Volinsky (2006) put it. A study by Hill (2006) showed this: consumers linked to a prior customer had an adoption rate that was 3-5 times greater. Further, in a survey it was found that 68% of all consumers consult friends and relatives before they purchase home electronics. As a comparison, only 53% used search engines to find product information (Leskovec, Adamic & Huberman, 2007). So, we all depend and rely on our friends when consulting to buy products. Viral marketing makes use of this in a smart way. Another important aspect of viral marketing is its speed. Traditional media like television need more time to get ‘aired’, while viral marketing can spread fast (Leskovec, Adamic & Huberman, 2007). When a video has been made, it can be spread immediately. With marketing there are different options for spreading your message. You can use direct marketing which is based on characteristics of consumers or mass marketing, which in turn is based on 18 population segments. These methods use rough estimates of consumers and their needs, it is suboptimal (Richardson & Domingos, 2002). With viral marketing, the consumer is the one that does the marketing and so the targeting for you. This consumer will be much more likely to know which of their friends, family members and colleagues have similar interests, needs and tastes. Hence, these people will be more likely to read the message, so targeting is much more effective than with mass or direct marketing (Dobele, Toleman & Beverland, 2005). Viral marketing techniques can reach adolescents, a part of the population that is difficult to reach by traditional media (Dobele, Toleman & Beverland, 2005). Marketing niche products is difficult to do with traditional media. Using mass media is often not practical and too expensive. With viral marketing, niche products can be marketed because of the effective targeting and low cost (Leskovec, Adamic & Huberman, 2007). In a recession, for most companies marketing budgets are reduced because of cost savings, although some firms use a recession to proactively market and increase market share (Srinivasan, Rangaswamy & Lilien, 2005). Viral marketing is a good option for firms which cut back marketing budgets, because of its low cost. For companies that try to make advantage of the recession by proactive marketing, marketing budgets will not shrink. The benefit of cost advantage of VM then has less impact on these companies, though it still is an advantage. 2.4.2 Disadvantages Viral marketing also has its disadvantages. The inappropriate use of viral marketing can be counterproductive for companies by creating unfavourable attitudes towards products, brands and firms (Subramani & Rajagopalan, 2003; Leskovec, Adamic & Huberman, 2007). An important disadvantage of viral marketing is that consumers may feel exploited by viral marketing campaings. This is when consumers ‘discover’ that a message has a higher purpose than entertaining or exciting. There has been a lot of discussion about this subject. The blair witch project, a movie that was a big success, gained this success for a great part from viral marketing. A website existed in which findings of the sheriff and official police reports were shown about the findings and whereabouts of the students of the blair witch project. Also, a forum was created in which was suggested the movie had really happened. Later came out that this was all done by promotion and marketing companies, and the responses on forums were posts by family members of the movie makers. If this was known earlier publicly, the blair witch would probably never have been such a big success (Leskovec, Adamic & Huberman, 2007). This is why some people just do not like receiving any kind of viral marketing, how funny or exciting it may be. Designing a viral campaign is difficult and requires specific skills. Making a viral a success is a difficult task. If the viral is not spread, no awareness or extra sales are created, while with traditional media you are sure of a baseline of people that hear from your product or company. So only using a viral marketing campaign without using traditional media is concerns a lot of risk for a company. That is why 19 viral marketing is a tool which is often used in combination with other tools. What made one viral campaign a big success, may not work for another. It is difficult, relatively to other kinds of marketing (e.g. television, radio, magazines etc.) to predict how successful a viral marketing campaign will be (Richardson & Domingos, 2002). Another difficulty is that a viral is hard to control once it is launched. A television or radio commercial can be stopped relatively quickly (within a few hours) while a viral can not really be stopped anymore (Richardson & Domingos, 2002; Subramani & Rajagopalan, 2003; Leskovec, Adamic & Huberman, 2007). 2.5 Email: the most common form of viral marketing In this section, the use of pass-along email will be reviewed. Pass-along email is only one of the ways in which viral marketing can exist. The reason for examining pass-along email separately is because it is by far the most important form in which viral marketing exists (Phelps et al, 2004). Emailing is the number one internet activity in the world. More than 90 percent of the people that have access to the internet, use email. 50 percent of the total online community uses email on a daily basis (Madden, 2003). Email is used in a business as well as a private setting. People communicate by email with friends, family, colleagues and other relatives. This makes email a huge communication medium, which offers great opportunities to marketeers. According to Priore (2000), the average American household received nine email marketing messages a day in 2004. This comes down to 3,285 emails a year. Because of its low costs to companies, the ability to target directly and relatively selectively and high response rates relatively to other direct marketing tools, emailing was very interesting to companies. However, because of its attractiveness, every company started using it and now this kind of marketing is so saturated that it does not have very much added value for firms anymore (Phelps et al, 2004). When receiving a message from a marketeer, a consumer has only got to press the delete button. Deleting an email from a person they know however, is not that common. This is the key success factor of viral marketing, and makes consumers which are persuaded by friends much more open to this than by media advertising (Phelps et al, 2004). Email has become, in the last decade, a common channel for interpersonal communication like postal mail and telephone. There are some differences with other common channels however. By email, a person can communicate with a larger number of others more quickly and easily. Further, pass-along email is very well suited for spreading images, videos and verbal content that is very detailed to be spread via word-of-mouth (Phelps et al, 2004). In viral marketing theory with respect to emailing, the overall process of how an email spreads is divided in four stages. These stages are shown in figure 2.6 and depend on each other. If a person does not pass stage 1, it can not go to stages 2, 3 and 4. It is assumed that in every stage a percentage of the total people who receive an email will abandon the cycle. 20 In the next part different aspects of email as viral marketing will be highlighted. These are: reactions of consumers to receiving viral marketing emails, the content of an email, the motives to send an email to others and the target selection in viral marketing email. 2.5.1 Reaction to receiving pass-along email In their research, Phelps et al (2004) make a distinction between heavy internet users (which also use pass-along email a lot) and moderate or light internet users (which use pass-along emailing rarely). The first group is called Viral Mavens, the latter Infrequent Senders. These two groups use group emailing differently. Viral Mavens receive at least one pass-along email every day, while Figure 2.6. Typical pass-along email episode (adapted from Phelps et al, 2004). Infrequent Senders receive around four pass-along emails per week. Though there are differences between Viral Mavens and Infrequent Senders, they have a lot of similarities in their reactions to receiving email. Phelps et al (2004) make a distinction between positive emotional responses (see table 2.1) and negative responses (see table 2.2). 21 Table 2.1. Positive emotional responses to receiving pass-along email (adapted from Phelps et al, 2004) Next to the positive and negative emotions, other important aspects of receiving pass-along email exist. For example, a lot of people think that pass-along emails originate from people with too much free time. They do not perceive these originators as either good or bad. What did have a great influence on the reaction of both Viral Mavens and Infrequent Senders was the mood or mindset of the receiver. If they are feeling rushed, frustrated or had a bad day at work, they report frustration or annoyance much more often. People are aware of this themselves, they state that their mood does influence the feeling towards a pass-along email, but does not influence their feelings towards the sender (Phelps et al, 2004). Viral Mavens eel negative emotions in the absence of pass-along email. They would miss passalong email if it were taken away. The less intensive the user of pass-along email, the less they would miss it. No Infrequent Senders were found to be missing it if it were taken away (Phelps et al, 2004). Last, Viral Mavens were not concerned of viruses spreading in pass-along email, while Infrequent users reported to be concerned about this (Phelps et al, 2004). 22 Table 2.2. Negative emotional responses to receiving pass-along email (adapted from Phelps et al, 2004) 2.5.2 Content of pass-along email Content is the most important success factor for a viral marketing campaign (see part success factors). If a company can create a great content for an email, the chances that people will pass it along increases substantially (Phelps et al, 2004; Dobele, Toleman & Beverland, 2005; Leskovec, Adamic & Huberman, 2007; Burrows, 2009) researched the content of pass-along emails and divided them in different categories (see table 2.2). 23 Table 2.3. Contents in pass-along email (adapted from Phelps et al, 2004) Only a few emails in the table above concerned products and/or companies. This means that this method of advertising is not exploited optimally or that the messages send by companies do not meet the passalong threshold (Phelps et al, 2004). Also, the structure of the pass-along emails was reviewed. There are seven major categories in which the pass-along emails can be divided: 1. text messages (74.7 %) 24 2. static pictures (10.1 %) 3. cartoons (6.1 %) 4. URLs (5 %) 5. animated cartoons (2.9 %) 6. movies (0.6 %) 7. other (0.5 %) It has to be noted here, that this research stems from 2004. My expectations are that especially movies are now more frequently forwarded in pass-along emails than in 2004. What is also interesting to see, is that no differences exist in the number of pass-along emails that men and women received. Yet, women pass more messages along to others (more about this in the target selection part). About 75 percent of the people who send pass-along email personalize the emails once in a while. Pass-along email is personalized if it is sent to one individual at a time, by the inclusion of a note written by the sender, and if the sender changes the subject line, according to Phelps et al (2004). Though 75 percent of the people personalize some emails, only one-third of forwarded messages contained this. Infrequent Senders personalize pass-along email more often than Viral Mavens (51 % versus 29 % respectively). 2.5.3 Motivations for sending pass-along e-mail Phelps et al (2004) also researched why people send pass-along email to their friend, family, colleagues and other relatives. The outcomes are summarized in table 2.4. What is worth to notice here is that four of the six top-rated reasons involved enjoyment and entertainment. These two reasons are mentioned as most important by a lot of authors (Phelps et al, 2004; Dobele, Toleman & Beverland, 2005; Leskovec, Adamic & Huberman, 2007; Burrows, 2009). In this research, it is proven that enjoyment and entertainment are the two best motivators for passing along email. This is probably why humour is the number one ingredient in viral marketing. The other two motivations that were top-rated had a more social nature: to help and to communicate caring. All these reasons (enjoyment, entertainment, caring etc.) exist because people have a desire to connect and share with others. So sending a humorous picture to someone else is making you enjoying something with others (Phelps et al, 2004). Most respondents indicated that they experienced positive emotions when they sent pass-along emails. The emotions they felt were excitement, helpfulness, happiness and satisfaction (Phelps et al, 2004). But, not all emails were passed along, some conditions have to be met before people will forward a message. Herein lays a distinction between Viral Mavens and Infrequent Senders. Viral Mavens have the criteria that it must be something important or it must contain a message which the other person will like. Viral Mavens will only forward messages when they are in the mindset for it (Phelps et al, 2004). Infrequent Senders are more leery in sending pass-along email. As stated above, they do not pass-along 25 email that often. For Infrequent Senders to pass along an email, a certain quality and relevance level has to be reached. This quality threshold lies higher with Infrequent Senders than with Viral Mavens (Phelps et al, 2004). Therefore, they are much more selective in choosing what email to pass along and what not. Table 2.4. Motives for sending pass-along email (adapted from Phelps et al, 2004) Not all pass-along emails are opened by receivers off course. Although the percentage lies much higher, some emails from relatives are deleted without opening like spam. Respondents commonly open messages from people they know. However, knowing the source can make a person delete the email because the source is known in his or her eyes as someone who sends low quality or excessive numbers of email. Further, when receiving an email with a subject line that contains “Fwd: Fwd: Fwd:” people will delete the email more often. The subject line proved to be very important for passing along email in any case. Special attention should be dedicated to this. Besides these aspects, long download times or 26 worries about viruses also makes people delete email. In opening or deleting an email, the mindset of a person also plays an important role. When a person is not “in the mood”, he or she will delete an email more often. In figure 2.7 the numbers of emails received versus emails passed along for 34 participants are shown from the research of Phelps et al (2004). Here has to be noted that at the time of this experiment, the “love bug” virus was active, which made people more reluctant to opening and passing along email. We can therefore state that the normal figures would be higher. Figure 2.7. Pass-along emails received and forwarded (adapted from Phelps et al, 2004) 2.5.4 Target selection in pass-along email In many studies is shown that selecting a target group is one of the success factors for a viral marketing campaign to work (Phelps et al, 2004; Burrows, 2009). This is the same for pass-along email (Leskovec, Adamic & Huberman, 2007). It is essential for marketeers to find people who will find the information relevant enough to pass it on to relatives. All users (Viral Mavens and Infrequent Senders) will quash email that they find uninteresting or irrelevant (Phelps et al, 2004). Finding people who are interested is not easy however. A very practical solution in this is emailing the list of customers who have subscribed for receiving updates from the company or its products. In the ideal situation these people are opinion leaders with a lot of power over their relatives. On top of that, they have to be really interested in the message as well. The goal in this for a company is to initiate a big fire by using a small lucifer. Finding the right people means heavy users or people that do not receive a lot of pass-along email, but that send al email along. Phelps et al (2004) have made a distinction by figure 2.8. The users of cell 2 and 3 are the people that have to be targeted to increase the chances for success. Finding these 27 people can be done by demographic, psychographic, and behavioural proxies (Phelps et al, 2004). What is interesting to note is that in the findings of Phelps et al (2004), it appeared that women are more likely than man to pass along email messages, while they receive the same amount of emails. On top of that, women have a great purchasing power and their representation online is increasing rapidly. This makes women a very interesting target market for marketeers. Wrong targeting can make a pass-along email campaign fail. It can even hurt a company if the wrong target market is chosen. Bad news travels just as fast, if not faster, than good news (Phelps et al, 2004). Figure 2.8. Pass-along profiles (adapted from Phelps et al, 2004) 2.6 The success factors and optimal use of viral marketing With a television commercial, you are assured of a minimum of viewers, as viewers of television are usually obliged to watch. With viral marketing, this assurance is not there (Burrows, 2009). As a marketeer you have to create something that people actually want to watch, and especially something people want others to watch as well. This is the key in the development of a viral marketing campaign (Burrows, 2009; Dobele, Toleman & Beverland, 2005; Phelps et al, 2004). How to do this will be discussed here. Different aspects will be highlighted, followed by a conclusion on how to optimally use viral marketing according to the literature. 2.6.1 Success factors On YouTube, 200,000 videos are uploaded every day. In total, there are 90 million videos on YouTube. Further, a lot of videos, pictures, funny stories etc. are circling on the internet. To succeed as a viral, the viral has to be extraordinary in some way. The most important factor in this is content (Burrows, 2009). If the content of a video is right, it is a reasonable guarantee for success. Humour is by far the most used genre for a viral. The most successful virals also, are based on humour. But, humour is also the biggest cause of failure. Understanding how to use humour in a viral is 28 one of the biggest challenges for marketeers (Dobele, Toleman & Beverland, 2005; Burrows, 2009). When you make a mildly amusing television commercial, the campaign will still be a success as long as the viewers will not switch to another channel. The viewer can be passive. With a viral, a viewer has to be active. The viewer has to put energy in watching the viral and sharing it with friends. So if you make a mildly amusing viral, viewers will not put the energy required in it. If a viral is not going to be really amusing, the marketeer could better not make it (Dobele, Toleman & Beverland, 2005; Burrows, 2009). Other genres can also work well. For a genre or viral to work the key of the content is to stir emotions of consumers, change the way people look at the world or instigate discussion (Burrows, 2009). For a good content, a great idea is needed. Working with the best people and equipment does not guarantee anything if the idea is not great. On the other hand, if the idea is great, the camera work does not have to be great anymore. When making a viral marketing campaign, much effort has to be put on the idea (Burrows, 2009). Before starting to think what a viral marketing campaign is about, it is important for a company to first make clear what the target group is. People who receive a viral ask their selves questions like: do I want to be a member of this group who likes this viral? Will my friends like it? Is this viral worth sending to others? When people send a viral to others, they tie their name to it in some extend. So before making a viral, a firm has to make sure who to target. Else, a humorous viral will end up being a little bit of fun for everyone but no one will send it through (Phelps et al, 2004; Burrows, 2009). A good distribution is another success factor. No one will be able to view this great viral if it is not properly seeded. As a company, there is just the start of the distribution to worry about, once the viral is seeded and it is good, consumers will send it through themselves. Before that, a company has to send it to the right people (influential people), post it on relevant blogs, forums and databases. If this is done properly, chances for success are higher (Burrows, 2009). Timing is an important factor as well. When a company can seed a viral at the right time, the changes of success will increase. This can be done by implementing a viral which relates to a recent event and seeding at times of day when people are reading their emails (Leskovec, Adamic & Huberman, 2007). Successful viral marketing depends for the most part on consumers. If they value a viral enough and do not feel like they are used by a company to promote a product or brand, a viral marketing campaign may become a great success. 2.6.2 The optimal use of viral marketing Above, different aspects of viral marketing have been highlighted. Some of the aspects described earlier have an influence on the optimal use of viral marketing. In this paragraph, the factors determining the optimality of viral marketing will be discussed. I will highlight some factors influencing optimality and conclude with how viral marketing can be used optimally accordingly to the literature. 29 If we look at the formula of how virals spread: number of accumulated users = [(1 + fan-out * conversion rate) * retention rate]frequency * time (Jurvetson, 2000), we can see that in an ideal world, a viral has a number of factors that have to score high for optimal spreading. This is the fan-out, conversation rate, retention rate, frequency and time. For optimal use of viral marketing these factors have to score high, this is the mission of marketers. But the question of how to make optimal use of viral marketing remains. How can these factors be affected in a way a viral becomes a success? Before starting to think what a viral marketing campaign is about, it is important for a company to first make clear what the target group is (as stated above in part 2.4.1). People who receive a viral ask their selves questions like: do I want to be a member of this group who likes this viral? Will my friends like it? Is this viral worth sending to others? When people send a viral to others, they tie their name to it in some extend. So before making a viral, a firm has to make sure who to target. Else, a humorous viral will end up being a little bit of fun for everyone but no one will send it through (Phelps et al, 2004; Burrows, 2009). A clear understanding of the target group up front will make the rest of the process better understandable. The second factor determining optimal use is the content of a viral. This has to be extraordinary in some way. A viral has to stir emotions of consumers, change the way people look or instigate discussion (Burrows, 2009). If the content of a viral is not convincing in some way, it will be very hard to make a viral marketing campaign a success. For people to participate in viral marketing, they have to be triggered. Reasons to participate proactively are (De Bruyn & Lillien, 2008): • They feel extreme satisfaction or dissatisfaction • They have a lot of commitment to the firm • They have a very long relationship with the firm • They experience the product very novel or/and useful On top of these arguments to participate, the level of influence of a WOM contact on the receiver of a viral message is an important indicator if the targeted person will actively participate (Leskovec, Adamic & Huberman, 2007). Factors that account for the amount of influence are (Leskovec, Adamic & Huberman, 2007): • source expertise • self-confidence • assertiveness • having multiple interests • being an early adopter • being trusted by others • having a large social network • liking the product 30 • social status • having a network that is influential as well A good distribution is another factor for optimality. No one will be able to view a great viral if it is not properly seeded. As a company, there is just the start of the distribution to worry about, once the viral is seeded and it is good, consumers will send it through themselves. Before that, a company has to send it to the right people (influential people), post it on relevant blogs, forums and databases. If this is done properly, chances for success are higher (Burrows, 2009). Optimal would be, when the first spreading would occur to the minimum amount of consumers, but still triggering to make a viral a success. This is because consumers prefer contact from people they know above contact from a company trying to promote its brand, product or service. Theoretically speaking the optimal way of spreading thus would be through only one very influential consumer. Timing is, as described above, an important factor as well. When a company can seed a viral at the right time, the changes of success will increase. This can be done by implementing a viral which relates to a recent event (Leskovec, Adamic & Huberman, 2007). In conclusion, viral marketing can be used optimally when: • the target group is chosen up front • the viral has a strong, extraordinary content • influential influencers spread the message • the viral is properly seeded • the timing is right 31 3. The fmcg industry and viral marketing in practice After looking at the theory of how viral marketing can work optimally, we now take a look at the fast moving consumer goods industry. In the first paragraph, an explanation of this industry in general will be given and the characteristics of this industry will be highlighted. Next, some trends in the fmcg industry are given to get an understanding of the aspects that are and will be important for the fmcg industry. Finally, the use of viral marketing in practice will be explained. Because to my knowledge no earlier research is done explicitly about the use of viral marketing in the fmcg industry, this part is (like chapter 2) about viral marketing in general. 3.1 The fast moving consumer goods industry The fmcg industry is an industry in which products are sold that are made for consumers. These are the products that are generally sold at retail stores, most of them grocery stores. This is because fast moving consumer goods are products that are sold relatively quickly and at relatively low cost. Examples can be candy bars, drinks, soap, cosmetics, batteries, teeth cleaning products and detergents. Fast moving consumer goods are sometimes divided in real fast movers (like milk and juice) and slow movers (like herbs and canned meat) and are also known as consumer packaged goods (Webster, 2006) The fmcg industry is an industry characterized by heavy competition. Because consumers will buy fast moving consumer goods continuously, the market is always fighting for market share. This is done by big multinational companies like Procter & Gamble, Sara Lee, Pepsico, Nestlé and Unilever, though they are not so well known as their brands. This partly is what makes the industry different from other industries: it are not the multinationals but their different brands like Dove, Pampers and Nescafé who are found in grocery stores and are well known by consumers. Branding (and marketing in general) is therefore very important in this industry (Groothedde, 2005). 3.2 Trends in the fmcg industry In this part the trends in the fmcg industry will be discussed. Retailers in the fmcg industry are constantly seeking new innovative ways for gaining market share. The trends discussed in this part will cover the changes at the retailers, the price wars between retailers, the shift in marketing and the integration of the supply chain. Retailers are being faced with changes in the market nowadays. They have to cope with increased competition in price and service: margins for retailers shrink while better service is demanded. The grocery market is dominated by a small number of retailers and the number of manufacturers is reduced due to mergers and acquisitions. Only a few companies dominate some product categories (Groothedde, 2005). 32 Because of the worldwide crisis, grocery stores are at price war. Consumers are more focused on price than they were before the crisis, which makes private labels win market share over branded products. This sets pressure on the producers of these branded products (Unilever, P&G, etc.), which makes these companies focus on cutting costs (Nielsen, 2009). As stated above, companies that have to cut cost may make more use of viral marketing (Readon, 2009). So also in the fmcg industry the use of viral marketing may grow significantly. For companies it is getting harder to stand out in their marketing communications. Marketing is more diversified and diffuse than ever. Consumers are reached by different channels like television, radio, print and internet. In the fmcg industry it is expected that advertisement through the internet channel will grow in the future (Fornari, Grandi & Fornari, 2009). This also could mean more use of viral marketing. The distribution channels of fmcg are changing. Where most of the fmcg were and are sold in grocery stores, other places like gas stations, train stations and airports are turning into true fmcg distribution points. Another trend in the industry is the collaboration of fmcg companies with each other. A good example of this is the collaboration of Philips and Sara Lee (Douwe Egberts): their Senso was a huge success. This partnering occurs also up and down the production chain: buyers and suppliers (non consumers) integrate their IT systems for optimal collaboration on both sides (Pauwels, 2006). 3.3 Viral marketing in practice Online marketing is growing in the fmcg industry. According to Ferguson (2008), viral marketing and online WOM are growing even more rapidly. Although it is difficult to track spending on viral marketing and WOM, the Interactive Advertising Bureau reported that companies spent $ 4.9 billion on the internet channel in the first quarter of 2007, 26 percent more than in the previous year. WOM (of which viral marketing is part of) is leading this growth, 82 percent of the fastest-growing private companies use WOM techniques (Ferguson, 2008). In theory, spreading would be optimal when a small, influential target group is reached with the initial launch of a viral. Reaching many consumers as a company would not be optimal, because people are more influenced by a recommendation by an acquaintance than by a recommendation by a company. In practice this is different. There are different data about how well a viral is spread. A study in 2006 found that only 35 percent of the people living the U.K. receive viral e-mails. On top of this, only 13 percent of that group passed the e-mail on. Other reports are more positive. Another study in 2006 found that only 5 percent of consumers would refuse to share content with friends if there is some kind of branding in it. Over 40 percent of the respondents are likely to forward branded content (Ferguson, 2008). Because of these figures, in practice a company will try to send to a larger target group than would be optimal according to theory. 33 For even better success with virals other tactics are chosen. Practisers of viral marketing agree that the initial launch of a viral has to be addressed to real ardent fans. More effort has to be done than just sending an e-mail. This target group should get real tools to empower them in sharing their enthusiasm. To build customer loyalty, viral marketing has to make use of capturing customer identification through collecting e-mail addresses, signing up the customer for a product promotion etc. Only by this way of actively addressing consumers, the most will be made of viral marketing (Ferguson, 2008). A good example of this is BzzAgent, a company that has 300,000 agent volunteers who receive coupons and sneak previews of new products to try and then share their findings with others. According to their own research, these endorsers (generation zero) share the marketing message with an average of 12 other people (generation one). These 12 people further talk to about four additional people (generation two). How many people this generation talks to is not yet known (Ferguson, 2008). The content of a viral is most often based on a certain emotion (see chapter 2). In practice, fun (or happiness) is the emotion most of the times addressed. On the second place stands surprise. These two emotions are most common for viral marketing in practice (Wilson, 2000). Virals are not suited for every target group. In practice, reaching older people by viral marketing is difficult. Elder people are less familiar with internet than younger people, some elder people do not even use internet. Further the use of internet is different. Younger people use internet to download movies and watch them on YouTube, elder people do not (Ferguson, 2008). Other tactics to make sure a viral marketing campaign will be a success are shown in table 3.1. The launch of a viral in combination with these aspects (mentioning on blogs, posting to community sites, etc.) can make the difference between a successful and unsuccessful campaign. Table 3.1. Tactics that can jump-start a viral marketing campaign (MarketingSherpa, 2007) 34 Another issue in viral marketing practice is that it is not an anchor of marketing strategy. Viral marketing has to be used effectively in combination with other marketing communications to work optimally. It has to be integrated into a whole marketing mix. Concluded from this practical part of how to use viral marketing optimally in practice can be that a viral has to be a part of a greater whole (marketing mix), has to be send to a relatively large product group, the endorsing influencers have to be addressed actively (more than just sending an e-mail), the initial sending has to be to a large product group and tactics have to be used for making a jump-start for the viral. The variables found in theory and practice can be merged into one model containing all the variables. This model will be part of the conceptual model in chapter 4. Before all these variables are given, we can see an overlap in the variables. ‘The viral is properly seeded’ (a variable found in theory) is a bit broad. The practical variables ‘the initial sending is to a large product group’ and ‘a jump-start in the viral is made’ are both about the seeding of a viral as well. The variable ‘viral is properly seeded’ will therefore be replaced by these two. In total, based on (academical) theory and practice, eight variables determine the optimal use of viral marketing: 1. the target group is chosen up front 2. the viral has a strong, extraordinary content 3. viral plays on current or recent events (the timing is right) 4. is part of greater marketing strategy 5. initial sending is to a large target group 6. target group is actively addressed 7. a jump-start in the viral is made 8. influential influencers spread the viral 35 4. Method As stated in the introduction, the research question for this master’s thesis is: what is the optimal use of viral marketing in the fast moving consumer goods industry? This was researched by first making a study of theory and practice concerning viral marketing and by describing the fmcg industry. In chapter 2 the theory about viral marketing was discussed. This chapter concluded on how to use viral marketing optimally. In chapter 3, the fmcg industry was described and the use of viral marketing in practice was briefly described. Some additional elements of how to use viral marketing optimally were found. The elements of chapter 2 and 3 were brought together at the end of chapter 3 and eight variables influencing the optimal use of viral marketing were stated. In this chapter, the method of the research will be stated. From the literature we know the eight variables that determine the optimal working of viral marketing, now we will determine which elements are the important elements so a rank in the variables can be made. The elements determining the optimal use of viral marketing are shown in the conceptual model (see below) in paragraph 4.1. How this conceptual model is researched in practice and what method will be used is stated in paragraph 4.2. Paragraph 4.3 will highlight the operalization of the variables found in chapter 2 and 3 into measurable items in a questionnaire. Paragraph 4.4 will discuss the use of a questionnaire, paragraph 4.5 discusses the virals chosen for this research. Chapter 4 closes with a small introduction in paragraph 4.6 on the method for analysis. 4.1 Conceptual model In this model, all elements determining the optimal use of viral marketing that were found in theory as well as in practice are stated on the left side. In total, eight elements were found that determine the success of a viral marketing campaign. These are the independent variables. On the right side, awareness creation, interest creation and purchase decision are stated. In earlier research is proven viral marketing can lead to these three. These are the dependent variables. Further, the characteristics of the virals are moderating the influence. With these characteristics, the balance of the independent variables is determined. This means that in different virals, the different independent variables (can) have different weights on how strong they are accounted for in a specific viral. In every viral, there is a different mix of weights of independent variables. By researching four different virals, it is possible to determine which of these independent variables are most important. When it is possible to state which independent variables have the most influence in the fmcg industry, the optimal working of viral marketing can be determined for this industry. The second moderating variable is the respondent characteristics. People differ in age, gender, education etc. These differences influence the creation of awareness, intererst or the purchase decision. With this conceptual model, the research method can be chosen. 36 Key elements for optimal Viral Marketing Viral characteristics 1. viral has a clear target group 2. viral has strong, emotional content 3. viral plays on current or recent Awareness creation events 4. viral incorporated in total Interest creation marketing strategy Purchase decision 5. viral’s initial sending is to a large target group 6. actively addressing target group 7. jump-start in viral is made 8. influential consumers spread Respondent Characteristics the viral Figure 4.1 Conceptual model Now the conceptual model is clear, the best research method to investigate the relationship can be chosen. 4.2 Research method According to Zikmund & Babin (2007), four basic research methods exist. These four are: experiment, secondary data study, observation and survey (Zikmund & Babin, 2007, p. 53). For this study, a survey would be most appropriate, because an expirement is not practical, a research based on observation would make it hard to distinguish between the variables (so a rank in variables would be hard to make) and data on these variables in the fmcg industry do not already exist. On top of that, conducting a survey would be very suitable for this research, as I will explain. 4.2.1 Survey This research is based on literature, which states eight variables that determine the optimal use of viral marketing in the fmcg industry. These variables are brought together from different researches in chapter 2 and 3. The next step in this research is to determine which of these variables are more 37 determining in the success of a viral than others. For gaining generalizable results about the rank of these variables, quantitave data is needed. A survey is a good research method to obtain this. The survey in this study will measure the influence of the eight variables on the dependent variables; awareness creation, interest creation and purchase decision. In this way, it is possible to determine the explained variance for each independent variable on each dependent variable. Because this is done on four different virals, a rank in order can be made. The survey conducted is a self-administered, online questionnaire targeted at consumers. A viral is made for consumers to watch and pass along to their relations. So, targeting the questionnaire at consumers would deliver primary data which can serve as a good input for statistical analysis. Because the spreading of this questionnaire will be done by contacting (mostly) first and second grade personal relationships through Hotmail and hyves and sending the questionnaire to all the first year students of the course ‘Practische en Academische Vaardigheden’ (all students Economie & Bedrijfskunde are obliged to take this course, 843 students in total), the majority of the respondents on this questionnaire will probably be between the age of 16 and 28. Because virals are also (often) targeted at young people, this creates a good match. The targeted people for the questionnaire will probably be all Dutch speaking. To account for any language barriers or errors among respondents, the questionnaire will be held in Dutch. For obtaining data in a quick and efficient way, an online questionnaire will be made. This will be done by using a website standardized in conducting online research. The website is called thesistools.com. The advantages of using an online questionnaire are (Zikmund & Babin, 2007, p. 150151): - low cost - low response time - respondent convenience (time independent) - geographic independence - anonymity - standardized questions - visual appeal (the virals are shown by clicking on an url on thesistools.com) Next to the advantages of a questionnaire, disadvantages also exist. The main disadvantage of using a questionnaire is the length. In the questionnaire, four virals are shown. This is the maximum of number for a questionnaire, because filling it out will cost respondents at least 20 minutes of their time. By adding extra virals, the questionnaire would become too long and people would halfway stop filling it out so incomplete data would be gathered. Because at the end of the questionnaire, some respondent characteristics are asked for (these questions should be stated at the end of a questionnaire (Zikmund & Babin, 2007, p. 241)), this would make it impossible to analyze the data. Another disadvantage is the response rate. Conducting an online survey is known for a low response rate. Different methods are used 38 to increase the response rate. First, the questionnaire is send to personal contacts (except for the group ‘Praktische en Academische Vaardigheden (PAV)’) through e-mail and a personal hyves message. Second, the people targeted are triggered to fill out the questionnaire by telling them ‘there are some interesting movies they definitely want to see’. Third, the group of students for PAV, who will receive the e-mail in their student mail, will be contacted by the coordinator of PAV. This is an authority for the first year students. On top of that, in the e-mail send to these students, the students are advised to fill out the questionnaire to get a feeling with what an academically research questionnaire looks like. I expect these factors to increase response rate to get enough respondents. Because movies are upcoming and often used in viral marketing, these are the kind of virals investigated in this research. Viral movies (in this research just stated as ‘virals’) are used more and more by brands to create awareness and interest and to influence the purchase decision of consumers (Phelps et al, 2004). The growing information technologies most people have access to will probably lead to even more growth of viral movies in the future. 4.2.2 Validity and reliability For a research, it is important to be valid and reliable. The subjects internal validity, external validity, construct validity and reliability will be discussed here. Internal validity: exists to the extent that an experimental variable is truly responsible for any variance in the dependent variable (Zikmund & Babin, 2007, p. 211). The construct of the eight variables are based on earlier research. These variables have been proven to influence the optimal working of a viral. Because of this, the internal validity is guaranteed. Construct validity: exists when a measure reliably measures and truthfully represents a unique concept (Zikmund & Babin, 2007, p. 211). Most questions in the questionnaire are obtained from earlier research. These questions therefore already are proven to work. External validity: is the accuracy with which experimental results can be generalized beyond the experimental subjects (Zikmund & Babin, 2007, p. 211). The external validity of this research will be accurate, though limited. As stated above, conducting a survey is the best method to research the rank of the eight variables which makes a viral work optimal in the fmcg industry. The outcomes of this research however, will be based on four virals (because of the maximum limit of time for a questionnaire). To be really generalizable, more virals should be examined by respondents. This is a limitation for this research. However, as many virals are targeted at young people (see chapter 3), they do not differ immensely from each other. Based on the four virals selected (the virals selected are chosen to differ as much as possible, see below), a good representation of all virals has been made. More virals should be researched to verify this, but the results will be generalizable for the greatest parts. Reliability: an indicator of a measure’s internal consistency. Reliability is measured by Cronbach’s α (Zikmund & Babin, 2007, p. 210). In this research, reliability will also tested by using 39 Cronbach’s α. When converging multiple questions that measure the same variable, Cronbach’s α will be calculated so internal consistency will exist. 4.2.3 Accounting for survey errors To make a survey’s accuracy optimal, various forms of survey errors have to be accounted for. The most common errors that are made when conducting a survey are accounted for in this research. I will explain this by giving some examples of how some common made mistakes or errors are accounted for. The social desirability bias makes respondents answer questions by their desire, either conscious or unconscious, to gain prestige or appear in a different social role (Zikmund & Babin, 2007, p. 132). This bias is minimized by choosing for an anonymous online questionnaire. The questions that are most sensitive for social desirability are stated at the end of the questionnaire. An interviewer bias or error occurs when mistakes are made by interviewers failing to record survey responses correctly (Zikmund & Babin, 2007, p. 133). Because this is an online, selfadministrative questionnaire, no interview error can be made. Last, no data-processing errors can be made. Data-processing errors are category or administrative errors that occur because of incorrect data entry, incorrect computer programming, or other procedural errors during data analysis (Zikmund & Babin, 2007, p. 132). This is because the data obtained from the questionnaires is directly imported into an excel file, which can be directly imported into SPSS for further analysis. 4.3 Operationalization of the variables In this part of the research, we will make our research question measurable by operationalization. The research question is: what is the optimal use of viral marketing in the fast moving consumer goods industry? Before I make this question researchable, I will first explain what is meant by the concept ‘optimal viral marketing’. A concept is a generalized idea that represents something of meaning (Zikmund & Babin, 2007, p. 203). The concept ‘fast moving consumer goods industry’ was already explained in chapter 3, the concept ‘viral marketing’ in chapter 2. Marketing is all about getting results. This also holds for viral marketing. Viral marketing is used for creating awareness, creating interest and influencing the purchase decision of consumers in a positive way. Therefore, by optimal viral marketing in this research, the viral marketing is meant that creates the most awareness and interest and influences the purchase decision of consumers in the most positive way. Based on chapter 2 and 3, we can state that the construct optimal viral marketing is measured by eight variables (see the conceptual model). In this research therefore, we have to measure the influence of these eight variables on the three dependent variables: awareness creation, interest creation and purchase decision and account for the moderating variables of respondent characteristics to measure 40 optimal viral marketing in the fmcg industry. We will now transform the variables into measurable questions. 4.3.1 The independent variables Independent variable one states that a viral has to have a clear target group before making a viral. To measure this, respondents will be researched for how well they belong to the target group. The variance of these answers will be compared by the variance measured in the dependent variables. The questions stated to measure this are stated below (all questions are in Dutch, see above). When a Likert-scale is used, one means ‘zeer mee oneens’ and five means ‘zeer mee eens’. This holds for all of the variables. - Ik kan me identificeren met dit merk (Likert scale 1-5) - Dit merk past bij mij als persoon (Likert scale 1-5) The second independent variable states that a viral has to have a strong emotional content. Two questions are asked about this variable. - Welke emotie voel je het sterkst bij dit filmpje? Kies uit woede, vreugde, verdriet, angst, verbazing en afschuw (only one choice possible). - Ik voel deze emotie heel sterk (Likert scale 1-5) The first question asks repsondents which of the six basic emotions (happiness, sadness, surprise, disgust, anger and fear) they feel the strongest by watching a viral, the second asks them how strong they feel this emotion. The first question is asked to see if one emotion works better than another and the second question determines how well the viral plays on emotion. Independent variable three measures how well a viral plays on current or recent events. Because the virals chosen for this research are not launched recently, the question is formulated as follows: - Dit filmpje speelde in (maand en jaar) duidelijk in op actualiteiten (Likert scale 1-5) Some people may have difficulties remembering events from a few years back. Though, the big events are remembered by most people, and it is these big events that the virals play on. The fourth independent variable states that a viral has to be incorperated in the total marketing strategy. This is investigated by the question: - Ik heb naast dit filmpje op andere manieren van de promotie van dit merk gehoord of gelezen, bijvoorbeeld door tv-reclame, radio en magazines (Likert scale 1-5) The effect of a viral is better when consumers have heard of a brand / product / campaign through multiple marketing channels. Fifth, the independent variable: viral’s initial sending is to a large product group. This is researched by asking respondents: - Hoeveel mensen ken je die dit filmpje al hebben gezien? Kies uit: niemand, 1 of 2, 3 of 4, 5 of 6, meer dan 6 (only one choice possible). 41 Independent variable six states that the target group or consumers have to be actively addressed. This means that these consumers have to be involved and pursued to search more information about a brand or product. Two questions are stated : - Als het bedrijf, gepromoot in het filmpje, mijn e-mail adres zou vragen zou ik deze geven (Likert scale 1-5) - Als het bedrijf, gepromoot in het filmpje, een link zou plaatsen om meer informatie te geven zou ik hierop kijken (Likert scale 1-5) These two questions are asked because asking for an e-mail adres or referring to a website are common methods to use to involve customers after showing the viral. The seventh independent variable states that a jump-start for a viral should be made to make it successful. This can be done by posting about it on blogs and community sites or publishing about it in a specialist journal, pressed as well as online (see chapter 3). - Ik heb over dit filmpje al gelezen of gehoord via: blog, community sites (hyves / facebook / youtube), gedrukte vakbladen, online vakbladen (able to choose multiple options). The eighth and last independent variable states that the more influential the addressed person is for a particular brand or product, the better effect it will have on the success of a viral. Above, characteristics of what make a person influential are stated from the litarature (see chapter 3). Different questions, based on chapter 3, therefore are stated. Only the first question is asked for every movie, the other questions are asked at the end of the questionnaire. - Ik vind dit een prachtig merk (Likert scale 1-5) - Ik kom op voor mijn eigen mening, rechten en standpunten (Likert scale 1-5) - Ik wil nieuwe producten altijd als eerste hebben (Likert scale 1-5) - Ik heb interesses op meerdere gebieden (Likert scale 1-5) - Sociale contacten zijn een belangrijk deel van mijn leven (Likert scale 1-5) - Mensen stellen veel vertrouwen in mij (Likert scale 1-5) 4.3.2 The dependent variables The first dependent variable is awareness creation. The creation of awareness is measured by these two follow up statements: - Ik was al goed bekend met dit merk (Likert scale 1-5) - Na het zien van dit filmpje ben ik bewuster geworden van dit merk (Likert scale 1-5) By asking respondents how well they already knew the brand and how more aware they have become, awareness creation can be measured. The second dependent variable is interest creation. Interest follows awareness in the process of a consumer adapting to a new brand or product (see chapter 3). - Na het zien van dit filmpje heb ik (meer) interesse in dit merk (Likert scale 1-5) 42 Because interest follows awareness, only those people who state they are now (more) aware of the brand, will state that they are now interested in the brand. The interest creation by the viral therefore will expectedly be lower than the awareness creation. The third and last dependent variable is the purchase decision. This should follow interest according to theory and is measured by stating: - Na het zien van dit filmpje zou ik een product van dit merk willen kopen (Likert scale 1-5) - Na het zien van dit filmpje ga ik een product van dit merk kopen (Likert scale 1-5) The purchase decision follows interest of a consumer and should therefore be measured lower than interest creation (and therefore lower than awareness creation as well). 4.3.3 The respondent characteristics To research what variables make a viral work optimally, the respondent characteristics have to be accounted for. These respondent characteristics are not measured in one universal way in other research (Alwin & Krosnick, 1991). I therefore chose a basic way in researching these characteristics (Alwin & Krosnick, 1991): - Leeftijd (fill in) - Opleiding. Kies tussen geen, <MBO, MBO, HBO, Universitair - Geslacht (male or female) - Woonsituatie. Kies uit: bij ouders, zelfstandig, samenwonend (relatie), samenwonend (met kinderen) (only one choice possible) The questions about the independent variables are (except for the most questions about ‘influential consumers spread the viral’ stated for each viral movie. The dependent variables are measured for every viral as well. Because the characteristics of respondents are independent of the viral movies, these questions are only asked once. 4.4 The questionnaire The variables are now operational. The questions or statements are made concerning the different variables. Now these are clear, they have to be made into a questionnaire. In this paragraph, a brief explanation will be given about how and why the questions and statements are formulated this way. Zikmund & Babin (2007) describe multiple questionnaire design criteria. These criteria have to be accounted for to maximalize accuracy of a questionnaire. Pitfalls in questions that should be avoided are: complexity, leading, loading, ambiguity, doubl-barreled items and making assumptions (Zikmund & Babin, 2007, p. 236-240). Questions in this questionnaire are stated while examining them avoiding these pitfalls. Further, in a questionnaire, the composition is very important. Different compositions of the same questions can lead to different answers (Zikmund & Babin, 2007, p. 241). The composition is as 43 follows: the questionnaire starts with easy questions and ends with more difficult questions. Demographic and classifatory questions are stated at the end of the questionnaire, just like the personal questions (measuring the influence of a consumer). General questions are stated before specific ones. Composition adapted from (Zikmund & Babin, 2007, p. 241-244). See for the questionnaire appendix A. 4.5 The virals In this research, four different viral movies are chosen to determine the influence of the different variables. The reason to take four virals is because this is the maximum for an online questionnaire due to time. When four viral movies are used, at least 20 minutes is necessary for completing the questionnaire. Asking respondents more of their time would lead to incomplete questionnaires and thus incomplete data (see also above). Though four is a limited number, the results will give a good answer on how to use viral marketing optimally in the fmcg industry. All four viral movies are tested on the same variables using the same questions. The movies chosen for this research are based on the eight variables. The virals eventually used in the questionnaire are the virals that are most diverse when examining the brands and products they represent and the target group they apply to. Further, these virals have (relatively) many hits. This makes the virals successful when these virals also influence the three dependent variables in a positive way. This lead to these four virals: The first viral movie is that of Sprite Zero: in this viral is shown how a boy that is sleeping in a chair by the pool is launched by a rubber band pulled by his friends. The sleeping boy gets launched way too far and the movie imputes that he is hurt bad. The message that follows is: ‘Friendship is overrated. Sprite Zero’. This brand is targeted at young people, probably between 12 and 21 and has a surprising content. The second viral movie is that of Dove. The movie is called Dove Evolution and shows a normal looking woman transformed by the use of make up and photo shopping into a beautiful model on a billboard. The message that follows is ‘no wonder our perception of beauty is distorted’. The commercial is part of Dove’s real beauty, self-esteem campaign. Dove aims at women ranging from 2040 years old. The viral has a shocking content. Third, a viral of Captain Morgan is shown. This viral is about a man who is supposed to be at family of his wife. He told her he is sick and can not come. When she calls him while he is supposed to be in bed, he is in a bar. All the people in the bar are helping the man out by pretending to be different tv channels by making weird noises or comments. The viral ends by the question: ‘Got a little captain in you?’ Captain Morgan aims at young men. The viral movie has a funny content. The last viral movie is from Wilkinson. This viral is about ‘fight for kisses’. It is about a baby that is training in the basement of its own house to become strong and gain fighting skills. Before, he had al momma’s attention because of the softness of his skin, but now his father is using Wilkinson shaving blades, his father has a soft skin as well. Now his father has got the attention of momma, the 44 baby wants to win it back. The viral ends by the baby challenging his father to fight. Wilkinson aims with this commercial on the family: the game this viral refers to is based on children challenging their father (parents). This viral has a funny content. 4.6 Method for analysis To answer what makes viral marketing work optimally in the fmcg industry, a rank of the eight different variables has to be made. This is the main analysis to be made in this research. To measure this, multiple regression analyses will be made. The eight variables will be (where necessary merged) loaded on each dependent variable separately. This will be done for all four movies. In total, 3 * 4 = 12 regression analyses will be made. The outcomes of these analyses show how much variance in the dependent variable is explained by the separate independent variables and will therefore give a clear view of how important each variable is in determining optimal working of viral marketing in the fmcg industry. These outcomes will be compared to each other to find a rank of the variables. In this ranking, the effectiveness of the four different virals will be accounted for. This is done because in more effective virals, the determining variables (the independent variables that explain the most variance) should be weighed more than determining variables in a less effective viral. The effectiveness of the different virals (how well dit they score on awareness creation, interest creation and purchase decision?) will also be accounted for when making the rank. More on how this is exactly done in chapter 5. 45 5. Research results In this part of the research, the research results are discussed. The data necessary to make an analysis of what variables are most important in optimal viral marketing in the fmcg industry are obtained. The outcomes of the analyses are described here. In paragraph 5.1, a description of the sample will be given. In paragraph 5.2, multiple questions measuring one variable are merged (reliabilities of these mergers are given by Cronbach’s Alpha). Next, chapter 5.3 discusses the creation of awareness, the creation of interest and the influence on the purchase decision of the different virals. Paragraph 5.4 is about the regression analyses made. Last, paragraph 5.5 discusses ranking the eight variables. 5.1 Sample Respondents for this online research were found by asking people through e-mail and Hyves. In total, 1923 persons received an e-mail in which I requested to help me graduate. This e-mail was send in different ways, through different media: Hyves (my 354 ‘friends’), Hotmail (468 contacts were selected), the e-mail of my parents (258 people) and the e-mail of my supervisor for ‘Praktische en Academische Vaardigheden’ (843 first year students ‘Economie en Bedrijfskunde’). In total, 385 people filled out the questionnaire, of which 338 were complete and useful for research. This is a response rate of 17.6% (for the usable data), a pretty high percentage for an online questionnaire. The explanation for this is probably because many respondents are acquintances. Further, as stated above, the coordinator of ‘Praktische en Academische Vaardigheden’ sent an e-mail to all first year students. He is an authority for these students. The descriptives of the sample are stated below. Respondents 338 respondents Gender 184 males 154 females Age Range: 17-63 Mean: 23.5 Std. deviation: 8.31 Median: 21 Mode: 18 None: 0 < MBO: 4 MBO: 20 HBO: 60 University: 254 Living situation With parents: 144 On itself: 136 Together (relationship): 36 Together (with children): 22 Table 5.1. Sample characteristics Education 46 5.2 Merging the variables In this research, some variables are measured using multiple questions or statements. To make a regression analysis, most of these questions or statements that measure one variable have to be merged. Merging these questions or statements is done in this paragraph by using Cronbach’s Alpha. Only the independent variable ‘viral has a strong, emotional content’ and the dependent variable ‘awareness creation’ are not merged. This will be explained at the end of this paragraph. The independent variables that have to be merged are ‘viral has a clear target group’, ‘viral is actively addressing the target group’ and ‘influential consumers spread the message’. These three variables were measured by respectively 2, 2, and 6 statements. Results are in the table below. Independent variable Number of statements Cronbach’s Alpha / viral Viral Viral Viral Viral 1 2 3 4 Clear target group 2 0.908 0.955 0.922 0.937 Actively addressing target group 2 0.609 0.816 0.747 0.845 Influential consumers spread the viral 6 0.467 0.494 0.458 0.479 Table 5.2. Cronbach’s Alpha for each viral for merged independent variables In general, a Cronbach’s Alpha > 0.6 is accepted as high enough to merge statements or questions reliably (Zikmund & Babin, 2007, p. 210). As shown in table 5.2, the variable ‘influential consumers spread the viral’ does not obtain an Alpha high enough to be marked as reliable. Though the variables that make up this variable are based on earlier research (Richardson & Domingos, 2002; Subramani & Rajagopalan, 2003), the statements to measure these variables are probably not formulated accurately enough (see limitations for further explanation). For each viral holds, that when one or two of the original six statements were removed, the Cronbach’s Alpha would be higher than 0.6. Of the dependent variables, only the variable ‘purchase decision’ has to be merged. For this variable, two statements were made, both with a Likert scale of 1-5. The Cronbach’s Alpha here is: Dependent variable Purchase decision Number of statements 2 Cronbach’s Alpha / viral Viral Viral Viral Viral 1 3 4 2 0.850 0.923 0.947 0.948 Table 5.3. Cronbach’s Alpha for each viral for the merged dependent variable ‘purchase decision’ Two other variables were measured using multiple statements or questions. The independent variable ‘viral has a strong, emotional content’ had two questions, the first asking what emotion respondents felt 47 the strongest when they had viewed a viral, the second was a statement to determine how strong they felt this emotion. Because these two questions do not measure the same, they were not merged, only the statement was used for regression analysis. With the question which emotion was felt the most, the modus for each viral was calculated (for viral 1 and 2, the emotion ‘surprise’ was felt the most (viral 1: 52%, viral 2: 66%), for viral 3 and 4, the emotion ‘hapiness’ was felt the most (viral 3: 88%, viral 4: 66%)). For the dependent variable ‘awareness creation’, the first two statements were used as an introduction to the last statement. Therefore, for this dependent variable only the third statement was used for regression analysis. 5.3 The influence of virals on the dependent variables Three dependent variables exist in this research. These three are: awareness creation, interest creation and purchase decision. Every viral has (or should have) an influence on these three. For this research, the influences of four virals are tested on these three variables (so twelve regression analyses have been made, see the next paragraph). In this paragraph, the effect of the virals on the dependent variables will be presented. Awareness creation is the first stage of getting a consumer to adapt to a brand or product. A good viral would create this. For the four virals chosen for this research, the following awareness creation (on a scale from 1-5) was measured: Viral Mean awareness created Standard error Standard deviation Sprite Zero 1.93 0.054 0.993 Dove 3.07 0.060 1.098 Captain Morgan 2.60 0.065 1.200 Wilkinson 2.36 0.061 1.114 Mean scores 2.49 0.060 1.101 Table 5.4. Awareness created by the different virals As shown in the table, the viral of Dove created the most awareness. For awareness creation, this viral is the best of these four. After that, second was Captain Morgan, third was Wilkinson and last Sprite Zero. The mean scores of these four are significantly different (confidence interval of 99%). Interest creation is the second stage of getting a consumer to adapt to a brand or product. A good viral would create this, though probably not as strong as awareness. For the four virals chosen for this research, the following interest creation (on a scale from 1-5) was measured: Viral Mean interest created Standard error Standard deviation Sprite Zero 1.76 0.049 0.900 48 Dove 2.82 0.066 1.216 Captain Morgan 2.44 0.067 1.232 Wilkinson 2.07 0.058 1.059 Mean scores 2.27 0.060 1.102 Table 5.5. Interest created by the different virals As shown in the table, the viral of Dove created the most interest. For interest creation, this viral is also the best of these four. After that, second was Captain Morgan, third was Wilkinson and last Sprite Zero. The mean scores of these four are significantly different (confidence interval of 99%). The final stage of getting a person adapted to a brand or viral is the purchase decision. A good viral would influence this in a positive way. For the four virals chosen for this research, the following influence on purchase decision (on a scale from 1-5) was measured: Viral Mean purchase decision Standard error Standard deviation Sprite Zero 1.58 0.038 0.694 Dove 2.30 0.055 1.008 Captain Morgan 1.93 0.055 1.015 Wilkinson 1.75 0.048 0.880 Mean scores 1.89 0.049 0.899 Table 5.6. Purchase decision affected by the different virals. As shown in the table, the viral of Dove created the most awareness. For influencing the purchase decision of customers, this viral is also the best of these four. After that, second was Captain Morgan, third was Wilkinson and last Sprite Zero. The mean scores of these four are significantly different (confidence interval of 99%, only the difference between Captain Morgan and Wilkinson can be stated with a 95% confidence interval). Taking together these three different tables with the outcomes of the virals on the dependent variables, we can see that the viral of Dove has the most effect on all three and the other ranks are the same as well. If we had to rank the virals, it would be: Dove, Captain Morgan, Wilkinson and Sprite Zero. The differences in effectiveness will be accounted for in paragraph 5.5, when the variables are ranked. Last, from the data can be obtained that viral marketing leads mostly to awareness for a brand or product. We can see that the average awareness created by the virals is higher than the average interest created (this is significant with a 99% confidence interval). The average interest created in turn is significantly higher (99% confidence interval) than the purchase decision is affected. 49 5.4 The regression analyses To examine which variables in viral marketing are most important, the next step in this research is to find out which variables explain most variance in awareness creation, interest creation and the influence of a viral on the purchase decision. This is done by regression analyses for each of the four virals on each of the three dependent variables. This makes a total of 12 regression analyses. The results of these regression analyses are given for each dependent variable separately. For the total table of each regression analysis, see appendix B. 5.4.1 Awareness creation For awareness creation, four regression analyses have been made (one for every viral). These outcomes are given in table 5.7. In this table, the standardized β’s are given for all the independent variables, for each viral. The significance of each of these β’s is given. Respondent characteristics are also shown. Variable Standardized β (significance) Viral 1 Viral 2 Viral 3 Viral 4 0.284 (.000) 0.176 (.002) 0.297 (.000) 0.283 (.000) 0.108 (.018) 0.041 (.201) 0.100 (.027) 0.160 (.001) 0.178 (.001) 0.034 (.208) 0.055 (.131) 0.122 (.008) -0.112 (.024) 0.219 (.000) -0.055 (.196) 0.103 (.018) -0.243 (.000) -0.201 (.001) -0.033 (.278) -0.015 (.397) 0.208 (.000) 0.357 (.000) 0.183 (.001) 0.193 (.000) 0.004 (.471) 0.230 (.000) 0.143 (.003) -0.009 (.485) -0.021 (.342) .095 (.026) 0.140 (.004) 0.051 (.169) Age* -0.126 (.070) -0.125 (.044) -0.261 (.001) 0.007 (.464) Gender* -0.025 (.325) -0.158 (.004) 0.045 (.213) 0.139 (.011) Education* -0.062 (.140) 0.087 (.048) -0.031 (.280) 0.045 (.201) Living situation* 0.104 (.079) 0.034 (.295) 0.177 (.004) -0.093 (.083) Viral has a clear target group Viral has strong, emotional content Viral plays on current or recent events Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target group A jump-start in the viral is made Influential consumers spread the viral Table 5.7. Variance in awareness creation explained by different independent variables and respondent characteristics (these moderating variables are marked by a *) 50 5.4.2 Interest creation For interest creation, the same regression analyses were conducted. Again, four regression analyses have been made (one for every viral). These outcomes are given in table 5.8. In this table, the standardized β’s are given for all the independent variables, for each viral. The significance of each of these β’s is given. Respondent characteristics are also shown. Variable Standardized β (significance) Viral 1 Viral 2 Viral 3 Viral 4 0.381 (.000) 0.295 (.000) 0.287 (.000) 0.406 (.000) 0.023 (.319) 0.104 (.007) 0.068 (.048) 0.045 (.123) 0.078 (0.063) -0.018 (.345) 0.055 (.088) 0.161 (.000) -0.080 (.072) 0.161 (.000) -0.047 (.137) 0.084 (.012) -0.201 (.001) -0.207 (.000) -0.040 (.191) 0.036 (.210) 0.257 (.000) 0.498 (.000) 0.411 (.000) 0.360 (.000) -0.018 (.379) 0.154 (.001) -0.026 (.266) -0.043 (.165) 0.009 (.426) 0.060 (.076) 0.112 (.004) -0.010 (.407) Age* -0.047 (.285) -0.032 (.309) -0.143 (.013) -0.005 (.463) Gender* -0.127 (.008) -0.201 (.000) -0.061 (.093) -0.035 (.226) Education* 0.083 (.068) 0.100 (.014) 0.094 (.015) 0.066 (.057) Living situation* 0.018 (.400) -0.001 (.492) 0.035 (.259) -0.069 (.090) Viral has a clear target group Viral has strong, emotional content Viral plays on current or recent events Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target group A jump-start in the viral is made Influential consumers spread the viral Table 5.8. Variance in interest creation explained by different independent variables and respondent characteristics (these moderating variables are marked by a *) 5.4.3 Purchase decision For the influence of the variables on the purchase decision of customers, also four regression analyses have been made. These outcomes are given in table 5.9. In this table, the standardized β’s are given for all the independent variables, for each viral. The significance of each of these β’s is also given. Respondent characteristics are also shown. 51 Variable Standardized β (significance) Viral 1 Viral 2 Viral 3 Viral 4 0.432 (.000) 0.356 (.000) 0.272 (.000) 0.382 (.000) 0.037 (.205) -0.004 (.461) 0.031 (.251) -0.061 (.088) 0.172 (.000) 0.018 (.335) 0.129 (.002) 0.110 (.007) 0.022 (.330) 0.181 (.000) 0.020 (.343) 0.054 (.107) -0.180 (.001) -0.201 (.000) -0.116 (.013) 0.021 (.201) 0.305 (.000) 0.518 (.000) 0.325 (.000) 0.390 (.000) 0.029 (.295) 0.059 (.498) 0.068 (.079) 0.001 (.495) -0.077 (.046) -0.011 (.385) 0.140 (.002) 0.015 (.374) Age* 0.055 (.233) 0.058 (.161) -0.075 (.152) 0.026 (.351) Gender* -0.099 (.020) -0.022 (.321) -0.007 (.446) 0.031 (.276) Education* 0.052 (.150) 0.078 (.031) -0.010 (.419) 0.025 (.299) Living situation* -0.097 (.068) -0.005 (.461) 0.031 (.307) -0.094 (.057) Viral has a clear target group Viral has strong, emotional content Viral plays on current or recent events Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target group A jump-start in the viral is made Influential consumers spread the viral Table 5.9. Variance in purchase decision explained by different independent variables and respondent characteristics (these moderating variables are marked by a *). As stated above, these twelve regression analyses made, explain the influence of a variable on the effectiveness for each of the four virals. To make a realistic ranking of which variables are most important, the effectiveness of each viral has to be accounted for as well. This is done in paragraph 5.5, were the independent variables will actually be ranked. 5.5 Ranking the variables In this part, the outcomes of paragraph 5.3 and 5.4 will be taken together to get to a ranking of the independent variables. In paragraph 5.3, the effectiveness of each viral was found. In paragraph 5.4, the effect of each independent variable on each viral for each dependent variable, was found. Combining these two paragraphs will give a ranking of the importance of the variables that determine the optimal working of viral marketing in the fmcg industry. 52 In determining which independent variables are most important, the following method is used: the standardized β’s of each independent variable is multiplied by the effectiveness of a viral to obtain the best view on how important each independent variable is. In this way the effect of a viral is accounted for when determining what variables are the most important ones. This is done for each dependent variable separately. This method can best be explained by using an example. If we look at how important the independent variable ‘viral has a clear target group’ is on the dependent variable ‘awareness creation’, we calculate this for each viral separately. For the viral of Sprite Zero for example, 0.284 * 1.93 = 0.55. This calculation is made for each viral (four times). These four scores are counted up in the column ‘Total’. Based on these total scores for each independent variables, a ranking can be made for each of the dependent variables. In 5.5.4, these scores are counted up to determine a total ranking for what variables influence the optimal use of viral marketing the most. The numbers obtained from these calculations are used on interval level, not on ratio. This means that the differences in these scores are used to get a good insight on how the eight variables found in chapter 2 and 3 are influencing optimal viral marketing relatively to each other. 5.5.1 Awareness creation For awareness creation, the following results were obtained: Independent variables Sprite Zero Dove Captain Morgan Wilkinson Total Viral has a clear target group 0.55 0.54 0.77 0.67 2.53 0.21 0.13 0.26 0.38 0.97 0.34 0.10 0.14 0.29 0.88 -0.22 0.67 -0.14 0.24 0.56 -0.47 -0.62 -0.09 -0.04 -1.21 group 0.40 1.10 0.48 0.46 2.43 A jump-start in the viral is made 0.01 0.71 0.37 -0.02 1.06 -0.41 0.29 0.36 0.12 0.37 Viral has strong, emotional content Viral plays on current or recent events Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target Influential consumers spread the viral Table 5.10. Ranking the independent variables on their influence on awareness creation 53 From this, we can make up the following rank for the independent variables on awareness creation (from most to least important): viral has a clear target group, viral is actively addressing target group, a jumpstart is made, strong emotional content, viral plays on current or recent events, viral is incorporated in total marketing strategy, influential consumers spread the viral and the initial sending is to a large target group. 5.5.2 Interest creation For interest creation, the following results were obtained: Independent variables Sprite Zero Dove Captain Morgan Wilkinson Total Viral has a clear target group 0.67 0.83 0.70 0.84 3.04 0.04 0.29 0.17 0.09 0.59 0.14 -0.05 0.13 0.33 0.55 -0.14 0.45 -0.11 0.17 0.37 -0.35 -0.58 -0.10 0.07 -0.96 group 0.45 1.40 1.00 0.75 3.60 A jump-start in the viral is made -0.03 0.43 -0.06 -0.09 0.25 0.02 0.17 0.27 -0.02 0.44 Viral has strong, emotional content Viral plays on current or recent events Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target Influential consumers spread the viral Table 5.11. Ranking the independent variables on their influence on interest creation From this, we can make up the following rank for the independent variables on interest creation (from most to least important): viral is actively addressing target group, viral has a clear target group, strong emotional content, viral plays on current or recent events, influential consumers spread the viral, viral is incorporated in total marketing strategy, a jump-start is made and the initial sending is to a large target group. 5.5.3 Purchase decision For purchase decision, the following results were obtained: 54 Independent variables Sprite Zero Dove Captain Morgan Wilkinson Total Viral has a clear target group 0.68 0.82 0.52 0.67 2.69 0.06 -0.01 0.06 -0.11 0.00 0.27 0.04 0.25 0.19 0.75 0.03 0.42 0.04 0.09 0.58 -0.28 -0.46 -0.22 0.08 -0.90 group 0.48 1.19 0.63 0.68 2.98 A jump-start in the viral is made 0.05 0.14 0.13 0.00 0.31 -0.12 -0.03 0.27 0.03 0.15 Viral has strong, emotional content Viral plays on current or recent events Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target Influential consumers spread the viral Table 5.12. Ranking the independent variables on their influence on the purchase decision From this, we can make up the following rank for the independent variables on purchase decision (from most to least important): viral is actively addressing target group, viral has a clear target group, viral plays on current or recent events, viral is incorporated in total marketing strategy, a jump-start is made, influential consumers spread the viral, viral has a strong emotional content and the initial sending is to a large target group. 5.5.4 Overall Above, the importance of the eight independent variables are calculated. These calculations resulted, for each of the three dependent variables, in a column of total scores. For viral marketing to work optimally, a viral has to influence all three the variables as much as possible. For this, the total columns of the three dependent variables are counted up to derive at a total score for each variable. These scores indicate how the eight variables have to be ranked, and how the differences between the virals are. The results are stated in the table below (table 5.13). Independent variables Awareness creation Interest creation Purchase Decision Total Viral has a clear target group 2.53 3.04 2.69 8.27 0.97 0.59 0.00 1.57 Viral has strong, emotional content 55 Viral plays on current or recent events 0.88 0.55 0.75 2.19 0.56 0.37 0.58 1.51 -1.21 -0.96 -0.90 -3.06 2.43 3.60 2.98 9.02 1.06 0.25 0.31 1.63 0.37 0.44 0.15 0.96 Viral is incorporated in total marketing strategy Viral’s initial sending is to a large target group Viral is actively addressing target group A jump-start in the viral is made Influential consumers spread the viral Table 5.13. Ranking the independent variables on their total influence on viral marketing in the fmcg industry From this table, we can make up the final ranking of the variables (from most important to least important): 1. The viral is actively addressing the target group (score of 9.02) 2. The viral has a clear target group (score of 8.27) 3. Viral plays on current or recent events (score of 2.19) 4. A jump-start in the viral is made (score of 1.63) 5. Viral has a strong, emotional content (score of 1.57) 6. Viral is incorporated in total marketing strategy (score of 1.51) 7. Influential consumers spread the viral (score of 0.96) 8. Viral’s initial sending is to a large product group (-3.06) These results will be discussed in the next chapter. 56 6. Discussion The research results described in chapter 5 will be discussed here. This will be done by first looking at the scores of the virals on awareness creation, interest creation and purchase decision (from paragraph 5.3). Then, the independent variables will be discussed. What is their influence on optimal viral marketing in the fmcg industry (from paragraph 5.4 and 5.5)? This chapter closes by some noteworthy findings in the influence of respondent characteristics. 6.1 The virals Though the results for the virals are straightforward, a short discussion will be held here. As shown in paragraph 5.3, the four virals researched have a different influence on the three dependent variables. The viral of Dove scored best on all three, followed by Captain Morgan, Wilkinson and Sprite Zero respectively. These differences were found on all three dependent variables an were all significant. It is difficult to say if it is normal that when a viral scores well on one dependent variable, it will score well on the other two dependent variables. For these four virals this is the case. Further research would be needed to verify this statement. In the viral of Dove and Sprite Zero, surprise was the most felt emotion. For Captain Morgan and Wilkinson, it was happiness. So the virals with a surprise effect were ranked 1 and 4, while the virals containing happiness were ranked 2 and 3. From this we can say (though to be sure, more virals should be researched) that it is not one emotion that works best in viral marketing. Though, what can be stated is that surprise and happiness are, like stated in chapter 3, the most chosen emotions for a viral. So these findings match with the literature. Last, from the data can be obtained that viral marketing leads mostly to awareness for a brand or product. We can see that the average awareness created by the virals is higher than the average interest created (this is significant with a 99% confidence interval). The average interest created in turn is significantly higher (99% confidence interval) than the purchase decision is affected. From this we can draw, as we already expected, that viral marketing is best for creating awareness for a brand or product. The scores of the virals are used in paragraph 5.5 to make the most accurate analysis of the influences of the eight independent variables. A variable that scores well in a viral that has a lot of influence on the dependent variables should be rated higher than a variable that scores well in a viral that has not much influence on the dependent variables. The outcomes of the influence are discussed next. 6.2 The independent variables In this part, the interpretation of the results in paragraph 4.4 and especially 4.5 are discussed. This will be done by discussing the results of each variable separately. This paragraph finishes with an overview of the ranking of the variables. 57 6.2.1 A clear target group A clear target group when designing a viral appears to be an important variable for all three dependent variables. When a clear target group is established when making a viral, this will lead to far better results than when this is not done. For all the virals, a clear target group scored well. Overall, a clear target group when designing a viral is a very important aspect of optimal viral marketing (with an overall score of 8.27). 6.2.2 A strong, emotional content The variable ‘viral has a strong, emotional content’ has most influence on awareness creation. Only in the Dove viral, this was not found significantly. Further, for interest creation, a strong emotional content is significantly important in two of the four virals (Dove is included in these two). A strong emotional content does not have a real influence on the purchase decision. For this variable, the influence is there, but it is not as strong as a clear target group. For creating awareness (and interest), this variable should definitely be accounted for, when trying to influence the purchase decision of consumers, a strong emotional content is not important. So if a viral is used for creating awareness (what most virals are used for), a strong emotional content is important. Overall, when we weigh the three dependent variables the same, a strong emotional content is moderately important (with an overall score of 1.57). 6.2.3 Plays on current or recent events This variable scores well on all three dependent variables. Therefore, the overall score of this variable is relatively high (ranked third with a score of 2.19). From the data we can see that next to awareness creation and interest creation, this variable scores best on influencing the purchase decision (three significant positive results, opposed to two and one for awareness creation and interest creation respectively). Where other variables decrease in influence when moving more to influencing the purchase decision, this variable increases. This variable therefore is especially useful when a viral is used for influencing the purchase decision. 6.2.4 Incorporation in total marketing strategy Incorporation is in the literature seen as an important aspect determining the success of a viral. In this research, the total influence of incorporation in the total marketing strategy is moderately effective. However, some noteworthy results were obtained. For Dove, the most successful viral, incorporation in the total marketing strategy has a relative great and positive, significant influence. For the Sprite Zero commercial, this variable has a negative impact. Thus, what may make Sprite Zero less effective and Dove very effective, is the incorporation in the marketing strategy. It is difficult to say if this really is true, though it may make this variable more important than the total score of 1.51 would suggest. 58 Further, incorporation in the total marketing strategy is most important in creating awareness and least important in influencing the purchase decision. 6.2.5 Initial sending is to a large target group As we can see in paragraph 5.4, the initial sending to a large target group has a negative impact on the dependent variables (overall score of -3.06). This can best be explained by looking back at the literature. In theory (see chapter 2), the initial sending of a viral should be to as less consumers as possible, because when a consumer receives the viral from a friend, the viral will have more impact than when received by the firm that is marketed. That effect is shown here. The more people already received this viral by a company, the less effect it has. Therefore, a viral its initial sending should be to the least amount consumers possible, but still make this viral a success by having many consumers viewing it. This is a trade-off with practice. In practice, managers want to initially send the viral to many consumers (in the target group) to make sure many consumers view it. For each viral therefore, an optimum has to be estimated for the initial sending. The viral has to be send to enough consumers so eventually many consumers will see it, but not too many so the optimal effect will be negatively influenced. When a viral is very strong, the company does not have to send it to many consumers. We can see this from this research. For Dove, this variable has the strongest negative influence, while this is the best viral. When a viral is not that strong, the initial sending should be as big as possible. This estimation can probably best be based on a pre-test. 6.2.6 Actively addressing target group Next to a clear target group, actively addressing the target group is the most important variable for optimal viral marketing in the fmcg industry. This variable scores high on all of the three dependent variables, especially high on the Dove viral. All these findings are significant with a significance level of 99%. We can therefore state that when consumers are actively addressed by asking their e-mail, linking the viral to a website or other ways to actively address them, a viral will be much more successful (with an overall score of 9.02). 6.2.7 A jump-start is made For a viral to succeed, a jump-start should be made, according to the literature. However, in this research making a jump-start with a viral is proven to be moderately important. Only on the creation of awareness, a jump-start can be useful. What can be noted further, is that for the Dove viral this variable scored significantly better than for other virals. Overall, when we weigh the three dependent variables the same, a strong emotional content is moderately important (with an overall score of 1.63). 59 6.2.8 Influential consumers spread the viral The last variable is the influence of consumers who spread the viral. This variable proved to be somewhat important for all three dependent variables. However, for influencing the purchase decision, this variable has a negative, significant impact in the Sprite Zero viral. This may suggest that for the purchase decision, the influence of consumers does not matter. The influence of consumers is more important in creating awareness and interest. This makes some sense: according to theory, the more influential a person, the more chance his or her acquaintances will view the viral. Because the person they receive the viral from is influential, they are more interested at first. However, their purchase decision is not influenced by their acquaintance. Overall, when we weigh the three dependent variables the same, a strong emotional content is moderately important (with an overall score of 0.96). Overall, two variables really step out in their influence on the optimal use of viral marketing. The most important variables for optimal viral marketing in the fmcg industry are: having a clear target group when creating a viral and actively address your target group. These two variables should be at the base of each viral that is created. Further, some variables score moderate on their influence on the optimal use of viral marketing. These variables are: viral plays on current or recent events, a jump-start is made, viral has a strong, emotional content, is incorporated in total marketing strategy and is spread by influential consumers. What can be obtained by looking at the different research results for the virals, is that Dove is the best viral by scoring higher on the variables ‘incorporation in total marketing strategy’ and ‘a jump-start is made’. These variables probably are therefore also important in creating a good viral. Last, the initial sending of a viral is something to think about. Just sending a viral to the largest initial set of consumers is far from optimal because consumers prefer receiving virals from acquaintances than from a company. Sending a viral to a very small target group would be optimal, when your viral is really strong. A pre-test should point out what the best option is for a company. 6.3 Respondent characteristics This research is focussed on the variables that make a viral work optimal in the fmcg industry. Respondent characteristics are moderating variables in this research. However, some noteworthy findings in the influence of respondent characteristics will be discussed here. The age variable is proven to have a negative influence on awareness creation (for interest creation and purchase decision, not enough significant outcomes were obtained). This means that the older a person to watch a viral, the less awareness will be created. This is an argument for marketing managers to focus (or keep focussing) on young people when creating a viral. The creation of awareness for the Wilkinson viral is creating more awareness for women than for men. This is like expected (see chapter 4). The viral has a different target group than usual for Wilkinson. If this was the target group set before creating the viral, this was well executed. 60 The creation of awareness for Captain Morgan works better on people that do not live at their parents anymore. Also, the viral works better on young people than older people. This viral of Captain Morgan therefore works best on young people that live on their own. This fits with the target group Captain Morgan aims at. 61 7. Conclusion Viral marketing is a growing tool for companies to advertise their brands. This way of advertising is researched by academicals as well as practitioners of marketing. Viral marketing is used to create awareness, create interest and influence the purchase decision of consumers. Different studies have shown different variables that are important for viral marketing. To make viral marketing work optimally, however, no academical research (by my knowledge) has been done. The purpose of this study was to find out how viral marketing can be used optimally in the fast moving consumer goods industry. To give an answer on this, first a literature review was conducted to examine which variables are determining the optimal use of viral marketing. In this, academical (theory) and practical articles were reviewed. This led to eight independent variables that determine the optimal use of viral marketing in the fast moving consumer goods industry. The influence of these independent variables was tested by regression analyses of the effects of the variables in four different viral movies. The data for these analyses were obtained from a questionnaire held under Dutch consumers. With the regression analyses (and the different effects of the four different virals accounted for), the variables were reviewed for their importance. This thesis’ research question is: what is the optimal use of viral marketing in the fast moving consumer goods industry? The answer to this question is that there are eight variables determining how to use viral marketing optimal in the fast moving consumer goods industry. These variables are: 1. viral has a clear target group 2. viral has strong, emotional content 3. viral plays on current or recent events 4. viral incorporated in total marketing strategy 5. viral’s initial sending is to a large target group 6. actively addressing target group 7. jump-start viral is made 8. influential consumers spread the viral The variables were found not all to be even important. From the regression analyses the variables ‘viral has a clear target group’ and ‘viral is actively addressing the target group’ appear to most important in viral marketing. These variables should be accounted for first when making a successful viral. Further, making a jump-start and incorporating the viral in the total marketing mix are important for making a viral successful. These two variables determine if a viral will be moderately successful or really successful. The variables ‘play on current or recent events’, ‘let influential consumers spread the viral’ and ‘make a viral have a strong, emotional content’ have a moderate influence. These variables should be accounted for, but this is not priority in designing a viral marketing campaign. Last, the number of 62 consumers a firm should send the initial sending of a viral to, depends on the effectiveness of a viral. This should be measured by pre-testing. When a viral is very successful in creating awareness, creating interest and influencing the purchase decision, the viral should be send to a relatively small product group. When a viral is moderately successful, the viral should be send to a relatively large product group. Though this research is focussed on optimal viral marketing in the fast moving consumer goods industry, I believe the findings of this research are well applicable to other industries as well. Some small differences may be there, but the main findings of this research will be suitable for other industries as well. 63 8. Theoretical contributions and managerial implications In this chapter of this research, the implications and contributions to science and management will be given. This will be done by first describing theoretical contributions and then managerial implications. 8.1 Theoretical contributions For viral marketing, many literature exist. Though viral marketing is still a growing tool for marketing, extensive research has already been done on this subject so far. In studying this literature, different variables for optimal viral marketing (in the fmcg industry) were presented. Some research showed multiple variables to be important in viral marketing, but no overview of all the variables that make a viral work optimally were presented in one research. In this research this is done. This is good for research, because in further researching optimal viral marketing in the fmcg industry, these are the variables to account for. Further, the ranking of the eight variables were researched. This is, as far as my knowledge, never done before. The ranking of the eight variables have to be further researched (by using more virals) to determine real optimal viral marketing, though this research already shows that some variables are definitely the most important variables to account for. 8.2 Managerial implications What holds for theoretical contributions, also holds in many ways for managerial implications. For using viral marketing optimally in the fmcg industry, managers will have to account for the eight variables presented, while before it was not clear what variables should be influenced. For managers also, it is important to know which variables weigh more than others. This research gave a good picture for managers which variables of the eight can be good and which variables have to be good, in order to make a viral work. 64 9. Limitations and further research To have a complete understanding of how to interpret the findings of this research, it is important to be aware of the limitations of this research. As stated by Ferguson (2008): “researching viral marketing and word-of-mouth marketing campaigns remains an inexact and difficult science (Ferguson, 2008, p. 179).” The limitations of this research will lead to implications for further research. Both are discussed in this chapter. The main limitation of this research is the number of virals used for determining which variables are the most important ones in viral marketing in the fmcg industry. The eight variables are well found, but the ranking therefore is less certain. When examining more virals, other rankings could come up, though I do not believe major differences will be found. To make a more significant ranking, more virals should be researched. Due to the limited time available for research in a master’s thesis, more virals could not be researched. If more virals were to be researched, this would be at the cost of the in-depth analysis of these four virals. The use of viral videos to make conclusions about viral marketing is also a limitation. Though viral videos are only one way of viral marketing, other ways of viral marketing are different in the nuances, not in great parts. Literature on viral marketing often does not even make a difference in the different ways of viral marketing. Sending an e-mail to friends is the same, whether the content of this email is a funny text, a beautiful picture or a (link to a) surprising video. Therefore, the outcomes for viral videos will be pretty accurate in generalizing to other ways of viral marketing. Another limitation of this research is that this research focuses on viral marketing as a marketing tool on itself, cut from all other marketing tools. Researched is, if the viral marketing campaign is in combination with other marketing tools, but not how this is done. For more accurate results in how viral marketing works optimally, this should be done. Next, in calculations, non significant data was also used to calculate the eventual ranking of the eight variables. This was done, because the data was not significant in the regression analysis when it had a small influence in the regression analysis. When a small influence is measured, a bigger sample is needed to make sure this small influence is not based on chance. Therefore, when data was non significant, it was also not a big influence on the total score of a variable. Neglecting non significant data would result in more biased outcomes than using them, knowing that a bigger sample is actually needed to rule out chance. In further research, a bigger sample should be taken to make sure these small influences are also significant. Further, the sample taken for this research is biased. All respondents in this research have to speak Dutch because the questionnaire is in Dutch, almost all respondents live in the Netherlands and in or around Amsterdam (a few exceptions can be there), respondents are mostly students on a university or HBO education and are aged between 18 and 23. This makes it difficult to generalize the results of 65 the optimal working of viral marketing in the fmcg industry. A more diversified sample should be used in further research to find a more accurate ranking of the variables. Last, in this research, variables to measure the influence of a consumer were used from Richardson & Domingos (2002) and Subramani & Rajagopalan (2003). These variables were translated into statement in the questionnaire to measure them. 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