Download optimal viral marketing in the fast moving consumer goods industry

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
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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
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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.
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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
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(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.
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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’).
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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).
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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).
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•
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):
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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:
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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
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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.
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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.
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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).
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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.
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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.
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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
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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.
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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.
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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
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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. When merging these variables into one, the
Cronbach’s Alpha appeared lower than 0.6. When Cronbach’s Alpha < 0.6, merging is not completely
reliable. From this can be concluded that the translation from this construct to questionnaire statements
was not optimal. Therefore, this variable is not measured optimally in this research. In further research,
more accurate results could be obtained for this variable.
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