Search Engine Marketing: More Than Just Ranking?
The Influence of SERP Ranking and Brand Name Repetition on Brand
Awareness
Master Thesis
Pier Kempenaar
Search Engine Marketing: More Than Just Ranking?
The Influence of SERP Ranking and Brand Name Repetition on Brand
Awareness
Pier Kempenaar
University of Groningen, Department of Marketing
Master Thesis
13-01-2020
Adress: Heidewei 32, Zwagerbosch Phone: +31629759905 E-mail: p.kempenaar@student.rug.nl
Student Number: S2732025
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stSupervisor: Dr. J.A (Liane) Voerman
TABLE OF CONTENTS
MANAGEMENT SUMMARY ... 1
ABSTRACT ... 2
1. INTRODUCTION ... 2
1.1 Searching and Finding Information Online ... 2
1.2 Using SEM to Beat The Search Engine Clutter ... 3
1.3 Brand Awareness ... 4
1.4 Short Term vs Long Term Effectiveness of SEM ... 5
1.5 Problem Statement ... 6
2. LITERATURE REVIEW ... 8
2.1 SERP Ranking Position & Brand Awareness ... 8
2.2 Brand Name Repetition & Brand Awareness ... 9
2.3 Internet Savviness and Skepticism Towards Advertisements ... 10
2.4 Materialism & Brand Awareness ... 12
2.5 Conceptual Model ... 12
3. METHODOLOGY ... 14
3.1 Experiment Design ... 14
3.2 Procedure ... 14
3.3 Experimental Variables ... 15
3.3.1 SERP Ranking Position ... 17
3.3.2 Brand Name Repetition ... 18
3.4 Operationalization of Variables ... 18
3.4.1 Brand Awareness ... 19
3.4.2 Internet Savviness ... 20
3.4.3 Materialism ... 20
3.5 Descriptive Statistics of Sample ... 20
3.6 Plan for Data Analysis ... 21
4. RESULTS ... 23
4.1 Condition Overview ... 23
4.3 Discussion of Results ... 27
5. DISCUSSION ... 29
5.1 Conclusion ... 29
5.2 Research Limitations & Recommendations for Future Research... 30
LITERATURE ... 32
APPENDIX ... 35
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MANAGEMENT SUMMARY
Nowadays it is not that hard to open your browser and search for something on Google. Google is probably even set as your homepage. However, most search engine users do not realize that the results on Google can be manipulated by organizations that want you to click on their link. Organizations use SEM to acquire the highest position and manipulate the SERP ranking.
However, acquiring the highest position on the SERP ranking costs resources. Young companies that are trying to gain brand awareness do not have these resources yet. For them it is advised to look into different directions. Is ranking the only thing that marketing managers can do to gain clicks and brand awareness?
This thesis analyzed the effect of brand name repetition in combination with SERP ranking position on both unaided an aided brand awareness. Internet savviness and materialism were respectively added as a moderator and as a control variable.
It turned out that SERP ranking was a slightly significant predictor of aided brand awareness. However, none of the EV’s, SERP ranking position and brand name repetition, were actually significant when the other variables, such as internet savviness and materialism were entered in the model. Individual characteristic, such as familiarity with established brands and materialism were much better predictors for brand awareness.
Although the insignificant results, it is still advisable to young companies to keep repeating their brand name in the search result. Theory has suggested that repetition leads to memory, which will on its turn lead to the intended awareness in future purchase situations.
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ABSTRACT
Nowadays it is not that hard to open your browser and search for something on Google. Google is probably even set as your homepage. However, most search engine users do not realize that the results on Google can be manipulated by organizations that want you to click on their link. Organizations use SEM to acquire the highest position and manipulate the SERP ranking. However, is ranking the only thing that marketing managers can do to gain clicks and brand awareness? This thesis will analyze the effect of brand name repetition in combination with SERP ranking position on both unaided an aided brand awareness.
1. INTRODUCTION
1.1 Searching and Finding Information Online
Imagine you have to purchase a product that you have never purchased before. You have no knowledge about the product and no idea what brands are available in the market. As always, you decide to use Google as a search engine to gather information about the product, the options and the brands that offer the product. You are probably not the only one gathering information this way. In May 2011, it was the first web site to achieve one billion monthly unique visitors (Business Insider, 2011). Moreover, according to Alexa Traffic Rank (2019)1, Google.com is the most popular web site in the United States, as well as in the world.
After your Google search, you find yourself facing an overkill of search results on the so-called search engine results page (SERP). You decide to click on the first link, because why not? However, what most people do not realize is that search engine results on Google, and especially the ranking of these results, can be manipulated by implementing search engine marketing (SEM) (Jansen & Spink, 2007)
SEM consists of two variants: paid and unpaid SEM. Paid SEM can be done by using search engine advertising (SEA), where organizations bid, i.e. pay money in a competition against other firms, for the highest ranking. The more you pay, the higher your search result will be on the Google SERP ranking. Unpaid SEM is done by using search engine optimization (SEO) techniques. In this
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variant, organizations try to optimize their website and search result in such a way that the algorithm of the search engine will place the link to their website higher in the SERP ranking.
Recently, the debate about SERP ranking and the manipulation of the ranking has been sparked in the United States. For example in August 2019, prominent American news websites, such as CNN2, CNBC3 and the New York Times4, have covered content about the manipulation of search results on search engines, such as Google. These news channels reported the bias that a SERP position can give towards political orientation. For instance, if a searcher encounters only republican pages and opinions on news articles on the first page of their Google search results and democrat views on the second page, it is likely that the searcher will be biased towards the republican view on certain topics.
Search engine results manipulation is not only relevant for politics. All kind of businesses and organizations can use SEM in trying to improve their SERP position. Take for instance the online retail sector. This sector has become indispensable in the last decade of Dutch retailing (CBS, 2018). For instance, the Dutch consumers spent 23.7 billion Euro online in 2018 (Emerce, 2019)5.
Moreover, 79% of Dutch inhabitants older than 15 years old indicated that they participate in online shopping. These numbers indicate a large opportunity for entrepreneurs. Yet, also a lot of online competition, which is a challenge for online retailers and brands in general. For instance, there are around 41.000 individual web shops in the Netherlands in 2019 (Statista, 2019)6, with most online companies increasing their spending in online marketing (Garside, 2007). It is therefore important, but difficult, for these online businesses to stand out from the clutter and get recognized by search engine users, because there is a massive choice overload for them.
1.2 Using SEM to Beat The Search Engine Clutter
Fortunately, standing out from the clutter can be done by implementing SEM correctly. As mentioned in the previous paragraph, SEM is a way to reduce searching barriers for the customer and allows them to find your website more easily. In this thesis we will therefore aim to find
2 https://edition.cnn.com/2019/08/19/politics/trump-google-manipulated-votes-claim/index.html
3 https://www.cnbc.com/2019/08/19/trump-claims-google-manipulated-votes-after-internal-docs-leak.html 4 https://www.nytimes.com/2019/08/19/us/politics/google-votes-election-trump.html
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more insights in how companies can use SEM to improve their findability on the results page of the search engine.
Yet, SEM is very broad and can be applied in many ways. Anything that improves your position and makes your brand more visible on the SERP can be regarded as SEM (Delaney, 2006). Many consider search engine optimization (SEO) and search engine advertising (SEA) as the most important methods of SEM (Berman & Katona, 2013; Panda, 2013). These two methods aim at gaining an advantage over competitors by getting the best SERP ranking. SEO aims to gain the most organic clicks and where SEA aims to get on top of the SERP ranking by advertising. Both these methods focus on trying to acquire the best ranking on the SERP.
However, SEM is much broader than just SEO and SEA and generating clicks. According to Dou et al. (2010), a way of SEM that should also be considered by marketing departments, besides SEO and SEA, is the use of branding to stand out in search engine results. In general, branding can be done in different ways. For instance, with the logo, colors, but perhaps most importantly for search engines: the brand name (Grewal et al., 1998). Currently, companies can put text in three parts of a search result on Google, i.e. (1) the search result title, (2) the URL itself (i.e. website address) and (3) the search result description This means that a company can thus mention their brand name repeatedly in different parts of the search result, in the hope that people will become aware of and recall the brand name better, also for future searches or purchases. Literature that researches the positive relationship between repetition and recall and memory goes back to the late 1800’s (Smith, 1896) and early 1900’s (Ebert & Meumann, 1904; Reed, 1914, etc). Thus, this relationship and effect are not new on its own. However, the
relationship has not been tested in an online search engine context. For this reason, brand name repetition will be used as the second experimental variable in this experiment.
1.3 Brand Awareness
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the recent years the definition of brand awareness has been extended. For instance, according to Lee & Leh (2011) brand awareness consists of five variables: brand recognition, brand recall, top-of-mind, brand dominance and brand knowledge. The last three variables are added to the definition of brand awareness given by Keller (1993). Moreover, the definition of brand recall got split into unaided recall and aided recall. (Keller, 2008).
One of the motivators for organizations for creating brand awareness, that keeps returning in past research, is brand salience. Brand salience is “the extent to which a brand visually stands out from its competitors” (Van der Lans et al., 2008). Organizations want consumers to be aware of their brand because they should recall the brand when they are intending to purchase anything related to the product the organization is offering. High brand salience thus means high brand awareness, which is essential for brands in the purchase of a consumer (Alba & Chattopadhyay, 1986).
To fill the gap that research has left on long-term effectiveness of SEM, this thesis will focus on the brand awareness that search engine results generate as the dependent variable. This thesis will focus on the definitions of brand awareness given by Keller (2008), since I am interested in the split between aided and unaided brand awareness that Keller describes.
1.4 Short Term vs Long Term Effectiveness of SEM
Visually standing out from competitors is very relevant for brands, since most shoppers tend to browse just a few seconds before they consult their memory and previous encounters with brands (Van der Lans et al., 2008). In these few seconds, it would thus drastically increase the brand awareness if a brand has a high level of salience. Visually standing out is also very relevant for SEM because also online, most shoppers normally spend less than 10 seconds on the results page (Granka et al., 2004).
But why is it so important to stand out in these 10 seconds on the SERP? There is an entire process and logic behind brand salience leading to future purchases. According to Alba & Chattopadhyay (1986), consumers have a very limited set of brands they consider when they are in the decision of making a purchase. Research has shown evidence that, in the situation of browsing for brands, consumers heavily rely on their memory of previous encounters with
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of. A high level of brand salience will make it possible for the brand that a consumer is thus aware of the brand. Moreover, in line with the argument made by Alba and Chattopadhyay (1986), once the consumer is aware of a brand, the brand will then be considered in (future) purchase decisions. Therefore, a brand does not only want to have a high level of salience because it leads to a short term purchase. A brand also wants a high level of salience because it will lead to awareness and long term consideration of the brand in future purchase decisions. These effects can therefore be regarded as long term effects of brand awareness.
Unfortunately, research has not yet investigated brand awareness in the context of online search engines thoroughly. Jerath, Ma & Park (2014) confirm this by stating that “the commercial success of sponsored search advertising in the past decade has motivated a significant body of work studying its different aspects”. However, this literature has only focused on which
keywords advertisers should bid on, what their bidding strategies should be, and how advertisers can improve the performance with regards to short-term success factors, such as click-through rates and conversion rates. Despite the importance of both the short- and long-term effects of advertising, researchers, have focused mainly on the short-term effect of keyword search ads. However, advertisers are starting to recognize that search engine advertisements can have long-term effects or branding implications (Yoo, 2014). Some researchers even claim that search results can help build brand awareness, regardless of whether people click on them (Hansell 2005)
Literature has, thus far, left this gap in the long-term effects of search engine marketing. Therefore, this thesis will focus on the influence of SEM on the awareness level of the brand itself, for brands can be seen as long-term equity.
This statement is confirmed by Kitts & LeBlanc (2004), who argue that search engine effectiveness is largely centered on the number of clicks generated, although evidence suggests that advertisers are more interested in the effectiveness of branding than actual clicks. These arguments lead to the following problem statement.
1.5 Problem Statement
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not many research into the branding effects of search engine results, while research into these effects is becoming indispensable. As mentioned before, that is why this thesis will try to fill this gap, also because branding is long-term focused, while generated clicks is very short-term
focused. The goal of this thesis is therefore to answer the following research questions: how does the SERP ranking position and brand name repetition in a company’s search engine result
influence brand awareness? This question will be answered by answering the following sub questions:
1. What is the effect of the SERP ranking position on the level of brand awareness? 2. What is the effect of brand name repetition on the level of brand awareness?
3. What is the effect of brand name repetition on the effect of SERP ranking position and the level of brand awareness?
4. What is the effect of the level of internet savviness on the effect of SERP ranking position on the level of brand awareness?
5. What is the effect of the level of materialism on the level of brand awareness?
The aim of these questions is to generate suggestions for the marketing department of bouw7, a young company that is excessively trying to gain brand awareness. Bouw7 has been chosen because it is a young brand, that is trying to compete with established brands. According to Dou et al. (2010), both well-known brands and lesser known brands can profit from improving their position on the SERP. Big brands do not automatically appear on top of the SERP because with good SEM strategy, small brands can come on top of the SERP and outperform big brands when it comes to online noticeability.
Although the playing field should be equal because of this, the problem for young companies and small brands is that it becomes more difficult to stand out on the SERP because global spending in online marketing keeps increasing (Garside, 2007). Big brands have relatively large budgets when it comes to SEM. It is therefore important for smaller brands to spend the budget that is available very efficient.
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2. LITERATURE REVIEW
If you search for something on a search engine such as Google, almost all search results look the same. Therefore, there are not a lot of methods that can be used to stand out from the competitors. Fortunately, there are some ways in which brands can stand out on Google. This chapter, in which I review the current literature on the topic of brand awareness in the context of an online search engine, will explain these methods and thus how brands can visually stand out from the competitors on the SERP.
2.1 SERP Ranking Position & Brand Awareness
A large amount of research on decision making, marketing, and cognitive psychology, has investigated online search behavior (Häubl & Trifts, 2000; Bechwati & Xia, 2003; Klein & Ford, 2003; Kulviwat, Guo, & Engchnil, 2004). It turns out that, as problem solvers, people usually search for information trying to maximize the accuracy of the search outcome while minimizing the effort exerted to acquire it (Bettman, 1979). One of the most obvious reasons for clicking on and/or remembering a certain brand from a search engine is therefore the SERP ranking position.
The bounded rationality theory (Simon, 1955; Stigler, 1961) could be consulted to explain why people do not look past the first few results on the SERP. The bounded rationality theory argues that individuals have “limited cognitive resources to acquire and process all the available information. They therefore frequently choose alternatives that are satisfactory, rather than optimal, expending only the effort necessary (Garbarino & Edell, 1997; Häubl & Trifts, 2000)”.
Thus, the bounded rationality theory is very useful in explaining why people click the results that are on top of the SERP ranking. However, it does not explain why people also should be more aware of the results on top of the SERP. A theory that could explain why this happens is the theory of priming. Priming
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Based on these theories, it can be expected that search engine users will try to minimize the effort in acquiring the desired information and that they, thus, will look at the highest ranked search results. The first hypothesis can therefore be described as:
H1: The degree of brand awareness will increase, if the SERP ranking position increases.
2.2 Brand Name Repetition & Brand Awareness
The previous theory explains why people click certain links and ignore others. But how can we explain, besides the obvious SERP ranking theory, why people recognize and recall certain brands while they forget the other brands on the SERP.
As mentioned in the introduction, research that examines the relationship between repetition and memory started in the late 1800’s and the early 1900’s. More recent research has found many current research fields with regards to memory and repetition, such as advertising (Webb, 1979), branding (Burke & Skrull, 1988), music (Schweinberger et al., 1997) and the negative effects of repetition on memory (Peterson et al., 2012).
Earlier I explained why brands want consumers to be aware of their brand. This can be done by making your brand visually stand out compared to competitors. One way of achieving this brand salience could be repeating your brand name. According to Britt et al. (1972), the average consumer is confronted with 300 to 600 advertisements per day. However, only 53 percent of consumers are able to recall an advertisement they have seen (Franz, 1986). This means that 47 percent of people do not have any recollection of what brands or advertisements they had seen that day. This loss in memory can be explained by misplaced attention. People do not pay attention to the brands, they purely watch the content of what is presented to them (Burke & Skrull, 1988), whether this is an advertisement or a search engine search result.
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Moreover, Peterson & Mulligan (2012) dedicated an entire research towards the negative effect of repetition. According to them, repetition does not always achieve the intended goal. This is mostly because of the generation effect, which means that people think in pairs and categories which they previously encountered. To counter this negative effect, respondents will be presented a list of brands which are not very common. More on this in the methodology chapter.
Although literature reports some negative effects of repetition, it is still highly likely that brand name repetition will lead to a higher level of brand awareness (brand recall + brand recognition) (Burke & Skrull, 1988). Therefore, the second hypothesis will be:
H2: The degree of brand awareness will increase, if the Brand name gets repeated in the
search result.
Now it has been established that it can be expected that SERP ranking and brand name repetition will have a positive effect on brand awareness. But what if these two interact with each other? Can we expect that these two will amplify each other? The answer to that is yes. Not only do the SERP ranking position and brand name repetition add up to each other, they also add an extra interaction effect. As mentioned in the previous paragraph, the bounded rationality theory suggests that people do not look far on the SERP because they try to minimize the efforts for finding the result they are looking for. This would mean that the repetition of a brand name would be even more effective if the result has a high SERP ranking position as well. Therefore the third hypothesis is:
H3: The positive effect of brand name repetition on the degree of brand awareness will
increase if the SERP ranking position increases.
2.3 Internet Savviness and Skepticism Towards Advertisements
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Lewandowski (2017) argues that researchers and marketeers assume that search engine users understand the distinction between paid advertisements and organic search results.
However, in his experiment, Lewandowski (2017) showed that the majority of internet users are not able to tell the difference between advertisements and organic search results on Google. An interesting variable that could explain why people do not see the difference between
advertisements and organic search results is internet savviness. Internet savviness, or internet search skill, is intensively researched by Novak in the late 90’s. For instance, Novak et al. (2000) argue that consumers who show signs of high internet search skill, and thus are internet savvy, have a large control over the information they perceive on the web, which would mean that internet savvy users would have a large understanding of the difference between advertised search results and organic search results.
But what happens once a search engine user is internet savvy and knows the difference between and advertised result and an organic result? They can become skeptic towards advertised search results, especially when claims of advertisements are very subjective and are not measured in a standard way (Ford et al., 1990). It therefore also depends on the keyword and search result claims how high the level of skepticism is towards the result. It can be assumed that consumers, who show signs of skepticism towards advertisements, are more likely to click organic links and are likely to ignore advertised links.
These findings are confirmed by research by Dou et al. (2010). It is argued by them that people with a low degree of internet search skill are more influenceable by the SERP ranking and less by the actual content of the search result. On the other hand, people with a higher degree of internet search skill would be less influenced by the SERP position because they have experience with search engines and are probably aware of the fact that the best results are not always on top of the SERP ranking, thus the advertised links.
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H4: The level of internet savviness will weaken the positive relationship between SERP
ranking and brand awareness.
2.4 Materialism & Brand Awareness
The second variable, that can impact brand awareness through online search engines, is materialism. According to Chuchinprakarn (2003), there is evidence that consumers who pay more attention to brand names, and are therefore more likely to remember them, show higher levels of materialism. In the context of this thesis, it can therefore be expected that respondents who show higher levels of materialism are more likely to have a higher brand attention, since they pay more attention to brand names. The final hypothesis can therefore be constructed as:
H5: The degree of brand awareness will increase if the degree of materialism increases.
2.5 Conceptual Model
All the previous mentioned variables and its relationships lead to the following conceptual model (figure 1):
H1(+) H4 (-)
H3 (+)
H2 (+) H5 (+)
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The following table (table 1) will give a clear overview of the hypotheses for this model:
H1 The degree of brand awareness will increase, if the SERP ranking position increases.
H2 The degree of brand awareness will increase, if the Brand name gets repeated in the search result.
H3 The positive effect of brand name repetition on the degree of brand awareness will increase if the SERP ranking position increases.
H4 The level of internet savviness will weaken the positive relationship between SERP ranking and brand awareness.
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3. METHODOLOGY
In this chapter I will explain how the experiment was formed and conducted among the respondents. First an overview of the experiment design will be given, followed by the variables and the measurement scales of these variables.
3.1 Experiment Design
As introduced in the introduction, brand awareness will be used as the dependent variable.
SERP ranking and brand name repetition will be used as the experimental variables. The experiment in this thesis will consist of a 2x3 design. The experimental variable SERP ranking
consists of 2 groups: high and low ranking. In this variable high ranking will be manipulated by putting the focal brand at the second ranking on the SERP. On the other hand, a low ranking will be manipulated by putting the focal brand at the 7th ranking out of the eight brands. A simplified overview of this can be seen in table 2 below.
Variable/group Brand name included only in search result title
Brand name included only in search result description
Brand name included in both search result title and description
High SERP Ranking
Condition 1 Condition 2 Condition 3 Low SERP
Ranking
Condition 4 Condition 5 Condition 6
Table 2: Experiment Conditions
3.2 Procedure
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The experiment will be tested in the following way: Respondents will be shown a SERP where the ranking and the brand name repetition will be manipulated. The SERP will contain an imaginary brand, because the respondents should not have a bias already towards one of the shown brands.
Moreover, the experiment will only contain the textual part of a SERP. Pictures and other minor salient factors, such as advertisements, will be disregarded, since they can influence the respondent in a way that is not part of the intended manipulation.
3.3 Experimental Variables
The experimental variables have been manipulated by manipulating both the SERP ranking position and the brand of the focal brand name “Accme” within the search results. Accme has been chosen as the fictive brand name, since Acme is a popular fictional brand name in the US7. Besides that, Accme includes the first letters of the word accounting.
I started with the SERP of a Google search into brands that offer accounting software with the keyword “Boekhoudpakket”. After removing some interfering salient aspects of the SERP, such as advertisements and ratings, the image on the next page (image 1) showed up.
Afterwards I edited the page to manipulate both the SERP position and the brand name repetition of the focal brand Accme. These results can be seen in the next two paragraphs, after the original SERP.
Manipulation checks were not conducted for these manipulations because both were factual manipulations. The focal brand Accme was either high or low positioned on the SERP ranking and the brand name was named in either one or in both the title and the description of the search result, which cannot be interpreted differently.
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3.3.1 SERP Ranking Position
The SERP ranking position was manipulated by swapping the 2nd SERP or the 7th result (of the 8 results) for a search result of Accme. I have chosen to put this result at the 2nd or 7th ranking because the first and last ranking positions would be too obvious. The manipulated SERP looked as follows (image 2):
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3.3.2 Brand Name Repetition
The brand name of the focal brand Accme has been named in the title, the description or in both of them. This is manipulated by generating a fictive search result for Accme where the brand name was thus repeated or not. The result of this manipulation can be shown in the following images (image 3-5):
Image 3: Accme brand name only in the title
Image 4: Accme brand name only in the description
Image 5: Accme brand name in both the title and the description
3.4 Operationalization of Variables
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Variable Source Items Scale Factor Analysis Eigenvalue % & Cronbach Alpha Brand Awareness Based on Nicholls et al. (1999)
1. Please write down all brands, that you can remember from the previous page, that offer accounting software. (Unaided) 2. Do you remember seeing the following
brands? (Aided) Yes-No, nominal Internet Savviness Novak et al. (2000)
1. “I am extremely skilled at using Internet search engines.”
2. “I consider myself knowledgeable about good search engine use techniques.” 3. “I know somewhat more than most users
about using Internet search engines.” 4. “I know how to find what I am looking for
using Internet search engines.”
5. “Compared to other things that I do on the web (e.g., email, chat, etc.), I’m very skillful at using Internet search engines.” 6. “Compared to other skills that I have (e.g.,
sports, cooking, singing), I’m very skillful at using Internet search engines.”
7 point Likert scale. 3.761 (62.68%) .893 Materialism Richins (1987)
1. It is important to me to have really nice things.
2. I would like to be rich enough to buy anything I want.
3. I’d be happier if I could afford to buy more things.
4. It sometimes bothers me quite a bit that I can’t afford to buy all the things I would like.
5. People place too much emphasis on material things.
6. It’s really true that money can buy happiness. 7 point Likert scale 2.965 (59.31%) 8.25 (after deleting item 5) Control Variables
1. What is your gender? 2. What is your age?
3. How familiar are you with brands that offer accounting software?
Nominal Ratio
7 point Likert scale
Table 3: Operationalization of the variables.
3.4.1 Brand Awareness
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3.4.2 Internet Savviness
Internet savviness is based on the scale by Novak et al. (2000), which named their variable “internet search skill”. This construct measures how good an internet user is in finding information they are looking for on a search engine. The scale is very straight forward and is measured with a seven-point Likert scale, where 1 represents being extremely skillful at searching on the internet and where 7 represents being extremely bad at searching information on the internet.
3.4.3 Materialism
The materialism operationalization is based on research by Richins (1987). Once again, the variable is measured with a seven-point Likert scale, where 1 represents being extremely materialistic and where 7 represents being extremely unmaterialistic. However, there is one exception in this operationalization. The scale for item 5 is reversed. This item had to be removed during the analysis, since the Cronbach alpha would be higher if the item was deleted. Thus, to improve the reliability of the scale, the item was deleted.
3.5 Descriptive Statistics of Sample
In total 335 respondents opened the survey via the distributed link. However, only 191 responses were completed. Within these 191 responses, 10 were not useable due to failing the attention check. This led to 181 responses that were considered useful. After analyzing the dataset, I found that there were some duplicate responses. Because of this, a total of 179 responses were considered to be valid. These responses were distributed among the groups in the following way:
SERP ranking/ brand name repetition
Brand name included only in search result title
Brand name included only in search result description
Brand name included in both search result title and description High SERP Ranking n = 32 (17.9%) n = 22 (12.3%) n = 32 (17.9%) Low SERP Ranking n = 33 (18.4%) n = 26 (14.5%) n = 34 19%)
Table 4: Experiment Condition Distribution
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In the dataset, there was a strange outlier: one person remembered all the 8 brands from the SERP correctly. After checking the other data of this respondent, there was no reason to assume that this was an invalid response. Therefore this respondent has been included in further analysis.
3.6 Plan for Data Analysis
As a preparation for the analysis, some dummy variables have been created. These variables consist of: SERP Rank (High vs Low), Brand Name Position (Title only, Description only, Both) and the according condition the respondents were in (combination of both EV’s.).
After making these conditional dummy variables, I conducted a factor analysis and a reliability analysis on the multi-item scales internet savviness and materialism. It turned out that both of these variables consisted of 1 factor. In the case of materialism, the Cronbach alpha could be improved by deleting item 5 of that scale, which is what I did.
After that, I made dummy variables for the DV, about whether the respondents remembered seeing the focal brand “Accme” either aided and/or unaided. It turns out that only 26 (14.5%) respondents remembered seeing Accme without any aid. However, 91 (50.8%) respondents indicated that they remembered seeing Accme with the aid of seeing the brands, including some filler brands. After this, I made a dummy variable on whether Accme was the first brand that the respondents remembered or if the brand was in the first 3 positions that the respondent could remember. This caused me to use four different dependent variables: 1. Brand awareness unaided, 2. Brand awareness aided, 3. Brand awareness rank 1, 4. Brand awareness top 3. The results of the analysis will be presented for the different models that have been introduced in the previous chapter.
All in all, the formula for the conceptual model, that will be used in the analysis, can be formulated as:
Y = β0 + β1XSERP+ β2XBrand name repetition+ β3XSERPXBrand name repetition+
β4XInternet Savviness+ β5XSERPXInternet Savviness+ β6XMaterialism+ 𝛽7𝑋𝐺𝑒𝑛𝑑𝑒𝑟 + 𝛽8𝑋𝐺𝑒𝑛𝑑𝑒𝑟+ 𝛽9𝑋𝐹𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑖𝑡𝑦
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Model Description Formula
1 Experiment design 𝑌 = 𝛽0+ 𝛽1𝑋𝑆𝐸𝑅𝑃+ 𝛽2𝑋𝐵𝑟𝑎𝑛𝑑 𝑛𝑎𝑚𝑒 𝑟𝑒𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛 2 Design + interaction effects 𝑌 = 𝛽0+ 𝛽1𝑋𝑆𝐸𝑅𝑃+ 𝛽2𝑋𝐵𝑟𝑎𝑛𝑑 𝑛𝑎𝑚𝑒 𝑟𝑒𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛 + 𝛽3𝑋𝑆𝐸𝑅𝑃𝑋𝐵𝑟𝑎𝑛𝑑 𝑛𝑎𝑚𝑒 𝑟𝑒𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛 3 Design + interaction effects + internet savviness + interaction with SERP 𝑌 = 𝛽0+ 𝛽1𝑋𝑆𝐸𝑅𝑃+ 𝛽2𝑋𝐵𝑟𝑎𝑛𝑑 𝑛𝑎𝑚𝑒 𝑟𝑒𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛 + 𝛽3𝑋𝑆𝐸𝑅𝑃𝑋𝐵𝑟𝑎𝑛𝑑 𝑛𝑎𝑚𝑒 𝑟𝑒𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛+ 𝛽4𝑋𝐼𝑛𝑡𝑒𝑟𝑛𝑒𝑡 𝑆𝑎𝑣𝑣𝑖𝑛𝑒𝑠𝑠 + 𝛽5𝑋𝑆𝐸𝑅𝑃𝑋𝐼𝑛𝑡𝑒𝑟𝑛𝑒𝑡 𝑆𝑎𝑣𝑣𝑖𝑛𝑒𝑠𝑠 4 Design + interaction effects + materialism + gender + age + familiarity
Y = β0+ β1XSERP+ β2XBrand name repetition
+ β3XSERPXBrand name repetition+ β6XMaterialism
+ 𝛽7𝑋𝐺𝑒𝑛𝑑𝑒𝑟+ 𝛽8𝑋𝐺𝑒𝑛𝑑𝑒𝑟+ 𝛽9𝑋𝐹𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑡𝑦
5 Full model Y = β0+ β1XSERP+ β2XBrand name repetition
+ β3XSERPXBrand name repetition+ β4XInternet Savviness
+ β5XSERPXInternet Savviness+ β6XMaterialism
+ 𝛽7𝑋𝐺𝑒𝑛𝑑𝑒𝑟+ 𝛽8𝑋𝐺𝑒𝑛𝑑𝑒𝑟+ 𝛽9𝑋𝐹𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑡𝑦
Table 5: Models for Analysis
The analysis, which consists of ANOVA tests and binary logistic regressions, will be conducted per each of the 5 models, and per each of the four DV’s. This means that 20 regressions will be conducted. I have chosen to do a binary logistic regression, since the DV’s are measured in a binary way. The respondents are either aware of Accme (1) or they are not (0). The results of these binary logistic regressions can be found in tables 9 and 11 in the next chapter. After conducting these regressions, I checked the omnibus tests of model coefficients to see if the model in the regression was significant and checked both the R-squared numbers. After this check I went to see if the effects of the IV’s on the DV’s were significant (sig.) and what the direction of this effect was (B).
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4. RESULTS
In this chapter, the results of the analysis will be presented and will be used to discuss the meaning of the results of the experiment that has been conducted for this thesis. As mentioned in the previous chapter, 20 regressions have been conducted for each model and each DV. These DV’s are: (1) remembered Accme unaided, (2) remembered Accme aided, (3) remembered Accme unaided top 3, (4) remembered Accme unaided first. The following table (table 6) shows how many of the respondents actually remembered Accme:
Respondents (of 179 in total)
% of total
1. Remembered Accme unaided 26 14.53%
2. Remembered Accme aided 91 50.84%
3. Remembered Accme unaided, top 3 25 13.97% 4. Remembered Accme unaided, first 10 5.59%
Table 6: How many respondents remembered seeing Accme?
The average amount of correctly remembered brands of the respondents is just 1.2, which means that people will, on average, only remember 1 brand correctly after seeing a Google search with 8 available brands. For this reason, I have chosen to not include the last two DV’s. Since the people that remembered Accme automatically put Accme in their top 3, it is not relevant enough to do further analysis with this DV. The same holds for the respondents who put Accme in the first place when being asked for the brands they could remember. Only 5.59% of the respondents put Accme in first place. This number is so small that it is not relevant to do further analysis on this DV as well. Therefore I continue doing further analysis on the first two DV’s. The next table shows the distribution of the first two DV’s per each condition and how well Accme was remembered over both the EV’s.
4.1 Condition Overview
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Variable/group Brand name included only in search result title
Brand name included only in search result description
Brand name included in both search result title and description
Total per condition High SERP Ranking 5/32 unaided (15.63%) 20/32 aided (62.50%) 4/22 unaided (18.18%) 12/22 aided (54.55%) 7/32 unaided (21.88%) 20/32 aided (62.50%) 16/86 unaided (18.6%) 52/86 aided (60.47%) Low SERP Ranking 2/33 unaided (6.06%) 16/33 aided (48.48%) 3/26 unaided (11.54%) 10/26 aided (38.46%) 5/34 unaided (14.71%) 13/34 aided (38.24%) 10/93 unaided (10.75%) 39/93 aided (41.94%) Total per condition 7/65 unaided (10.77%) 36/65 aided (55.38%) 7/48 unaided (14.58%) 22/48 aided (45.83%) 12/66 unaided (18.18%) 33/66 aided (50%) Table 7: Remembered seeing Accme, per condition.
Table 7 clearly shows that respondents who saw Accme high on the SERP ranking had the highest awareness in both the unaided and aided question than the respondents who saw Accme low on the SERP ranking. On the other hand, the results for brand name repetition are not as clearly in table 7. The respondents who saw the brand name of Accme in both the title and description had the highest awareness of Accme when it comes to unaided brand awareness. However, when it comes to aided brand awareness, the respondents who saw the brand name of Accme only in the tile had the highest aided awareness of Accme. To get a better feeling of this data, two charts (chart 1 & 2) have been created which show the data from the table. These charts can be found below.
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Chart 2: Remembered seeing Accme aided, per condition.
4.2 Logistic Regressions
After getting a general feeling for the data and the brand awareness per condition, it was time to conduct further analysis of the data. At first, to get a glimpse of the significance of the relationships, ANOVA tests have been conducted per DV. After that the logistic regression analyses have been conducted to test the relationships of the variables in each of the previous described models. The results for both unaided and aided brand awareness will be discussed in the next two paragraphs.
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Brand Awareness Unaided, B=
Model 1 Model 2 Model 3 Model 4 Full Model
SERP Ranking .65 .53 .33 .22 .11 Dummy Brand in title only -.37 -.74 -.66 -1.13 -.84 Dummy Brand in both .62 .98 1.02 1.31 1.25 SERP*title only .52 .67 1.15 1.10 SERP*both -.57 -.61 -.71 -.66 Internet Savviness .31 .64* Internet Savviness*SERP -.89** -.95** Materialism .28 .25 Age -.05** -.05** Gender -.07 .01 Familiarity -.40*** -.42***
Rsquared (Cox & Snell .021 .022 .057 .097 .123 Rsquared (Nagelkerke) .037 .040 .101 .171 .219 F(sig.) .291 .543 .161 .033** .015**
Table 8: Regression Analysis for Unaided Brand Awareness *= 90% significant
**= 95% significant ***= 99% significant
Brand Awareness Aided, B =
Model 1 Model 2 Model 3 Model 4 Full Model
SERP Ranking .75 ** .65 .71 .50 .56 Dummy Brand in title only .37 .41 .49 .39 .48 Dummy Brand in both -.22 -.42 -.42 -.37 -.35 SERP*title only -.08 -.16 .22 .18 SERP*both .42 .42 .35 .31 Internet Savviness .34* .46** Internet Savviness*SERP -.35 -.38 Materialism .45*** .38** Age -.03 ** -.03*** Gender .34 .28 Familiarity -.23** -.26, ***
Rsquared (Cox & Snell .039 .041 .059 .115 .138 Rsquared (Nagelkerke) .052 .055 .078 .154 .183 F(sig.) .068* .186 .146 .009*** .006***
Table 9: Regression Analysis for Aided Brand Awareness *= 90% significant
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4.3 Discussion of Results
What do these tables say about the hypotheses that have been formed in chapter 2? From both tables, it can be concluded that model 1, model 2 and model 3 are not significant on a 95% significance level. Model 4 and model 5 are considered to be significant after checking the omnibus test of model coefficients.
As can be seen in table 8, there are four significant effects (90% significance level) on unaided brand awareness in the full model test (model 5). These are the familiarity with brands that offer accounting software, age, internet savviness and the interaction effect of internet savviness and SERP ranking. From table 9, it can be also be concluded that the SERP ranking position, internet savviness, materialism, age and familiarity with brands that offer accounting software have a significant effect on the aided brand awareness of Accme.
Based on the statistics in table 9, it can be assumed that the SERP ranking does have a significant effect on aided brand awareness. However, this does only hold for the first model, in which only both the EV’s are considered. In the case that there are no other variables that influence the aided brand awareness, SERP ranking is a better predictor than brand name repetition. When more variables are added to the equation, SERP ranking position becomes less and less significant. Other variables, such as internet savviness, materialism and familiarity with brands that offer accounting software become better predictors of aided brand awareness.
Especially the familiarity with brands that offer accounting software showed a very high level of significance (99% significance level) on aided brand awareness. The results in this experiment displayed a negative direction of this effect. Since the scale for familiarity was negative, this means that the effect of familiarity with accounting software is actually positive on brand awareness. This makes sense, since the involvement of people who are familiar with accounting software was probably much higher than the involvement of the people who are not familiar with brands that offer accounting software. They are therefore more aware of the brands that were presented and might have recognized Accme as a not familiar brand, which made Accme stand out.
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effect is actually negative. Which means that the higher the level of internet savviness of the respondents, the lower the aided brand awareness of Accme.
The negative relationship between age and the degree of brand awareness is also
significant. This means that the higher the age, the lower the degree of unaided brand awareness of Accme. This could say something about targeting strategies for marketing managers. The younger people will easier be aware of the brand.
Table 10 summarizes whether the hypotheses from chapter 2 can be accepted or rejected for both aided and unaided brand awareness of Accme. In the next chapter, a final conclusion will be formed and recommendations for future research will be given.
Hypothesis Hypothesized Results Unaided Results Aided
H1 Brand awareness will increase if the SERP ranking position increases.
Rejected Accepted for model 1, rejected for the other models. H2 Brand awareness will increase if the brand name
gets repeated in the search result.
Rejected Rejected H3 The positive effect of brand name repetition on
the degree of brand awareness will increase if the SERP ranking position increases.
Rejected Rejected
H4 The level of internet savviness will weaken the positive relationship between the SERP ranking position and the degree of brand awareness.
Partially accepted Rejected
H5 The degree of brand awareness will increase if the degree of materialism increases.
Rejected. Partially accepted
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5. DISCUSSION
This chapter will be used to form a final discussion about the experiment that was conducted in this thesis. First of all, a conclusion for marketing managers will be given. Second, the limitations of this research and the current research field will be discussed, followed by recommendations for future research in the topic of SEM and brand awareness.
5.1 Conclusion
To conclude, the results for aided brand awareness indicate that it does pay off to put resources into SEM, because a high SERP ranking position leads to a higher degree of brand awareness. However, the marketing managers should also consider that internet savvy searchers can see through the game of SEM and that these search engine users are not influenced by SERP ranking alone. If internet savvy searchers are not affected by SERP ranking position, then maybe they might get influenced by brand name repetition. Although there were no significant effects of brand name repetition on either unaided or aided brand awareness, it is still advised to repeat the name of your brand in both the title and description. The fact that there was no significant result in the conducted experiment does not mean that repetition does not lead to brand awareness. Some respondents explicitly mentioned that they did not remember the brands because they were too busy reading the descriptions of the search results. Coincidently out of the eight original SERP results in the experiment, only 3 used their brand name in the description. 2 of them were low ranked SERP results. Based on this, it would make sense that the people who focus on search result descriptions only would not remember the brands when they were asked for it.
Unfortunately, there were not a lot of hypotheses that could be accepted due to the lack of significance. Moreover, the results that are significant do not tell us a lot about implementing SEM, but more about the characteristics of search engine users. During the analysis there were also some results that popped up, that were not hypothesized, but still can be used for marketing managers.
First, it can be concluded that, for unaided brand awareness, there is a significant effect of the level of internet savviness on the positive relationship of the SERP ranking position on the degree of brand awareness. This means that when people show a higher level of internet
30
mentioned in chapter 2, internet savvy searchers should know that there is a difference between paid and unpaid search results. They probably also know that paid search results may not lead to their intended goal of finding information (Dou et al. 2010). The fact that this is not the case in this research means that SERP ranking is still useable, even when the searcher is very savvy. This is something that marketing managers of young companies, such as bouw7 should consider.
Secondly, the results indicate that it can be concluded that materialistic people tend to have a lower level of aided brand awareness than unmaterialistic people. As mentioned in chapter 2, materialistic people value brand names more and are therefore more likely to be aware of them. Again, this theory is rejected by the results of the conducted experiment. Marketing
managers should therefore not focus on the level of materialism, but find other theories that could back up the fact that brand name repetition is useful.
Lastly, marketing managers of young companies, such as bouw7, should consider the degree of familiarity that consumers already have with the established brands. This result can be used to conclude that, as mentioned in chapter 2, search engine users do consult their memory and awareness of previous encountered brands when it comes to browsing to brands. In this case, the respondents who were familiar with accounting software were also aware of Accme.
Targeting “experts” in the field of software, would therefore be a great marketing campaign.
5.2 Research Limitations & Recommendations for Future Research
Although the experiment in this research was thoroughly prepared and well thought out, there remain some limitations to this research. One of these limitations is the relatively small sample size that was used in the experiment. The survey reached 360 respondents, however, only 50% of these responses were considered useful. Many respondents stopped after seeing the Google image.
Unfortunately, only 26 of those respondents remembered the focal brand Accme without any aid. Besides, the average brand that the respondents remembered correctly was just 1.2. This indicates that people just do not remember many search results, let alone brands. Some respondents
31
brand awareness. Another limitation of this research is therefore that it primarily only focused on whether the brand name was repeated, instead of where the name was placed.
For future research I would recommend that there should be deeper research into variables that can be manipulated by marketing departments. In this experiment, there were a lot of characteristics measured. Only two variables, SERP ranking position and brand name repetition, were manipulated, and five were passively measured. After the analysis it turned out that all, except for one, significant results belonged to the passively measured variables. These are variables that cannot be directly changed by marketing managers.
Another recommendation for future research is that researchers should consult the research by Balatsoukas & Ruthven (2012) when it comes to the position in which the brand name should be mentioned. Their article gives a good indication where people look when they are searching for something on Google.
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APPENDIX
Appendix 1: Survey
SEM Branding Survey
Start of Block: Introduction
Q19 Welcome to this survey! Please select your preferred language (Dutch or English) on the top right of this page and press the arrow to begin.
Welkom bij deze vragenlijst! Selecteer de gewenste taal (Nederlands of Engels) rechtsboven op deze pagina en druk op de pijl om te beginnen.
Page Break
Q21 Dear Participant, Thank you for your participation in my study. As a token of my appreciation, you can win a €20 Bol.com voucher. 1. Note that this survey will include attention checks. Therefore, please always read the question first before answering. 2. Please do not talk about the content of this survey with other people. We -once again- thank you for your cooperation! Please click on the arrow below to start.
End of Block: Introduction
Start of Block: SERP introduction
Q4 Please imagine the following situation:
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End of Block: SERP introduction
Start of Block: SERP Image
One of the 6 SERP images. See chapter 3 for how these images were created.
End of Block: SERP Image
Start of Block: Brand Attention
Q6 Please write down all brands, that you can remember from the previous page, that offer accounting software. If you do not remember all of them, you can leave a blank space.
o
Brand 1: (1) ________________________________________________o
Brand 2: (2) ________________________________________________o
Brand 3: (3) ________________________________________________o
Brand 4: (4) ________________________________________________o
Brand 5: (5) ________________________________________________o
Brand 6: (6) ________________________________________________o
Brand 7: (7) ________________________________________________o
Brand 8: (8) ________________________________________________ Page Break37 Yes (1) No (2)
⊗
Exact (1)o
o
⊗
Twinfield (2)o
o
⊗
Accme (3)o
o
⊗
Rompslomp (4)o
o
⊗
Unit4 (5)o
o
⊗
Moneybird (6)o
o
38 Strongly agree (1) Agree (2) Somewhat agree (3) Neither agree nor disagree (4) Somewhat disagree (5) Disagree (6) Strongly disagree (7) I am extremely skilled at using Internet search engines (1)
o
o
o
o
o
o
o
I consider myself knowledgeable about good search engine use techniques (2)o
o
o
o
o
o
o
I know somewhat more than most users about using Internet search engines (3)o
o
o
o
o
o
o
To check your attention, please select "strongly agree" (4)o
o
o
o
o
o
o
I know how to find what I am looking for using Internet search engines (5)o
o
o
o
o
o
o
Compared to other things that I do on the web (e.g.,email, chat, etc.), I’m very skillful at using
Internet search engines. (6)
39 Compared to others skills that I have (e.g., sports, cooking, singing), I’m very skillful at using Internet search engines. (7)
o
o
o
o
o
o
o
Page BreakEnd of Block: Internet Search Skill
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End of Block: Materialism
Start of Block: Background Characteristics
Q10 What is your gender?
o
Male (1)o
Female (2)Q7 What is your age?
________________________________________________________________
Q20 How familiar are you with brands that offer accounting software?
o
Extremely familiar (1)o
Familiar (2)o
Slightly familiar (3)o
Not familiar/ not unfamiliar (4)o
Slightly unfamiliar (5)o
Unfamiliar (6)o
Extremely unfamiliar (7)42
Start of Block: End note
Q16 Thank you for participating in this research about search engine results and brand awareness! Please fill in your email address If you would like to have a chance to win the €20 bol.com voucher
________________________________________________________________
