Commercial advertising, mainly television commercials, in comparison to viral advertising is more effective in generating awareness and is equally as effective in generating purchase intent (Robinson, 2009). However, no literature tackled viral advertising through word of month in modern day social networking such as Backbone and Mainstream. In this research, college students will be defined as the target audience of my research question, between the ages of 15 and 23. Viral advertising will be defined as the form of advertising that is most commonly executed online.
In this research it comprises personal posts through social outworking sites such as Backbone, Mainstream, and Twitter. Commercial advertising will be defined as a form of advertising executed through multiple ways such as Out Of Home advertising, posters, and television commercials. Word of mouth will be defined as a component of viral advertising as a way for products to gain popularity and generate purchase intent in the absence of commercial advertising. Crosscuts will be defined as a croissant-donuts hybrid made popular by a restaurant in New York and has become a trend in the Philippines.
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Literature Review A number of research studies are devoted to viral advertising and its effectiveness. Social media such as Backbone, Mainstream, Twitter, and Tumbler, are tools to execute viral advertising. In order to break away from the clutter of commercial advertising, marketers delve into viral advertising for more personal strategies and to form relationships with the consumers (Wright, Khan, Harrington, & Kier, 2010). In the business world, viral advertising is known to be one Of the leading forms Of communication (Smith, Coyly, Lightproof & Scott, 2007).
On the other hand, the effectiveness of Commercial advertising through the use of billboards, television commercials and radio immemorial has declined over time (Robinson, 2009). Studies on Viral Advertising Like any other form of advertising, there are principles that need to be considered when using viral advertising. Dee Also, Bryce Bassett, and James Haskins (AAA) studied viral advertising, delving into the factors that affected viral advertising through the use of the Bayesian belief and other methods.
The researchers (Also et al AAA) discussed principles that are necessary for successful viral advertising: viral advertising operates in a dynamic environment, is based on personal preferences and emotion, and involves OTOH negative and positive feedback. The Bayesian Belief Networks also showed that next to personal experiences, word of mouth was considered as the source with the highest credibility and influence when assessing consumer perceptions toward businesses (Also et al. AAA). However, the word-of-mouth phenomenon is complex and cannot be directly controlled, so that better business productivity is not always guaranteed in viral marketing (Also et al. , AAA). Ted Smith, James Coyly, Elizabeth Lightproof, and Amy Scott (Bibb) conducted a survey targeting CENT Network brand site visitors, participants ho had authentic web cookie for their visit to the brand in the last 120 days. In the survey, the researchers (Smith et al. Bibb) aimed to measure the influence of behavior of the participants by measuring data collected via the survey: what forms of communication they used and with whom did they communicate with, what did they commonly talk about online, and how involved they are in open forums. The study ended with multiple conclusions; having a large connection through personal networks does not mean having a large influence being one of them.
Elizabeth Wright, Nile Khan, Catherine Harrington, and Lee Kier (2010) observed the decline of loud and noisy commercial advertising, having consumers actually pay to avoid commercial free programming and features similar to it. With the decline of commercial advertising, a trend in online media advertising has begun to grow and this is evident through the use Of social media as campaign strategies of political figures in the United States (Wright et al. , 2010).
The advancement in technology along with consumers’ behavior turning away from the noise and clutter of advertising, companies are turning to social media and making personal connections to advertise to nonusers (Wright et al. , 2010). Studies on Commercial Advertising A quantitative research conducted by Raja Stentorian, Gerard Tells and Richard Bribers (2011 a) found that advertising elasticity, which is the “percentage increase in sales or market share for a 1% increase in advertising” (p. L can be used to measure the effectiveness of advertising.
Tells and colleagues collected econometric models using market data in order to record advertising elasticity (2011 a). The researchers (Wright et al. , 201 1 a) found that compared to print advertising, television advertising elasticity is higher only in the short run; while print advertising elasticity is higher in the long run. Both short- and long-term advertising elasticity also seemed to decline over time (201 1 a). Peter Danger and Tracey Dagger (2013) used quantitative research to measure and compare the effectiveness of traditional advertising.
The study aimed to help firms evaluate the effectiveness of their advertising channels. The research involved the development of a database of individual-level exposure. This combines ten media channels and purchase activity of the same participants into a single-source data. This is then used to estimate advertising effectiveness. The researchers (Danger & Dagger, 201 3) collected a random sample of 20,000 people between the ages of 25 and 54 since this is the target market of the retail company being studied.
A sale was then advertised through three different categories: online media (social networks such as Backbone and Twitter), mass media (television, newspapers, billboards and magazines), and direct media (catalogs and e-mail). Through quantitative research and data analysis, the results were as follows: traditional media still had a high rate of effectiveness with radio remaining insistently effective, online media remained inconsistently effective.
The researchers (Danger & Dagger, 201 3) advice firms to handle their own form of advertising and which form will be most suitable for the content and message they intend to broadcast. Sub-section on Viral vs.. Commercial Aching-Nan Chaos, Canaan Coors and Tiger Lie (2012) conducted a research on the effectiveness of traditional advertising with the emergence of online advertising. The strategic shift of businesses towards online advertising put into question the effectiveness of traditional advertising. The target artisans were mall goers, primarily the younger shoppers.
The survey questionnaires were then handed out to the participants. Through a survey questionnaire, the researchers (Chaos et al. , 201 2) asked participants to evaluate the regularity they would the notice each of the variable messages advertised in Online advertising and traditional advertising, with 5 being the most frequent / always and 1 being equivalent to no regularity / never (Chaos et 2012). The t;Test was used in order to properly analyze two samples for two different categories from the same individual. The researchers (Chaos et al. 012) found that traditional advertising effectiveness is higher than that of online advertising and their hypotheses, where there is a difference between the effectiveness of traditional and online advertising, were declined. The research ended with a conclusion of advising businesses to balance their focus between online and traditional advertising. Through quantitative research, Dirk Bergmann and Alexandra Bonito (201 1) were able to study the key to maximum effectiveness of both online and traditional advertising.
The researchers designed models for advertising and product markets, and exponential models. With these models they were able to find the right forms of advertisement for specific products and messages. Sub-section on Product/Service and Audience Studies on viral and commercial advertising and their effectiveness in the Philippines on a Filipino audience have yet to be performed. However, the emergence of online advertising in the Philippines is slowly being recognized by the public through Newspaper articles.
One article entitled “Pinots trust word-of-mouth more than traditional, online ads – Nielsen” (TTS, 201 3), reported that traditional advertisements remained to be trusted among consumers. The Nielsen study, known as a global leader in measurement and information, said online advertising is dominating in increase in trust levels for consumers residing in Southeast Asia. The new-age in technology may be a major contributor to the rise in effectiveness of online advertising. Another finding of the Nielsen study is that regardless of form of advertising used, Filipinos are more drawn to relatable plots and heart warming stories in ads.
Since there is no previous study related to this research, this research could possibly be an important tool to future studies on the emergence of viral advertising and the effectiveness of traditional advertising in the Philippines. The Elaboration Likelihood Method The theory to be used in this research question will be the theory of Elaboration Likelihood Model, formulated by John T. Capitol and Richard E. Petty in the asses. This theory explains how persuasion is dealt with in two ways: the central route and the peripheral route (White, 2011 b).
The central route zeroes in on the worth of the persuasive message using a systematic process having high involvement from the receiver due to interest towards the message, while the peripheral route is triggered when the subject is not inclined and uninvolved to the worth of the persuasive message, White describes it to be heuristic (201 b). Though this theory may not tackle the effects of the message, it still discusses the process of how the receiver takes in the persuasive message and this is highly applicable to advertising and ultimately generating purchase intent.
Choc Change-Hon. (1999) uses advertising on the world wide web as a form Of persuasion towards the receivers. Using the elaboration likelihood model, the researcher studies the high- and low-involvement of receivers when presented with online advertisements. The participants, a total of 203 undergraduates, were divided into two groups and had a pre-test wherein they were exposed to products and measured their involvement by using a semantic scale. The experiment then proceeded by asking the participants questions regarding their opinions and attitudes toward specific web sites and banner ads on each one.
The second part of the experiment asked participants questions regarding their personal opinions towards advertising and online advertising in general. The last part of the experiment asked for the demographics of the participants. The results came out as follows: Participants in high-involvement situations had more chances of clicking the banner ads out Of interest as compared to those in low-involvement situations (Change-Hon., 1999). As for the low-involvement situations, receivers are more likely to click on banners that are eye catching, large in size and has dynamic animation (Change-Hon., 1999).
Along with this theory will be the post-positivism worldview. I will be taking in the personal opinions of my participants and know that these opinions are their own making and is more of an objective truth. Methods Sampling The researcher will classify her friends in her social networks according to the following age brackets: 15-17, 18-20, and 21-23. The researcher will then use stratified random sampling to select a total of six people, two people from each age bracket. The researcher will then use snowball sampling until she has collected data from 12 people.
Data Collection The researcher will contact the initial six participants through online means such as Backbone chat, or via text or call. Data will be collected through the interview method wherein the researcher will consult with each participant individually and ask a series of questions connected to the research question. The interview will be recorded using the recorder application on the phone and important points will be taken down during the interview process. After recording the interviews, each one will be transcribed by the researcher.
Questions to be asked in the interviews can be found in Appendix B. Data Analysis Inductive Analysis will be used to analyze the data transcribed from the recorded interviews. Encoding the data will be the first step followed by the second step, which is to create domains for the coded data. After creating mains, the researcher will then analyze the domains and search for patterns or recurring themes. With these themes a generalization will be formulated among the domains.