Welcome to Viral Marketing: Decoding the Viral Loop.
After the success of games like Candy Crush and FarmVille many firms have taken to viral marketing on Facebook and other social media websites.
Yet, will viral marketing approach work for other products, as well?
When we look at research studying this phenomenon we find that they provide either descriptive accounts of particular initiatives, or, advice based on anecdotal evidence. What is missing is an analysis of viral marketing that highlights systematic processes that results in predictable desired outcomes.
In this article we take look at viral marketing from various different perspectives: the sender, the receiver and the message. We try to understand what motivates someone to pass on message and how the mechanism works.
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Table of Contents
- Viral spread happens reactively, not proactively
- Characteristics of viral spread
- Viral Marketing : The Participants’ view
- Determining the optimum number of exposures
- The Viral Equation
- Some Viral Marketing Models
- Quadrant 1. What initiates the input for word of mouth
- To reduce the perceived risk
- What sources of information do the receivers seek?
- Quadrant 2. Effects of word of mouth on the receiver
- The groups’ predisposition towards your brand
- Why you should seed the network first
- Seed only relevant groups
- Positioning of the sender
- ‘Attribution theory’- The motives
- Quadrant 3. What initiates word of mouth output
- Are some motivations better for certain product categories?
- Taylor’s six segment strategy wheel (1999)
- Target opinion leaders first
- Quadrant 4. Effects of word of mouth for the communicator
- The Sender, the Receiver and the Group
- Framework for Viral Marketing
- Awareness Creation and Benefits Signaling (ACBS)
- Why people comply?
- How to increase compliance
- Publicly acknowledge compliance
- For closed-system of products leverage Informational Influence
- Where to apply these models
- Use influencers to leverage Targeted Recommendation and Motivated Evangelism mechanisms
- Use novices or newbies when leveraging ACBS & SUGM mechanisms
- Types of networks
- Densely Knit Groups
- Ramified Networks
- The Product Perspective
- What motivates the communicators to initiate WOM
- Positive Word-of-Mouth (PWOM)
- Product involvement
- Helping the company
- What can we do to increase Positive Word-of-Mouth
- Facilitate customer-to-customer know-how exchange
- Negative Word-of-Mouth (NWOM)
- Experiences during actual consumption and viral spread
- How to use this in viral marketing?
- Provide superior product performance.
- Ensuring satisfying customer-employee contacts
- VM for Utilitarian Products
- User mind-sets and platforms
- The Message
- What type of messages get passed on?
- ‘Accessibility-diagnosticity theory’
- Mobile Messages and Viral Marketing
- The MVM mechanism
- Viral marketing SMS and films
- Viral Videos
- Use of emotion in viral videos
- Viral Videos need to go where TV won’t go
- So, what works in viral videos?
- How you name your video ads
- Use of celebrities in videos
- Email Viral marketing
- Propagation rate and Large initial seeding
- Use of emotions in viral marketing
- Use of Joy
- Use of sadness
- Use of hope
- Use of Anger
- Use of Fear
- Use of Disgust
- Role of the Genders
- Emotion v/s Engagement : Presence of Flow
The first thing to know about Viral Marketing is that…
What this means is, viral spread is a reactive behaviour rather than a proactive one.
(Gil-Or, O. (2010) set out to test out this hypothesis.
An experiment was initiated to figure out the possibility of generating demand using viral marketing on Facebook, which included the promotion of a restaurant group page. As a part of the experiment, the “Cramim restaurant” Facebook page was created using the pre-defined Facebook’s template for restaurant pages.
In order to start the distribution of the restaurant page virally, an invitation to become a fan of the “Cramim restaurant” page has been sent to 20 friends that were identified. The invitation was sent without any additional message attached, to avoid the influence of the audience by the recognition of the message source.
During the following few weeks two other actions were taken:
- A message to the existing restaurant members was sent, in which they were told that the members of the group will get special offers from time to time and they were asked to invite their friend to join the group and enjoy these benefits.
- A special coupon was offered exclusively to the group members where they got an offer to get a free glass of wine and an appetizer while dining in the restaurant. The coupon was used in order to attract more Facebook users and give them a reason to become a fan of the “Cramim restaurant” Facebook page.
The message path was tracked manually. This approach tracked which friends each group member got and in some cases, the researchers got in direct contact with the individuals for tracking cases where apparently different “routes” lead to the same person.
When the group members were asked about the way in which they first heard about the group. There were three ways that were mentioned:
- A friend that became a group fan and sent an invitation to his friends
- A message of the friend joining the group was published on his publicly-exposed wall page.
- The logo of the “Cramim” group that appeared on a friend’s personal info page was seen by his friends that got curious about this group.
During this first month 80 new members (including the first 12 members) joined the “Cramim” group.
If one ignored the anomaly of the one long-branch that was developed, there were four branches with that were seven-members deep.
That meant that the viral message was transferred six times from the first sender of the message. It is important to reiterate that the “message” could be transferred reactively by someone within one’s network that gets exposed to the restaurant group information.
The first proactive approach was actually used very rarely. The majority of the members joined as a result of the reactive message transfer i.e. path no. 1. This is really surprising since it means that the community could grow without any special efforts from the marketer’s side.
To understand the spread mechanism better, researchers used the Facebook admin statistics tool. It was mainly used in order to track the fans’ activity and statistics. This graph shows the time-based progress of the total number of fans that joined the community during the first 5 weeks since the original message was distributed with an average of 2.3 members a day and with a convex graph that showed a reduced growth rate.
Having seen this, let’s proceed to see how the virus spreads…
The stochastic process that shows influence is propagated from the seeding to their neighbours, and further.
However, all mentioned models and algorithms ignore one important aspect of influence propagation in the real world. That is influence propagation often happens only within a close proximity of the seeding.
For example, study of Chaet. al. in Flickr network reveals that the typical chain length is less than four; another study of Leskovec et. al. suggests that social influence happens on the level of direct friends. Moreover, shared information in social networks such as Facebook, in most cases, can be seen only by friends or friends of friends i.e. the propagation is basically limited within two hops from the source. (Dinh, T. N., Nguyen, D. T., & Thai, M. T. (2012, June), p 2)
This gives rise to two questions:
- When the influence only propagates locally, is massively reaching customers via viral marketing still affordable?
- In addition, can we speed up the spread of information for time-critical applications such as political campaigns or time-sensitive announcements?
To determine the best rate of message propagation we, then, need to first find out the optimum number of contacts to seed with our message.
Additional Resources: - Viral Lift - Mark Carrigan - How to create a buzz with viral marketing - PJ Germain - Viral Marketing: What the ALS ice bucket challenge can teach us about content marketing- Mark Stokes - Invisible Influence: The Hidden Forces that Shape Behavior- Jonah Berger
In epidemic models it is assumed that all individuals have an equal probability of getting infected with every interaction.
Another discussed point is that traditional epidemic and innovation diffusion models also often assume that individuals either have a constant probability of ‘converting’ every time they interact with an infected individual,
that they convert once the fraction of their contacts that are infected exceeds a certain threshold.
In both cases, it is expected that an increasing number of infected contacts results in an increased likelihood of infection.
But what has been observed in real life marketing scenarios is quite the opposite. In real viral marketing campaigns researchers have observed that the probability of infection decreases with repeated interaction. (Leskovec, J., Adamic, L. A., & Huberman, B. A. (2007), p 46).
This is an important finding for marketers who assume that more the exposures (interactions) the better is the viral spread.
What Leskovic, Adamic and Huberman, 2007, found was that the probability of purchasing a product increased with the number of recommendations received, but quickly saturated to a constant and relatively low probability. This means individuals are often impervious to the recommendations of their friends, and resist buying items that they do not really want no matter how many recommendations, or exposures they recieve. (Leskovec, J., Adamic, L. A., & Huberman, B. A. (2007), p 46)
It was also observed that smaller and more tightly knit groups were more conducive to viral marketing. (Leskovec, J., Adamic, L. A., & Huberman, B. A. (2007), p 46). We will go into details of groups and types of groups a little later in this article. Let’s now understand the formula for viral propagation.
Therefore, it is important to find out how many seeds to influence to begin the viral marketing process.
It is common sense, that as long as every new seed is able to infect at least one other new seed, the infected base continues to grow. The number of new seeds that a current seed can bring to the infected base, in turn, depends on the number of requests sent out by the user (N) and the conversion rate (Cr) of those into the following equation:
Viral Index = V =N * Cr > 1
This simple equation proved to be a powerful diagnostic for Plaxo managers when Plaxo ran a viral campaign to get new users to use their application. (Kalyanam, K., McIntyre, S., & Masonis, J. T. (2007))
The Viral Index V indicates the relative size of each new generation of customers compared to the previous period.
For example, when V _1.1, each new generation of customers is 1.1 times the size of the previous generation. When V _ 1.0, each new generation is smaller than the previous one and the number of new customers eventually goes to zero. V is indeed a magic number, and V _1 a magic threshold.
For best results it is necessary to increase Cr as well as N. But only increasing ‘N’ (the number of exposures) doesn’t increase the viral index, as seen in the previous point.
The first model explores the motivations of the sender and the receiver.
In this study Greg Nyilasy (2006), sets out to understand the phenomenon of word-out-mouth propagation (viral marketing in its traditional form) in detail. He studied things like how does it work? How does it influence the consumers? What are the factors that make it more effective? And, what causes it and what effects does it have?
The results of the study are measure over four parameters the perspectives of the sender and the receiver and the triggers to word-of-mouth propagation and the effects. This is tabulated in a 4 X 4 matrix as shown below:
What causes receivers to seek information or advice, etc.
People usually seek information when searching for additional information, or searching for a product / service. They also come across new information when someone in their network sends across such information (the motivation for group members to send such information varies and is covered later in this article).
Why does such a need arise to look for information?
Early research proposed that one of the crucial predictors of what influenced people to seek more information; thereby causing the occurrence of input word of mouth was perceived risk.
Perceived risk is the subjective assessment of potentially negative outcomes of acquiring or using a product.
Early studies and a more recent replication found empirical support for the hypothesis that the more risky the consumer perceives the purchase decision to be; the more likely he/she would be exposed to word of mouth.
A higher level of perceived risk is associated with services as opposed to products, according to ‘services marketing theory’. Risk is one of the reasons why consumers of services use word of mouth sources more often than purchasers of products, a proposition that has further empirical support.
The more difficult the decision, higher is the perceived risk by the individual.
The difficulty level of a decision is calculated on 2 dimensions:
1) Number of alternatives from which a choice has to be made, and
2) Number of attributes on which a choice has to be based.
Additional attribute is that of complexity of attributes to be considered.
The level of risk associated with decision tasks and the level of difficulty determine the type of influence sources that the customer seeks.
When difficulty levels of a decision task increases people feel less confident about making good judgements and they seek sources that are similar to themselves. (Duhan, D. F., Johnson, S. D., Wilcox, J. B., & Harrell, G. D. (1997), p 5)
E.g. High school seniors who are considering various colleges are often overwhelmed with the amount of information that is sent to them from various colleges. A common response is to ask the family members.
When perceived task difficulty increases, customers are more likely to seek information from strong-tie sources. (Duhan, D. F., Johnson, S. D., Wilcox, J. B., & Harrell, G. D. (1997), pp 10)
Additional Resources: - How to become viral on Reddit - Oxygen - 13 Tips to create a viral blog, Joshua Becker- Tim Denning - 5 mistakes that prevent your content from going viral - Pam Dyer - Six Attributes of Viral Content - Daisy Qin - Top digital marketing campaigns of 2016 that became viral marketing hits- Adam Barsby
A different line of research, using ‘network analysis’ methods, suggests that the kind of social relationships the receiver has with potential communicators (preceding the communication event) is another important predictor of whether word of mouth will occur. (Nyilasy, G. (2006), p12)
If this relationship is a closely-knit and strong one, then the receiver will seek information from sender.
Relying on the ‘strength of ties’ theory, sociometric research in marketing found that the stronger the relationship between the members of a particular social network, the more likely that these strong-tie relationships will be used for word of mouth communication.
In other words, there is strong empirical evidence (also replicated recently) for the common sense notion that if word of mouth occurs, it tends to be between close friends and relatives rather than superficial acquaintances (although ‘weak ties’ are also important, especially for the spread of word of mouth between overlapping social networks, as we will see later). (Nyilasy, G. (2006), p12)
When it comes to topics related to technology, research, science, etc. the receivers seek out industry experts, experts in the community or influencers for the information. (Nyilasy, G. (2006), p 12)
The ‘two-step flow’ theory of media and advertising effects stated that instead of direct effects, commercial messages were channelled through ‘opinion leaders’ – individuals influential in social networks – and it is only through their output word of mouth that viral communication effects can occur. (Nyilasy, G. (2006), p12)
Similarly, individuals who are seen are ‘experts’ in a community are sought for their advice when it comes to reducing the perceived risk of purchase.
Favorable predisposition toward the brand moderates the effects of word of mouth on product evaluation, i.e. the new seeds, too, perceived the brand more favorably.
Similarly, highly diagnostic information such as prior impressions about the brand and the presence of extremely negative information also influence the extent to which word of mouth is related to communication effectiveness variables.
A study carried out in this direction reports that a favorable brand name reduces the persuasiveness of negative word-of-mouth (NWOM). This means when the brand is strongly perceived to be positive, negative word-of-mouth doesn’t have any effect on the new seeds in changing their already held perceptions.(Nyilasy, G. (2006), p13) .
Hence, a strongly favorable brand helps build immunity against negative word-of-mouth (NWOM).
Communicators that come from a primary group (family and friends) are more trustworthy and credible than impersonal or weaker personal ones. This is the case in terms of (Nyilasy, G. (2006), p 13)
“The greater the similarity (homophily) of the seeker and source is, the greater will be the influence of the source on the seeker’s decision.” (Gilly, M. C., Graham, J. L., Wolfinbarger, M. F., & Yale, L. J. (1998), p 9)
Another reason suggested by the two-step flow theorists is that normative influence (conformity to influencers and group norms) is also at play when word of mouth (informational influence) is passed along. (Nyilasy, G. (2006), p13)
What this means is messages which adhere to the norms of the group get passed along.
E.g. messages about new software in the market are more likely to get passed along in a software developers’ social group than a message about the latest fiction novel released by an author.
On the other hand, the perception that the communicator is an expert source enhances word of mouth effectiveness, even if the message is initiated by the sender. (Nyilasy, G. (2006), p13)
“The greater the expertise of the source, the more likely he or she will be perceived to be an opinion leader. The greater the expertise of the source, the greater will be the influence on the seeker’s decision.” (Gilly, M. C., Graham, J. L., Wolfinbarger, M. F., & Yale, L. J. (1998), p 9)
This theory proposes is that if the receiver thinks that the communicator is unbiased, i.e. un-incentivized, or isn’t likely to benefit personally by propagating the message, the causal attribution implies the communicator really believes in the message; which makes the receiver accept the message.
On the other hand, the attribution for paid-for messages is that the motivation of the source is commercial in nature and, not genuine evaluation. Consequently, the message is received sceptically.
“The findings of the study suggest that the receiver’s causal attribution about the motives behind the communicator’s behaviour is a key mediator in the Negative Word-Of-Mouth –brand evaluation relationship.” (Nyilasy, G. (2006), p14)
The literature reviewed in this area investigates the factors influencing the likelihood and extent to which communicators engage in positive or negative word of mouth. The two-step flow theory proposes that mass media messages are not directly influential; rather they should be filtered through opinion leaders.
To understand this we study Taylor’s six segment strategy wheel
In 1999 Golan and Zaidner (Golan, G. J., & Zaidner, L. (2008)) tried and applied the Taylor’s six segment strategy wheel to viral advertisements.
The research question in the study asked if different product categories use different messages strategies in viral advertisements. The results in Table 5 indicate that such indeed was the case.
Successful viral advertisements for some of the product categories based their creative strategies on the ritual view more predominantly than on the transmission view. The ritual view was more widely used in the fashion (84.6%), alcohol and tobacco (82%), food and beverage (66.6%), entertainment and media (65.3%), and automotive (64.1%) product categories.
A combination of the ritual and transmission views was common in the travel (50%), banking (50%) and non for profit (41.6%) product categories. The only product categories that were relatively evenly balanced between the ritual and transmission views were the electronic and communications (46.7%, 36.3%), other (44.7%, 39.5%) and household products (50%, 35.7%) product categories.
The results of the study indicate that viral ads were primarily designed around the ritual view as a whole and across product categories. The results also indicated that most viral ads employed the ego strategy accounting for more than 50% of total ads.
Viral ads were not absent of the transmission view approach as nearly a quarter of the viral advertisements employed the ration strategy.
When synthesized with the results of the advertising appeal results, one could argue that viral ads were often based on an individual appeal (ego rather than social) that was based largely on humor while attempting to provide some information to the user.
In layman terms, it could be argued that viral advertising strategies target users through the gut rather than the brain. The prominence of this approach will likely advance rather than wane. Viral advertising competes daily with thousands of video clips that are user generated rather than professionally produced.
Opinion leaders process the information first, since they tend to be more frequently exposed to mass media. So the opinion leadership trait can be understood as a knowledge-based antecedent to output word of mouth.
The rationale for this type of investigation has been that the identification of opinion leaders is the key for marketers to be able to manage word of mouth. In the framework of the two-step flow theory this has meant that advertising campaign should target opinion leaders first.
While it is conceivable that word of mouth has an effect on the communicator – not only on the receiver of the communication – not much research has investigated this possibility.
The most important effects are ego-enhancement and the reduction of cognitive dissonance.
A word of mouth episode on the one hand might reassure the communicator that (s)he has made the right purchase decision. Just by talking about it, the communicator can get rid of negative feelings associated with cognitive dissonance.
On the other hand, the communicator might also feel good about him/herself as (s)he helps out a fellow human being. (S)he might also entertain the thought that (s)he was knowledgeable and competent in something. These forms of ego enhancements can be powerful emotional effect on the communicator.
Gil-Or, O. (2010) has conducted a study high-lighting two factors that play a key role in determining the nature of influence in viral marketing.
- The first is the role of the influencer — whether the influencer is active or passive in his/her attempt to influence.
- The second is the level of network externalities — the additional benefits that the group may accrue because more people are adopting the product or service within a user community.
Together, these two dimensions highlight four quadrants—regimes in which the nature of the influence and the factors underlying the recipient’s decision to comply with the influence attempt are qualitatively different.
In this quadrant, the role of the influencer in persuasion is passive and the network externalities are minimal.
Users emailing online greeting cards from Web sites such as Hallmark or BlueMountain to their connections represent typical instances of ACBS. When a user sends out a card from the site, the recipients get a personalized email message informing them of a greeting created by the sender available at the site and providing the URL to access it.
The URL directs visitors to the card on site and once there, he or she is offered the choice to send a greeting to the original sender or to a connected other.
In this process, recipients are indirectly made aware of the service offered by the site and are persuaded to use it.
The influence factor, though passive in this case, is high because the greeting has been created by a known person.
The role of the influencer is mainly to create awareness and signal benefits to others within their social network and can be particularly influential in encouraging trial and adoption of novel products and services.
Targeted Recommendations (TR)
In this scenario the influencer plays an active role in spreading the word and the network externalities are minimal.
This results out of the fact that there is no change of benefit for all users when the communicator forwards the content to other recipients. A user emailing a news story from an online content site to a connection is an instance of this quadrant.
Majority of online content sites such as WSJ, ESPN, MSNBC, and NYTimes offer the “send this story to a friend” option on their sites. These features make it possible for the recommender to send an email message with the URL of the particular story in it.
TR success hinges on the ability of the recommender to accurately predict the recipient’s interests and preferences (based on his or her private information), and or forward the information only to those who s/he thinks are likely to appreciate it.
This is advantageous for sites that offer a broad array of content (such as ESPN.com which covers more than sixteen sports in detail), as the information provided by the influencer enables relevant content to be provided to recipients. (Gil-Or, O. (2010), p 4)
Typically, the communicator can predict the recipient’s interest and preferences based on private information. Hence, Targeted Recommendation shows great promise to spread special product information within the target group.
The experience of ideavirus.com, a content provider, indicates that 56% of the recipients referred to content at the site by a recommender visited it and over 60% of these visitors also downloaded content that was recommended.
Signaling Use, Group Membership (SUGM)
This scenario describes the scenario where the influencer’s role is passive but both the recipient and the influencer benefit from the network externalities.
Instances include the use of specific kinds of products; for example, file compression utilities such as winzip and animation software such as Flash.
When a user sends the connected other individual a file compressed using winzip as an email attachment or makes a Flash animation available on a homepage, the recommender’s role in spreading the word about the software is passive.
This route is highly effective in the initial stages of the lifecycle when a software package is not widely known and used. This portrays the early users as being technically advanced. The influencer’s recommendation, albeit passive, has the effect of signaling the user’s membership in a group with desirable attributes.
Motivated Evangelism (ME)
This quadrant comprises contexts where recommenders play an active role in influencing connections and there are significant network externalities benefiting both influencers and recipients.
ICQ—an instant messaging application—and Dialpad—an application to place telephone calls over the Internet—are instances of motivated evangelism. In these instances, the influencer is well as the recipient need to use the product for either of them to benefit. The structure of benefits motivates early adopters to actively persuade connected others to also try the product so that they can both use the product.
It is conceivable that each new recipient turns into an evangelist for the product or service in his or her social network and the consumer base for the product or service grows exponentially, which is each marketer’s dream.
An individual’s response to referrals is based on how they perceive the influence. Two alternative models of influence are in force here.
- Normative influence—where the recipient perceives the request from an influencer as an implied expectation to conform, or
- Informal influence – where the recipient actively evaluates the information from the influencer before deciding whether to comply or not.
In contexts of normative influence, the mechanisms influencing action are identification and compliance.
Recipient behavior is driven by the desire to maintain the relationship with the influencer and/or be associated with a referent group by fitting-in in order to evoke a favorable response from the group. The recipient’s willingness to conform is stronger when recipient behavior is observable to the influencer and to others in the social network.
As an influencer if you publicly acknowledge the recipients’ compliance to your request, this demonstrates tracking behaviour and influences more compliance from the remaining members.
In contrast, the mechanism underlying informational influence is internalization, where behavior occurs only when such action is congruent with the recipient’s value system and by a personal evaluation of the benefits. Such compliance involves independent information processing by recipients with the goal of maximizing outcomes for themselves.
Informational influence is the central mechanism in Awareness Creation and Benefits Signaling.
Whereas, normative influence is the central mechanism in Signaling Use, Group Membership and Motivated Evangelism.
Either of these influences could play a role in Targeted Recommendation—determined by other factors such as the extent to which recipient behavior is observable to the recommender.
In Targeted Recommendation and Motivated Evangelism, the characteristics of the influencer play an important role. Some individuals wield more influence than others due to such factors as their specialized expertise, self-confidence, assertiveness, and social status.
Consequently, the benefits of seeding such individuals often referred to as efluentials is useful mainly for the Targeted Recommendation and Motivated Evangelism quadrants.
Recipient characteristics determine outcomes in the Awareness Creation and Benefits Signaling and Signaling Use Group Membership quadrants.
Novices—individuals with less experience with a product or service—are more likely to comply than those with prior experience with the product category.
Now, it’s time to look at the characteristics of groups and their types…
There are two structural archetypes. In densely knit groups, most members know each other, are in frequent contact with each other, but have little contact with outsiders (Figure 1). In network analytic terms, such groups are densely knit and tightly-bounded (Garton et al., 1997; Wellman 1997). By contrast, in ramified networks, few members are in contact with each, and a large portion of interactions are with outsiders. Such networks are sparsely knit and loosely-bounded. Reality, of course, often occurs in the continuum between these archetypes. A common one in contemporary societies is glocalization: rather densely knit clusters of relationships (usually at home, at work, and with kin) that also have many ramified ties to other people and groups (Wellman 1999; Hampton 2001).
For the sake of clarity, we concentrate here on two ideal types: densely knit groups and ramified networks. (Boase, J., & Wellman, B. (2001), p 9)
A virus can move quickly within a densely knit network because almost every member has frequent contact with every other member. This is true for all kinds of viruses. Densely knit groups allow for synergy, in which a particular group member is often exposed to a virus through frequent contact with other group members and, in turn, exposes and re-exposes other group members to the same virus. (Boase, J., & Wellman, B. (2001), p 9)
Not only are people in densely knit groups in direct contact with each other, they also tend to share common characteristics, such as socioeconomic status, tastes, or attitudes (Erickson, 1988; Feld 1981, 1982). They also have considerable influence over each other’s decision processes (Cross et at., 2001). This increases the likelihood that they will have similar patterns of behavior and hence be more likely to be exposed to the same virus.
Densely knit groups would lead to a fashion developing among a small group of people. It would be persistent, because it would be mutually reinforcing, but it would not spread widely. (Boase, J., & Wellman, B. (2001), p 13)
Homophily is important when trying to understand viral marketing. Because people within these groups have similar tastes, they are likely to buy similar products (Rosen, 2000).
Once something is introduced into a densely knit group, everyone in the group is sure to find out about it quickly (Rogers, 1995).
Furthermore, they are likely to buy the same product themselves. As Emanuel Rosen (2000) points out, this can have either positive or negative consequences for a producer. If a product is accepted into such a group, then the producer is likely to maintain that market. However, if the product is not accepted, the producer will have a very difficult time breaking into that market. (Boase, J., & Wellman, B. (2001), p 13)
For example, PayPal facilitates the transfer of money over the Internet to pay for purchases. To use PayPal, both parties must have accounts. Once a few members of a densely knit group are using PayPal, other group members will be tend to use it for the sake of simplicity (Bodow 2001; Van Hove, 1999). (Boase, J., & Wellman, B. (2001), p 13)
Densely knit groups are better suited for messages proposing behavioural changes or brand adoption.
If a virus could only spread within a densely knit group, then it would remain isolated and not spread on such a large scale. Ramified networks do not spread viruses as thoroughly within a defined population as within densely knit groups.
However, they reach out to a larger and more heterogeneous population. Viruses diffuse through a population in a curve that spreads rapidly when it moves to additional social circles. (Boase, J., & Wellman, B. (2001), p 15)
Eventually, diffusion levels off as friends of friends turn out already to have been virally infected by carriers who are closer in their social networks (Rapoport and Yuan, 1989).
“Structural holes” (Burt, 1992) between groups are filled by people who are connected to more than one group. These key gatekeepers and brokers are the means by which a virus spreads out through ramified networks.
Through the use of brokers – those who have membership in many different groups and thus link groups – a virus can travel between groups and spread throughout an entire population. Often, those linking two groups have “weak ties” with members of either or both groups. While strong ties stay within groups and thus circulate the same information and viruses (Granovetter, 1982), weak ties are more apt to have different social characteristics than the core members of a group (Feld, 1982). Hence, weak ties are more likely to spread the virus to new social milieus.
Weak ties play a key role in the spread of word of mouth through ramified networks because the Internet allows people to maintain their weak ties with little effort. (Boase, J., & Wellman, B. (2001), p 17)
Ramified networks are best for generating brand awareness.
Marketers tell us that viral marketing has been especially used in persuading teenagers to adopt new fads. For example, a sports shoe company hired a viral marketing firm to identify admired role models in high schools. These “aspirational leaders” (the marketers’ term) gave free shoes to such teens leaders. By wearing these and talking about them, the teen leaders create a persuasive demand for the new product. (Boase, J., & Wellman, B. (2001), 18)
Many readers have been asked to sign petitions, passed on electronically from hand-to-hand. Someone we do not know writes each statement, but close friends forward them to us – and to others on sizable lists of friends. This helps viral spread. (Boase, J., & Wellman, B. (2001), p 19)
Brokers are important for viral marketing because of their structural position. Or as Everett Rogers puts it, “diffusion campaigns are more likely to be successful if change agents identify and mobilize opinion leaders” (1995, p. 354; see also Valente and Davis, 1999; Weimann, 1994).
Trendsetters are the few people who will seek out new products and essentially decide whether or not they are “cool”. Cool products will be adopted by this group before they become popular, and will be abandoned once they become too main-stream. Unlike a computer or human virus, a buzz about a product will only occur if it fits into this cultural construct of “cool”.
Social networks are doubly important for bringing products from small groups of trendsetters to the wider public.
This is because they convey both sheer awareness and cultural approval. Trendy fashion companies, such as Reebok and Nike, have “coolhunter” employees. Coolhunters seek the new fashions of trendsetters, and they then act as brokers, by bringing these trends back to their company designers and eventually to stores (Gladwell, 1997).
Brands that thrive are no longer simply trying to publicize themselves in a monolithic way, they are inviting consumers to join them in creating meaning and being a part of the process.
Interaction is key; e.g. the computer games which have hidden levels or secret passwords for dedicated gamers; or the Britney Spears re-mixer which breaks down her songs into individual elements like drums, bass, her voice, etc. and then allows you to remix it how you prefer it (whilst ensuring everything remains in time so you can’t have a bad mix); or Nike, who allow you to remix the colour schemes of their trainers online and brand them with your name. Consumers are becoming producers, which some herald as the next stage of the consumer revolution—mass-customisation.
‘Passonability’ is key in a multi-channel communication world full of phone calls, emails and text messages—if brands can involve people in playful ways which are passed on and disseminated organically, they are far more likely to be successful. . . Brands which are perceived to enhance our relationships and be worth sharing with friends are the ones which will prosper (Hodder, 2002, p. 16). (Moore, R. E. (2003), p 21)
WOM about a product can be categorised into two types: Positive Word-of-mouth (PWOM) and Negative Word-of-mouth (NWOM).
The grouping of motivations for engaging in Positive Word-of-mouth (PWOM) communication resulted in four major categories: (1) altruism, (2) product involvement, (3) self enhancement, and (4) helping the company.
Altruism : Altruism is the act of doing something for others without anticipating any reward in return. In about 28.7 percent of the PWOM conversations, altruistic motives were found to guide people to share consumption experiences with others. These individuals had the intention of aiding the receiver to make a satisfying purchase decision.
Product involvement : The purchase and use of products that are perceived highly important or relevant tends to create excitement, and WOM is employed to vent the positive feelings. Personal interest in the product excitement resulting from product ownership, and product use were cited as reasons by 33.3 percent of the respondents for engaging in PWOM.
Self-enhancement : Respondents appeared to have the need to share their positive consumption experiences through WOM communication in an effort to enhance their image among others by projecting themselves as intelligent shoppers. About 20 percent of the respondents had initiated PWOM to show connoisseur-ship, to project themselves as experts, to enhance status, and to seek appreciation.
Helping the company: The final motive for engaging in PWOM communication is the desire to help the company. Although this is an act of altruism, a separate category was created because the objective here was to help the company rather than the receiver of the WOM. In these conversations, the source of the messages suggests explicitly that the receiver patronize a particular company. Nearly 18 percent of the PWOM conversations were initiated with the motive of helping the company.
To leverage from such PWOM you might want to…
eWOM communication impacts the perceived overall value of the firm’s offering in a significant manner. Also, customer-to-customer know-how exchange has a direct relationship with loyalty intentions, as well as an indirect relationship that was mediated through overall value of the firm’s offering. (Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006), p8).
Research provides evidence that the perception of value from the firm’s offering is also impacted by the value received through interactions with other customers of the organization. (Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006), p8). This means that prospects attribute the value received from other customers to the value received from the organization.
It is not enough to provide the opportunity to interact, the customers need to be motivated and empowered to interact with one another.
This team of researchers ran the analysis using the 30% (n =184) of the respondents with the lowest composite opportunity scores (std. dev.=0.78). The results of the analysis for this group did show a significant positive effect of opportunity on C2C know-how exchange.
The grouping of motivations for engaging in Negative Word-of-mouth (NWOM) communication produced the following categories: (1) altruism, (2) anxiety reduction, (3) vengeance, and (4) advice seeking. The motivations for engaging in PWOM and NWOM communication differed except for the motive of altruism which was found in both types.
Altruism : Almost 23 percent of the respondents indicated that their motive for engaging in NWOM communication was to prevent others from experiencing the problems that they had encountered. The motive was to help others by warning them about negative consequences of a particular action.
Anxiety reduction : A considerable number of respondents had used NWOM communication as an avenue to vent their anger. About 25 percent of the respondents indicated that sharing their negative experiences with others helped in easing their anger, anxiety, and frustration.
Vengeance : NWOM communication was used by 36.5 percent of the respondents to retaliate against the company associated with the negative consumption experiences. Consumers shared their negative experiences with the motive of deterring others from patronizing the businesses that they perceived did not care enough about customers, did not listen to customer complaints, and consequently should not be allowed to operate. The respondents guided by the motive of vengeance explicitly advised others not to patronize a particular business.
Advice seeking : Consumers who had encountered negative consumption experiences and were unaware of the means to seek redress tend to share their negative experiences to obtain some advice on how to resolve their problems. Seventeen percent of the respondents were found to be motivated to seek advice when engaging in NWOM communications.
Grouping the critical consumption experiences resulted in the following four categories: (1) product performance, (2) response to product/purchase problems, (3) price/value perceptions, and (4) employee behavior.
The study indicates that nearly 44 percent of the consumers who encountered experiences that fall in the category of price/value perceptions are driven by the motive of helping the receiver and 32 percent of them share the experiences because of self-enhancement.
Among the consumers who engaged in PWOM due to satisfying product performances, the motives of product involvement (52%) and self-enhancement (26%) are predominant. Of the consumers who engaged in PWOM that were triggered by satisfaction with employees, 37 percent had the motive of helping the company, and 27 percent had the motive of helping the receiver; about 29 percent of the respondents engage in WOM because of a relatively high level of product involvement. The consumers who received satisfactory responses to product failure problems speak favorably about the company with a motive of helping either the company (28%) or the receiver (41%).
The study also indicates that more than one-third of the consumers who were dissatisfied with product performance engage in NWOM communication with a motive of helping the receiver and others share their experiences because of vengeance (31%) or to seek advice (22.6%).
Of the consumers who received unsatisfactory responses to product failure,
- 45% engaged in NWOM to seek vengeance
- 21% engaged in NWOM to help the receiver and
- 20% engaged in NWOM to seek advice.
The consumers who engaged in NWOM due to unacceptable price/value perceptions
- 56% cited anxiety reduction and
- 20% the intention to help as their motives
Examination of the motives of consumers engaged in NWM due to dissatisfaction with employee behavior indicated that 56.5% of them had a motive of vengeance, i.e., trying to dissuade others from patronizing a particular company.
The study found that satisfying product performance and employee-consumer contact experiences accounted for about 60% of PWOM. This can be utilised to our advantage by selling only high quality products which are reliable and durable.
The old adage of under-promising and over-delivering helps here.
The resulting WOM may draw the attention of potential buyers to the company and eventually benefit the company.
When customers feel they’re getting inadequate responses to their product problems from the support staff they feel irritated and their overall perception of the product reduces.
The consumers’ poor value perceptions during post-purchase evaluations accounted for about 58% of the NWOM. By ensuring satisfying employee-consumer contact experiences are likely to spark PWOM in the marketplace as these types of experiences constitute major components of PWOM communications.
Otherwise, not solving product problems to customers’ satisfaction prompts them to engage in NWOM conversations. Consumers who perceive that their purchase was not a “value buy” based on post-purchase cost-benefit evaluations are likely to share the experience with others in the form of NWOM.
Once you have an understanding of the types of experiences that are likely to trigger WOM communications, it is useful for managers interested in WOM communication to leverage these findings.
For example, knowing that inadequate responses to product problems are likely to increase NWOM and satisfying responses spark PWOM, the marketers should emphasize on programs that improve their response to customer problems.
Our study also found that nearly 50% of WOM messages geared toward helping a firm are triggered by courteous employee behaviors.
Moreover, altruistic motives of helping the receiver are triggered mainly by price/value perceptions and responses to consumer problems.
Further, high product involvement motives for engaging in PWOM are primarily triggered by satisfying product experiences.
Similarly, motives for self-enhancement arise primarily from superior product performances.
The findings reported here suggest also that the consumers who experienced poor value perceptions utilize NWOM as a mean of anxiety reduction.
Further, consumers who were unhappy with product performance and who did not receive adequate help from the company are likely to engage in NWOM to seek advice from others. These findings suggest that managers can minimize NWOM communication by ensuring quality product performance, solving customer problems without delay, and ensuring employee competence.
Given that motivations are a function of consumption experiences, managers can influence NWOM by eliminating negative consumption experiences.
There’s a slight difference when it comes to viral marketing for products that are hedonic or utilitarian.
Viral Marketing follows different characteristics when it comes to utilitarian products (products purchased purely for their utility value).
Unsolicited and incentivized broadcast messages from friends are the least effective sharing mechanisms for primarily utilitarian products. (Schulze, C., Schöler, L., & Skiera, B. (2014), p 13)
Consumers use Facebook with the intention of having fun and being entertained rather than doing something useful. Thus, viral marketing messages for utilitarian products on Facebook do not correspond with their situational expectations or schema (Bartlett 1932).
Consequently, consumers unconsciously devote fewer mental resources to evaluating the actual message content and instead rely more on heuristics, simple inferences, and social cues.
Viral marketing campaigns for low-utilitarian products on Facebook are well-suited to follow the best-practice strategy of products such as FarmVille and encourage unsolicited and incentivized broadcast messages from friends for spreading viral marketing messages. (Schulze, C., Schöler, L., & Skiera, B. (2014), p 14)
Recommendations for viral marketing campaigns for high-utilitarian products on Facebook, such as job search or stock market applications, differ radically. Sharing mechanisms for such useful offerings should avoid using unsolicited messages or broadcast messages from friends. In addition, although incentives associated with these products are not harmful, they are ineffective in Facebook’s fun- and entertainment-oriented setting.
In fact, not using any viral marketing sharing mechanism is four times better for these products than FarmVille-type, unsolicited, incentivized broadcast messages from friends.
If it is necessary to give Viral Marketing a try, utilitarian products should rely on solicited viral marketing messages that customers can either direct at individual friends or broadcast to strangers.
On Facebook, for example, promoting a useful product in the “Likes” section on consumers’ “About” pages will be far more effective. (Schulze, C., Schöler, L., & Skiera, B. (2014), p 14)
We all know that messages that are engaging enough get passed on. But what makes a message engaging?
It seems that individuals are encouraged to spread marketing messages voluntarily if the messages:
(1) capture the imagination by being fun or intriguing,
(2) are attached to a product that is easy to use or highly visible,
(3) are well targeted,
(4) are associated with a credible source, and
(5) combine technologies.
This study provides additional perspective and explanation for the power of word of mouth. According to this study testing the theory the ‘vividness’ of information (unique to word of mouth due to its oral and interactive nature) is what generates favourable responses from consumers receiving it. Since vivid information is more ‘accessible’ than impersonal messages, receivers are more likely to use it when formulating product judgements (it’s more ‘diagnostic’). (Nyilasy, G. (2006), p 14)
Experts confirmed that recipients getting a mobile marketing message from familiar communicators participate more frequently in a campaign as initial contacts. The reason is the personal message gaining more credibility than that coming directly from the self-interested advertiser. (Wiedemann, D. G. (2007, March), p 1)
Taking advantage of the inherent nature of cell phones as communication vehicles MVM enables consumers to share mobile information and content within their social network.
Therefore, MVM facilitates spreading commercial information and content within the desired target group. Another advantage of MVM is that advertisers can significantly expand the campaign reach at low company expense.
According a survey of Skopos, 30% of the 2,500 respondents said a friend’s recommendation would convince them to download a mobile application. These finding illustrate the tremendous potential of MVM for communication and distribution purposes. (Wiedemann, D. G. (2007, March), p 2)
Researchers found out in a trial (n=500) that 17% forwarded one or more mobile messages. Mobile ads that were forwarded were those that were seen as especially entertaining or informative.
In the survey of (n=9,462) 19% to 42% (depending on the analyzed campaign) forwarded a mobile greeting card once and 22% to 41% repeatedly. (Wiedemann, D. G. (2007, March), p3)
Within MVM a variety of different participants (such as the advertiser, the connection point, the initial contact, the communicator and the recipient) are involved, their roles have to be analyzed. As starting points the advertiser can promote and place the mobile viral content in the content section of high-traffic connection points on the stationary or mobile Internet (e.g., portals of mobile network operators) or send it to initial contacts being the first group of recipients. If a recipient forwards the mobile marketing message, he will act the role of the communicator.
The motivation of the communicator can be intrinsic or extrinsic.
Intrinsic motivation is based on the inherent need of individuals to feel competent and to control their environment in order to enhance or stabilize their self-esteem.
Extrinsic motivation rests upon tangible (e.g., free mobile content) or intangible rewards (e.g., public praise on a mobile community). Furthermore, we distinguish the role of the communicator in persuasion in active or passive. Consumers will only accept mobile marketing, if they obtain an added value. Consequently, in MVM there must be an added value for recipient, such as information, entertainment, raffles or monetary incentives.
The content type in MVM can be a mobile application, a video, a voice message, an image or a text. The content generation is either (completely) done by the advertiser, e.g., with mobile voice greeting cards, or (completely or partly) done by the user, e.g., with mobile communities or Multimedia Messaging Service (MMS)-based greeting cards.
Two possible models can be distinguished in MVM: push and pull.
Within the push recommendation type the communicator sends unsolicited referrals or content to the recipient, whereas within the pull recommendation type the recipient actively requests the referral or content.
Another important technical issue is the underlying enabling technology for sending, replying and forwarding content.
After realizing the true dreadfulness of its film Godzilla, Sony Pictures raised its advertising budget to $50 million, opened the film on a record 7363 screens, and only managed to break even.
The widespread use of SMS technology has even narrowed this small window of time. SMS is a short message no longer than 160 characters of text sent by one user to another, most commonly via a mobile phone.
Coupled with viral marketing, the technology creates a positive or negative buzz around a brand, product, or service. The instant buzz can be cruel, notes Huck (2003), page 2.
Traditionally, Hollywood counts on a buffer—a few days—to entice audiences before the word, good or bad, leaks out. Nowadays a turkey like. . .Gigli is stricken from day one..
Why has this time period contracted? Consumers are reported to be text messaging their friends halfway through a movie to tell them whether or not it is any good. The word is then transmitted quickly around a wide network of peers and extended on to a wider audience via online chat groups. The result is that movies often have dramatic drop-offs between the opening session and the rest of the weekend despite saturation level marketing (the average film costs $63 million to make and market).
Here are some examples:
The Hulk took in $62 million on its opening weekend, plummeting 69.7% by the end of the week.
2 Fast 2 Furious earned $50.4 million at opening before dropping 63%.
Charlie’s Angels: Full Throttle took in $37 million, and then spiralled downward 62.8%.
This fundamentally changes the game for marketers, reducing the potential payback window to a few hours and dramatically raising the risk associated with marketing expenditure to ensure widespread product trial or adoption.
In the context of all viral marketing, Dobele et al. (2005) found that successful viral marketing campaigns comprise an engaging message that involves imagination, fun and intrigue, encourages ease of use and visibility, targets credible sources, and leverages combinations of technology.
Involvement and enjoyment are established drivers of offline success (Twose & Smith 2007), which we expected to remain important online.
Branding is another established metric of offline creative success. Unless advertising memories are associated with a particular brand, there is clearly little chance of those memories having a positive impact on brand attitudes. (Southgate, D., Westoby, N., & Page, G. (2010), p 4)
Wu and Huberman (2007) have used digg.com data to show that novelty plays an important role in the popularity of online content. The phenomenal success of videos such as Old Spice’s ‘Man your man could smell like’ and Evian’s ‘Roller babies’ suggest that unusual ads can work well online.
Other YouTube measures, such as average rating, number of comments, and number of times ‘favourited’ were also captured and examined. Generally, these measures were less representative of overall viral success. For example, on average we found our videos were ‘favorited’ just 28 times for every 10,000 times they were viewed, rated only 14 times and commented on just nine times.
Additional Resources: - How to go viral on YouTube- Susan Hallam - Viral of the Month: Durex Connect- Phil Szomszor - What makes a video go viral?- Chris Worthington The best viral recruitment ads of 2016 so far- Recruitment Grapevine How can you make a viral video?- Lara Doherty Viral Video Marketing: Things to Know and Keep in Mind - Wisden Writers - The 'V' Word- Why your video won't go viral- Todd Wasserman
It seems that the common wisdom in designing viral video campaigns is to make the content surpass the standards for what is socially acceptable in traditional television advertising (Lindstrom 2009).
However, research on edgier, highly emotional content, such as sex appeal and more extreme humor, in television advertising documents the risk of interfering with effective brand communication (Kellaris and Cline 2007; Severn, Belch, and Belch 1990). Thus, striking a balance between highly creative, emotionally engaging content and effective brand communication could be even more tenuous in producing viral video ads than for traditional television advertising. (Eckler, P., & Bolls, P. (2011), p 2)
Viral success depends on consumers’ active participation in forwarding messages to others, so campaigns are often more about the emotional impact of the message than the product itself (MindComet 2006). A popular viral video could be built around a nondescript product with a “wow factor” in the message (MindComet 2006). Because emotionality of the message is what likely drives consumer participation, viral videos often employ strong emotional appeals. Prior research has found that viral ads rely more on appeals related to humor, sexuality, nudity, and violence than television ads (Porter and Golan 2006).
As Mads Holman of London’s Go-Viral agency advised, viral videos should contain “things you can’t see on TV” to be successful (Lindstrom 2009). (Eckler, P., & Bolls, P. (2011), p 4)
It is unlikely that a video lacking a certain amount of emotional engageability will spread virally, regardless of other factors. At the same time, just because a video has this emotional engageability by no means guarantees that it will go viral; other factors (e.g., word of mouth, computer-based recommendation systems, and trendy cultural topics and memes) will influence a given video’s viral ability (Bardzell, Bardzell, and Pace 2008, p. 7). (Eckler, P., & Bolls, P. (2011), p 4)
- Pleasant viral video ads evoked the most positive attitude toward the ad.
- Viral video ads with pleasant emotional tone seemed to evoke the most favorable brand attitude.
- The strongest intent to forward viral video ads was with pleasant emotional tone (Eckler, P., & Bolls, P. (2011), p 9)
Responses turned less favorable as the emotional tone became more mixed and were least favorable for ads with negative tone (i.e., unpleasant).
This pattern of results mimics findings from traditional advertising on the relationship between emotion and attitudes, suggesting that positive emotional tone often results in positive attitudes and negative emotional tone often results in negative attitudes (e.g., Du Plessis 2008; Faseur and Geuens 2006). (Eckler, P., & Bolls, P. (2011), p9)
This study indicates that as emotional tone becomes more mixed, viewers evaluate these messages as both pleasant and unpleasant and become less favorably oriented toward the message and less willing to forward it.
Attitudes and pass-along intentions form using limited processing, and therefore, when viewers infer a general sense of pleasantness (approach), it facilitates a positive attitude and the desire to share the feeling with others. (Eckler, P., & Bolls, P. (2011), p 9)
How the ads are named can also make a difference. When tracking down the ads for this study, we found that videos can be very difficult to find if they are given obscure names.
This is despite the fact that YouTube has a very good video search feature. The ad name itself clearly has two functions: among random surfers, an intriguing name may help drive viewing; however, among focused searchers, a more obvious name may help increase viewings.
Celebrities play an important role online, as a source of entertainment, gossip and news, and many celebrity music and sports videos are among the most viewed of all time on YouTube. (Southgate, D., Westoby, N., & Page, G. (2010)) therefore examined whether the presence of a celebrity in an ad can drive online viewing, and in particular whether the popularity of a celebrity can impact the chances of a viral video being viewed. (Southgate, D., Westoby, N., & Page, G. (2010), p 6) We found that having celebrities in the videos did not affect the virality of the video.
In the context of email viral marketing, Phelps et al. (2004) suggested that messages that spark strong emotion – humour, fear, sadness or inspiration – are likely to be forwarded.
Results indicate that only individuals’ need to belong is positively associated with individuals’ pass along intentions and behavior. (Phelps, J. E., Lewis, R., Mobilio, L., Perry, D., & Raman, N. (2004), p 1)
Viral marketers are strongly encouraged to target individuals who opt in for such messages. Marketers might also want to search for online communities that reflect members’ desire to belong when looking for potential targets to spread their viral campaign messages.
Other strategies involve designing viral content that upon passing along satisfies individuals’ need to belong. In other words, designing campaigns that touch on a sense of belonging to a larger group of individuals with shared goals and motivations might result in favorable pass along behavior. (Phelps, J. E., Lewis, R., Mobilio, L., Perry, D., & Raman, N. (2004), p 1)
Watts and Peretti (2007) found that both the propagation rate (the degree to which people are willing to pass an ad on to others) and the scale of initial seeding determine the size of the viral audience.
To a large extent, the propagation rate is likely to relate to the creative mechanisms we have studied here, most specifically the likelihood to forward ‘buzz’ measure tested in “claimed likelihood to forward” hypothesis.
The initial scale of seeding then acts as a multiplier against this propagation rate. Watts and Peretti advocate ‘big mass-seed marketing’ – that is, placing advertising with a large number of consumers in order to give the ad a greater chance of going viral.
Through a content analysis of 360 viral advertisements, a study attempted to highlight the viral component in the ads by identifying the main advertising appeals employed by advertisers. Research Question number one asked what advertising appeals were most frequently used in viral advertisements?
Results indicated that humor was by far the most commonly utilized advertising appeal in the viral ads as it was incorporated in 91% of the ads.
Sexuality was the second most common advertising appeal as it was used in more than 28% of viral ads.
These advertising appeals were followed by the use of animals in ads (17.8%), violence (14.4%) and the use of children (12.8%) of all viral ads in the current analysis. (Golan, G. J., & Zaidner, L. (2008), p 9)
Humor and sexuality were the main advertising appeals used in viral ads. This finding is consistent with Porter and Golan’s (2006) study that found that humor and sexuality were the predominant advertising appeals used in viral advertising.
These finding point to both of these advertising appeals as the main meme factors that make viral ads ‘‘viral’’. That is, consumers are entertained or moved enough by advertisements based on humor and sexuality that they chose to forward these ads via email to their friends and colleagues.
The effectiveness of the viral message is moderated by gender, with male receipients more likely to forward disgust-based messages and female recipients likely to forward fear-based campaigns. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 3)
Viral marketing campaigns using joy are most suited to irreverent or fun brands such as Virgin, Apple, and Chick-Fil-A, or campaigns such as Amazon’s, Ford’s Evil Car, and the Australian Meat Board’s Eat Lamb campaign that seeks to encourage interest in a mature category. Brands targeting younger consumers may also benefit from using joy. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 19)
Viral marketing campaigns using sadness are most suited to social marketers seeking an immediate response to disasters (thus timing is critical), particularly acts of god. Consumers reacting to campaigns dominated by sadness were most likely to show a short-term commitment to the brand or campaign, rather than become encouraged to engage in long-term change. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 19)
For example, campaigns seeking child sponsorship in less developed countries were viewed as less successful when relying solely on sadness. Instead, these campaigns were often dominated by images of hope and messages that small contributions would make a big difference. Marketers must be careful to ensure that campaigns based around sadness encourage benevolence rather than guilt. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 19)
Viral marketing campaigns based on anger are most suited to single issue campaigns seeking an immediate reaction to injustice. Campaigns used by social marketers may include reactions to threats of destruction of wilderness areas, threats from governments including forthcoming acts of parliament, and perceived injustices perpetrated by corporations. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 20)
Brands facing competitive threats that wish to mobilize support for their cause, or support for government action limiting the competitors actions (such as Wal-Mart opening a new store in a local area) may also benefit from anger campaigns. Anger is a fleeting emotion and therefore is ill suited to campaigns that require longer-term action (for example climate change), or where issues may be complex or subtle, and thus not elicit an angry response from many people. Anger is best used in situations where people are being cheated because anger then takes on a protective role for people. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 20)
Viral marketing campaigns based around fear must be used very carefully and sparingly. Fear is also a short-term response to a perceived threat. Therefore, campaigns seeking to change behavior such as those on drink driving, drug use, sexual practices, or speeding may be best suited to fear when combined with either a solution (such as having a designated driver or using condoms), a punishment (such as speeding fines), or links to further information for concerned recipients. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 20)
Viral marketing campaigns using disgust or bad taste are best used when targeting young males, for rebel-styled brands such as brands targeting cultures who find disgusting events campaign humorous. Disgust-based campaigns in particular must be careful of crossing the fine line of acceptability, and must provide a humorous and surprising message at the right time. Brands should use disgust campaigns only intermittently, for example around major events such as the Super Bowl or Christmas, and must be carefully targeted to avoid unnecessary offence. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 20)
In viral marketing male recipients are more likely to pass on viral messages than are female recipients (63 percent male to 37 percent female). Men are also more likely to pass on messages involving humor, particularly disgusting humor, than are women.
In addition, we found the emotional responses of fear felt by female respondents were stronger than those felt by the male respondents.
Researchers were studying the effect emotions in viral spread. They had the participants view emotionally charged messages. After the viewing, when responding to a campaign featuring a fear element, female respondents used all three fear-related terms: afraid, scared, and fearful.
Male respondents were less likely to use all three terms.
In instances where female respondents felt fear the viral marketing campaign was more likely to be forwarded, as women tried to help other women by alterting them to the ‘danger’ or to a situation that could be scary. (Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007), p 21)
In 2015 Prof. Connie Bateman of North Dakota University (Bateman, C. R. (2015)) carried a test to find out why emotions increase the viral pass-on. In that study she found that it wasn’t the emotions per se that influenced pass-on, though they were an important feature. It was the engageability of the emotions that made the subjects want to pass-on.
The conflicting findings regarding emotion and viral marketing, as well as a number of studies using biometric measures, suggest that it is the level of engagement, rather than its emotional valence, which is significant in viral marketing. Siefert and his colleagues (2009), for example, used biometric measures such as skin conductance, heart rate, and respiration to indicate the intensity, but not the valence, of emotional engagement among study participants, and found a correlation between engagement and online buzz.
These findings suggest that the level of engagement, or the intensity of the experience, is more important than the specific emotion elicited by the content, and whether the emotion is positive or negative.
In a study that examined the relationship between consumers’ online engagement and Web site effectiveness, Sicilia and Ruiz (2007) conceptualized engagement as flow, a concept first introduced by Csikszentmihalyi (1990), who describes flow as “optimal experience” characterized by total involvement with life, the opposite of anomie and alienation, and “the state in which people are so involved in an activity that nothing else seems to matter.”
Rodriguez-Sanchez, Schaufeli, Salanova, and Cifre (2008) reported that the construct of flow consists of absorption, enjoyment, and intrinsic interest.
Drengner, Gaus, and Jahn (2008) viewed flow as a five-dimensional construct consisting of full concentration, absentmindedness, loss of sense of time, the impression that consciousness and activity are merging, and the subjective impression of having one’s activity under control.
They defined flow as a state characterized by a seamless sequence of responses facilitated by machine interactivity, intrinsically enjoyable, accompanied by loss of self-consciousness, and self-reinforcing (Hoffman & Novak 1996). Novak, Hoffman, and Duhachek (2003) found that online flow experiences occur for both experiential and goal-directed activities.
Huang (2003) found that the more intense the flow state, the more positively consumers rate the Web site. Hoffman and Novak (1996) reported that online flow increases recall, positive behavior, and a positive rating of the experience. Similarly, Sicilia and Ruiz (2007) found that Web sites that cause consumers to experience flow result in significantly more positive comments, significantly more positive attitudes toward the Web site, and, indirectly, significant increases in purchase intentions.
Intention to download content was significantly higher for individuals who experienced high flow than for those who experienced low flow. There was no main effect for pleasant vs. unpleasant condition and no interaction effect.
Willingness to pass along content was significantly higher among high flow individuals than low flow individuals. There was no main effect for level of pleasantness and no interaction effect
Individuals who experienced high flow were significantly more likely to purchase the content than those who experienced low flow. There was no main effect for level of pleasantness. and no interaction effect.
Finally, high flow was significantly more likely to result in the intention to attend a performance by the band featured in the content compared to low flow. There was no main effect for level of pleasantness and no interaction effect.(Bateman, C. R. (2015))
While we have tried to decode viral marketing, this is not a comprehensive study by any means. In this study we see what works and why it works. But, the parameters studied are not the entire range of parameters that exists that determine the success of viral marketing.
Now the important question is – Does this equip you to conduct a viral campaign?
The answer is – yes, it does equip you with enough conditions to consider that propagate viral spread. However, the creative input has to come from you.
This is similar to trying to decode the Monalisa. Just by studying a document that decodes the uniqueness, style and techniques used to create the Monalisa isn’t going to be enough to help you create one. But, having an understanding on these will help you along the path to explore creating your own.