Impact of Search Engine Optimization Dimensions on SME Companies
using Online Promotion in Malaysia
WONG CHEE HOO1, CHONG KIM LOY2, AW YOKE CHENG3, DONNA TUNONG SIGAR2,
ZAMZUL KHAIRI BIN ZULKIFLI2, JOANNIE JOMITOL2
1Faculty of Business and Communication, INTI International University, MALAYSIA
2UNITAR Graduate School, UNITAR International University,MALAYSIA
3Office of the Registrar,BERJAYA University College,MALAYSIA
Abstract: - This study aims to investigate the influence of Search Engine Optimization (SEO) aspects on Online
Promotion among Malaysian SME companies. The literature identifies four SEO dimensions that influence
Online Promotion: SEO Connectivity, SEO Competitiveness, SEO Experience, and SEO Techniques. The
online survey received 153 responses from Malaysian SME service providers. In addition to descriptive
statistics, the data were subjected to Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis.
The proposed framework builds a strong relationship between SEO Dimensions and Online Promotion for
Malaysian SME businesses. According to the analysis findings, there is a significant relationship between SEO
Competitiveness and Online Promotion for Malaysian SME businesses. In addition, the data found a significant
relationship between SEO Experience and Online Promotion. The value of SEO Competitiveness and SEO
Experience, as well as the responses to the study, show that these tactics are frequently used in Online
Promotion for SME companies in Malaysia. The findings will help company decision-makers enhance their
internet presence and reach. It may result in decreased marketing expenses and a rise in new clients,
consequently boosting the company's sales revenue.
Key-Words: - Search Engine Optimization, Online Promotions, SME, Malaysia.
Received: October 27, 2022. Revised: April 9, 2023. Accepted: May 3, 2023. Published: May 15, 2023.
1 Introduction
In today's competitive world, Internet use is rising
rapidly. It is almost hard to find information online
without a search engine. SEO is a marketing
strategy that tries to enhance the number of visitors
to a website from search engines through unpaid,
organic, editorial or natural search results. It seeks
to improve a website's position on Search Engine
Results Pages (SERP), [1]. SEO is a marketing
strategy for raising the search rankings of web
content. SEO in scientific publishing involves
creating a document so search engines may easily
find and send people to web content. SEO helps
websites rank higher in SERPs. SEO is performed
by using keywords strategically, best practices in
website design, and the open-access nature of
website content, [2]. It could also be beneficial in
the studies of behaviour and preferences in
browsing websites, [3], [4].
MCMC has reported that 88.7% of Malaysians
utilise the Internet, [5]. Users between the ages of
16 and 64 spend an average of 9 hours and 17
minutes online daily, [6] and Google is the search
engine of choice for 99.1% of users. Furthermore,
98.39% of Malaysians use the Internet to find
information, [7] and 6% use a search engine before
purchasing a final product, [8]. These statistics
demonstrate how online information searching has
become more popular over time. According to SME
statistics, 98.5% of business establishments in
Malaysia are SMEs, [9]. 38.9% of the GDP was
contributed by SMEs in 2018, [10]. Only 30% of
Malaysian SMEs employ SEO and other marketing
tactics to reach external stakeholders. The impact of
the Internet on technology is growing. The usage of
the Internet for advertising and business is also
expanding. It is important to stay ahead of the
competition and serve a broad audience.
Due to the scarcity of research on the influence
of SEO Dimensions and Online Promotion on SME
businesses in Malaysia, it is difficult for small
businesses to grasp the significance of SEO as an
efficient digital marketing tool. Internet use for
conducting business and advertising several types of
organizations is also rapidly rising. As a result, it is
critical to stay one step ahead of the competition and
to cater to the demands of a diverse range of people.
As Internet technologies continue to evolve at a
breakneck pace, SMEs must invest in and exploit
search engines to obtain access to global markets
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and compete with larger enterprises in their area.
This study aims to determine whether SEO
Dimensions, which are SEO Connectivity,
Competitiveness, Experience and Techniques
significantly impact Malaysian SMEs that use
online promotions.
1.1 Research Objectives
This study's objectives are to examine the influence
of four SEO Dimensions on Online Promotion.
1) To examine the relationship between SEO
Connectivity and Online Promotion for SME
companies in Malaysia.
2) To examine the relationship between SEO
Competitiveness and Online Promotion for SME
companies in Malaysia.
3) To examine the relationship between SEO
Experience and Online Promotion for SME
companies in Malaysia.
4) To examine the relationship between SEO
Techniques and Online Promotion for SME
companies in Malaysia.
2 Literature Review
2.1 Mozlow's Hierarchy of SEO Needs
In 2019, Rand Fishkin, the co-founder of SEOmoz,
came up with Mozlow's Hierarchy of SEO Needs.
This model is based on a simple pyramid structure
in which each piece is built on top of the previous
one. It is a visual representation of the factors that
should be considered when analysing the strengths
and weaknesses of an organisation's organic search
campaign. It is the most effective method for
prioritising search engine Optimization efforts to
maximise their effectiveness, [13].
Fig. 1: Mozlow's Hierarchy of SEO Needs, [13]
2.2 Dependent and Independent Variables
The research focuses on Online Promotion as the
dependent variable. For SEO dimensions relating to
connectivity, user experience, competitiveness, and
techniques will be independent variables.
2.2.1 Online Promotion
Sales promotion is organically increasing brand
awareness, retaining, and acquiring customers
through various channels, including television,
radio, print media, social media, and websites, [14],
[15].
The relationship between a website as a sales
promotion medium and SEO is discussed in this
research study to determine the extent to which SEO
Dimensions affect Online Promotion. A simple
relationship between SEO and sales promotion can
be illustrated as needing to maintain websites to
increase traffic and promote products or services.
One of the most effective ways to gain brand
consumer support is to combine a strong organic
SEO strategy with an effective content strategy,
[16]. Since the term sales promotion encompasses a
broader range of activities, the preferred term is
Online Promotion.
Other terms, such as web-based and online
brand promotion, refer to activities conducted via
the Internet and are thus considered synonymous
with Online Promotion. Online Promotion is a type
of marketing conducted via the Internet, [17].
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2.2.2 SEO Competitiveness
The goal of SEO is to place a website in the top
position. According to the Google Webmaster Tools
manual, the earlier a page is ranked in search
results, the higher chance for the company to gain
customers. After assessing a search ranking from 1
to 20, 80% of new website visits originate from
search engines, and 84% of that number never click
to the second page or the advertising links created
by the search results, [18].
Another study on digital marketing in the
Chennai hotel business shows that hotel websites
that are effectively and frequently optimized for
search engines using SEO led to earlier placement
on search engine result pages (SERPs) and gained
new customers, [19], [1]. When compared to
companies using traditional methods, companies
that apply SEO to the market are getting more new
customers, [20]. Thus, recognising competitiveness
is a significant component in SEO and should be
considered by businesses because appearing on the
first page of Google will likely bring many visitors
to their website.
2.2.3 SEO Connectivity
Web visitors desire quick answers and fast page
loads. It is a squandered opportunity for many sites,
especially since more than half of mobile visitors
leave if a page takes over 3 seconds to load, [21].
Slow mobile experiences make real users less likely
to find what they need or buy in the future.
Many people use search engines as a gateway to
the Web, making search engines a critical link in the
chain connecting content suppliers and users, [1].
The evaluation of search engine optimization (SEO)
algorithms is heavily dependent on bookmarks,
social signals, and the effect of content providers in
order to determine the value of websites, [22].
Because of this finding, a website that implements
SEO can increase traffic by gaining quality
backlinks and increasing authority. Search engines
have drastically impacted how Internet users access
information, shop for goods and services, research,
interact with others, and enjoy themselves online.
Websites optimised with SEO enhance the
companies' brand equity and improve awareness of
products and services provided by the companies,
[23].
2.2.4 SEO Experience
SEO plays a vital role in developing a robust
foundation for businesses by developing an
attractive website with a practical and clean user
experience that can be easily discovered through the
search engine, [24]. A combination of SEO process
and experience is crucial to increasing users'
experience that will benefit both customers and the
company, [25]. The respondents of the studies are
primarily experienced with the SEO strategy, and
their experience with regularly used tactics
positively impacts their company websites. SEO is a
long-term strategy since it can have an instant
impact on the company based on the actions taken;
these future actions will have a long-term impact
that will last for several years. With the market's
evolution, it is vital for businesses to monitor
changes and trends regularly. Even if the website
does not follow all SEO suggestions, businesses
may accomplish and deliver a satisfactory
experience to online customers by following the
fundamental stages, [24]. Thus, without a positive
user experience, users will have difficulty locating
information on company websites, creating a
negative impression, [26].
2.2.5 SEO Techniques
One of the most common SEO strategies used to
increase website ranking is on-page Optimization,
which is a technique used by website developers to
optimise or produce content for websites.
Since keyword factors would lead to website
improvement, it is best to consider the SEO
Techniques of keyword Optimization, e.g., usage of
keywords, related keywords, prefix and suffix, and
they should apply to the entire domain and must be
used in search queries, [27].
In order to boost Google's ranking, website
developers may also need to conduct regular content
Optimization and structure Optimization, which
include their URL, Meta page title, Meta
description, and Site content besides keyword
Optimization. Under these Optimizations, the design
of excellent websites may increase visitor traffic
relatively fast, [27].
Most of the SEO research is concentrated on
SEO Techniques. According to Aleksandar's (2020),
[24] research on applying SEO Techniques in
Internet marketing, SEO techniques make websites
easier to categorise and find. Two types of SEO
strategies for increasing a website's non-sponsored
search engine visibility: redesigning the site to make
it more consumer-friendly or concentrating
exclusively on methods that affect the search
engine's quality ranking process, [28]. Search
engines publish official guidelines to clarify which
techniques are acceptable and which are not, [29]. In
severe cases, search engines may remove websites
that engage in Black Hat SEO activities from the
organic list, [30].
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White Hat SEO refers to SEO tactics that adhere
to the guidelines and rules established by search
engines and do not adversely affect a website's
ranking, [31]. These techniques may not produce
immediate results, but they gradually improve the
SERP ranking and the likelihood of the website
being declined by the search engines decreases.
Additionally, the traffic generated by White Hat
SEO is frequently superior, and Optimization lasts
longer, [32]. To this end, even if a website offers
high-quality products and services that benefit
online customers' daily lives or work tasks and
activities, the website will fail to succeed if online
users cannot find and visit it.
2.2.6 Proposed Research Framework
The following conceptual framework serves as a
springboard for further investigation. The
relationship between Online Promotion and the SEO
Dimensions, which include SEO Connectivity, SEO
Experience, SEO Competitiveness, and SEO
Techniques, is depicted in Figure 2.
Fig. 2: The Study's Proposed Theoretical
Framework
The proposed theoretical frame is extended to PLS-
SEM analysis. Figure 3 is for the labels used in the
PLS-SEM analysis.
Fig. 3: Labels used in PLS-SEM Analysis
2.2.7 Hypotheses Development
H1: There is a significant relationship between
SEO Connectivity and Online Promotion for
SME companies in Malaysia.
H2: There is a significant relationship between
SEO Competitiveness and Online Promotion
for SME companies in Malaysia.
H3: There is a significant relationship between
SEO Experience and Online Promotion for
SME companies in Malaysia.
H4: There is a significant relationship between
SEO Techniques and Online Promotion for
SME companies in Malaysia.
3 Methodology
This study uses quantitative analysis to identify the
impacts of SEO Dimensions as independent
variables —Competitiveness, Connectivity,
Experience, and Techniques—on Online Promotion,
a dependent variable. Each variable is quantified
using a total of 33 questions that employ both
nominal and Likert scales. The research
questionnaire was designed to address the study's
four objectives and is divided into three sections:
Section A (demographic information), Section B
(independent variables), and Section C (dependent
variable). Section A contains ten questions designed
to elicit information about the respondents. This
section will categorise respondents and their
companies by gender, years of experience in digital
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marketing, job title, business type, company size,
annual revenue, number of sales and marketing
employees, annual SEO budget, SEO usage, and
type of search engine used. Section B contains 19
questions that examine the factors that most
significantly affect Online Promotion for Malaysian
SME businesses. Four distinct variables will
evaluate respondents: connectivity, experience,
competitiveness, and techniques. The questions
assist businesses in gaining a better understanding
of the variables associated with Online Promotion.
Finally, Section C includes four questions about the
dependent variable: Online Promotion, all of which
ascertain respondents' approval of the overall impact
of SEO strategy on their companies' Online
Promotion.
The questionnaires for the independent variables for
this study are based on an instrument developed by
Dinesh & Senthil Murugan, 2018, [33] and Kittur &
Mane, 2019, [34]. The dependent variable is based
on an instrument developed by Bhandari & Bansal,
2018, [19] and Lockett, 2018, [35]. The questions
were answered using the Likert scale, which
quantifies respondents' agreement with a set of
statements about the variables being measured.
Convenience sampling is used for this study.
The population for this study is drawn from lists
published by the Malaysian Digital Economy
Corporation (MDEC) Sdn. Bhd and the Selangor
Information Technology and Digital Economy
Corporation (SIDEC). Based on Krejcie & Morgan,
1970, [36]; Bukhari, 2021, [37], a sample size of
153 respondents is necessary to achieve a
confidence level of 95% with a margin of error of
5% for a list of 250 SME digital marketers. The
collected data will be analysed based on descriptive
and inferential statistics. After the data cleaning, the
data will be examined with a reliability test,
frequency distribution, central tendency and
variability measurement, normality test, and partial
least square analysis.
4 Results And Discussion
4.1 Respondents’ Demographics Analysis
According to Table 1, 69.3% of the sample
consisted of males. 57.5 % of respondents had fewer
than four years of experience in Digital Marketing,
and approximately 37.3% were employed in
business development, sales, or marketing. With
(48.4%) of the businesses provide Digital Marketing
and e-Commerce services. Over (36.6%) of
companies are medium size (30 to less than 75
employees), and (56.9%) generate between
RM300,000 and RM3,000,000 in annual revenue.
(57.5%) of the company reviewing their website
SEO performance over 4 times annually. Most
respondents (97.4%) use the Google search engine.
Table 1. Respondents’ Demographics
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4.2 Reliability Test, Centre of Tendency and
Variability
According to Table 2, all Cronbach's Alpha values
are greater than 0.7, indicating that all employed
instruments have a high degree of internal
consistency. The mean for the variables OLPR
(4.019), COMP (4.164), CONN (4.072), EXP
(4.193), and TECH (4.095). All mean values are
relatively close to 4, indicating that respondents
agreed with the questions. Additionally, the standard
deviations for OLPR (0.448), COMP (0.450),
CONN (0.182), EXP (0.385), and TECH (0.489) are
small, indicating that the variation of data is small.
All variables have skewness values ranging from
+0.152 to +0.867, indicating that the data are
slightly skewed to the right. The range of kurtosis
values for competitiveness, experience, and
techniques are between -0.451 and -0.162,
indicating that the data have somewhat light tails.
Connectivity (0.769) and online promotion (0.403)
kurtosis values imply that the data have fairly heavy
tails.
Table 2. Reliability Test, Normality Test, Skewness,
Kurtosis, Mean and Standard Deviation
4.3 Normality Test
The hypothesis statements for the normality test are
shown below:
H0: The sample variable is normally distributed.
H1: The sample variable is not normally distributed.
Table 3 shows that the calculated p-values for the
Shapira-Wilk, Anderson-Darling and Lilliefors tests
are less than the significance level alpha=0.05;
hence the null hypothesis H0 should be rejected, and
the alternative hypothesis H1 should be accepted. It
can conclude that all variables do not follow a
normal distribution. Thus, a different approach is
needed to reach a more vital conclusion. Partial
Least Squares Structural Equation Modelling (PLS-
SEM) with SmartPLS was used for additional
analysis.
Table 3. Normality Test Result
4.4 PLS-SEM Analysis and Results
According to Wong (2019), [38], PLS-SEM analysis
is used when the sample size is limited and the data
distribution is skewed. The PLS path modelling
estimation in the following Figure 4 are the
observations.
Fig. 4: PLS-SEM Results
Variable\Test Shapiro-Wilk Anderson-Darling Lilliefors
AVR COMP < 0.0001 < 0.0001 < 0.0001
AVR CONN < 0.0001 < 0.0001 < 0.0001
AVR EXP < 0.0001 < 0.0001 < 0.0001
AVR TECH < 0.0001 < 0.0001 < 0.0001
AVR OLP < 0.0001 < 0.0001 < 0.0001
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4.4.1 Target Endogenous Variable Variance
According to table 4, the endogenous latent variable
Online Promotion has a Coefficient of
Determination, R-Square = 0.549. This means that
the four latent variables SEO Competitiveness, SEO
Connectivity, SEO Experience, and SEO Technical
moderately explain 54.9% of the variance in Online
Promotion.
4.4.2 Inner Model Path Coefficient Measurement
and Significance
According to the PLS-SEM results in Figure 4 and
Table 4, the p-value for the inner model path
coefficient SEO Experience (0.490) and SEO
Competitiveness (0.238) is less than 0.05. It can
conclude that there is a significant relationship
between SEO experience and online promotion, as
well as between SEO competitiveness and online
promotion, for SME companies in Malaysia. The p-
value for the inner model path coefficients for SEO
Connectivity (0.083) and SEO Techniques (0.066) is
greater than 0.05, indicating no significant
relationship between SEO Connectivity and Online
Promotion and between SEO Techniques and
Online Promotion for Malaysian SME companies. It
can also be proved that its standardized path
coefficient is smaller than 0.10.
Table 4. Inner Model
4.4.3 Explanation of Outer Model Loading
The outer model illustrates the relationship between
the latent variables SEO Competitiveness, SEO
Connectivity, SEO Experience, and SEO
Techniques and their respective indicators. From the
result in table 5, the indicators of COMP3 (0.853)
and COMP2 (0.713) had the highest path
coefficients for SEO Competitiveness, followed by
COMP1 (0.551) and COMP4 (0.387). This
demonstrates that both COMP3 and COMP2
strongly correlate with SEO Competitiveness.
Meanwhile, correlations between indicators and the
latent variable range from moderate to strong for
SEO Connectivity; indicator CONN1 scored 0.842,
followed by CONN3 (0.790), CONN2 (0.616), and
CONN4 (0.563). Correlation values are significant
for SEO Experience, with EXP2 (0.800) having the
highest correlation with the latent variable. EXP1
(0.789), followed by EXP4 (0.766), EXP3 (0.732),
EXP5 (0.655), and EXP6 (0.614). Similarly, for
SEO Techniques, all indicators demonstrate a
significant correction with the latent variable, with
TECH4 exhibiting the greatest correlation value of
0.874, followed by TECH5 (0.798), TECH3 (0.797),
TECH1 (0.740), and TECH2 (0.626).
4.4.4 Indicator Reliability
The term "indicator reliability" refers to the
proportion of indicator variance that the latent
variable may explain. A reliability score of at least
0.4 is deemed appropriate for exploratory research.
Competitiveness, COMP2 (0.509), and COMP3
(0.728) are all reliable measures of competitiveness.
As a result, COMP1 (0.304) and COMP4 (0.150)
are unreliable indicators of competitiveness.
CONN1 (0.710) and CONN3 (0.624) are reliable for
evaluating connectivity variables. CONN2 (0.379)
and CONN4 (0.317) are not reliable indicators of
connectivity. EXP1 (0.622), EXP2 (0.640), EXP3
(0.536), EXP4 (0.586), and EXP5 (0.429) are all
reliable for evaluating experience variables, but
EXP6 (0.377) is not. Online Promotion
demonstrates that OLP1(0.612), OLP3(0.611), and
OLP4 (0.713) are reliable indicators, while OLP2
(0.065) is unreliable for evaluating variables
associated with Online Promotion.
4.4.5 Composite Reliability and Average
Variance Extracted (AVE)
In social science research, Cronbach's alpha has
been used to measure the reliability of internal
consistency, but it gives a conservative estimate
when PLS-SEM is used. Previously published
literature has advocated using Composite Reliability
as a substitute, [39]. As shown in Table 5, all
composite Reliability values are more than 0.6,
demonstrating the high internal consistency
reliability of all five reflective latent variables. Each
latent variable's Average Variance Extracted (AVE)
is analysed to determine convergent validity. All
AVE values exceed the permissible threshold of 0.5,
demonstrating convergent validity.
4.4.6 Discriminant Validity (Fornell-Larcker
Criterion)
Discriminant validity is demonstrated by evidence
that measures of constructs that theoretically should
not be highly related to each other are, in fact, not
found to be highly correlated to each other. The goal
Standard
error
Value
(Bootstrap)
Standard error
(Bootstrap)
Critical
ratio (CR)
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of discriminant validity evidence is to be able to
discriminate between measures of dissimilar
constructs, [11]. The Fornell-Larcker criterion is one
of the most popular techniques used to check the
discriminant validity of measurement models, [12].
Discriminant validity can be established if the
square root of the AVE in each latent variable is
greater than the other correlation values among the
latent variables, [40]. This is accomplished by
manually calculating the square root of AVE and
bolding it on the table's diagonal.
As shown in Table 6, the latent variable CONN is
found to be 0.713. This value is greater than the
correlation values in the CONN column (0.548,
0.196, 0.374) and greater than the correlation values
in the CONN row (0.328). Similar observations are
made for the latent variables COMP, EXP, TECH,
and OLP. As a result, discriminant validity appears
to be well-established.
Table 5. Summary of Outer Models Loading,
Indicator and Composite Reliability and Average
Variance Extracted
Table 6. Fornell-Larcker Criterion Analysis for
Checking Discriminant Validity
From the analysis of PLS-SEM, it can be concluded
that SEO Competitiveness and SEO Experience
significantly impact Online Promotions.
5 Conclusion and Recommendations
According to the OECD's 2019 report, Online
Promotion offers significant potential for SMEs,
from global reach to "targeting" techniques based on
advanced analytics and user data, which online
platforms excel at. Understanding the dimensions of
SEO on Online Promotions is critical for being
found when customers are looking for a competitor
and for being a dependable member of the World
Wide Web. It is unknown what effect search engine
optimization (SEO) has on marketing. Since SEO is
associated with organic traffic, which refers to
unpaid or free listings, it is critical to investigate its
effect on Online Promotion. This study examined
how four SEO dimensions affect online promotion
in Malaysian SME businesses. PLS-SEM revealed
the hypotheses H2: There is a significant
relationship between SEO Competitiveness and
Online Promotion for Malaysian SMEs, and H3:
There is a significant relationship between SEO
Experience and Online Promotion for Malaysian
SMEs. In addition, the research found that
hypotheses H1 and H4 are not supported. The
relationship between SEO Connectivity, Techniques
and Online promotion is insignificant. According to
the finding, the research objectives of this study
were achieved. Malaysian SMEs may expand their
reach and visibility through Online Promotion by
applying the dimension of SEO Competitiveness
and SEO Experience. This could result in lower
advertisement costs and increase more
new customers, boosting the company's sales
revenues. Due to the underrepresentation of this
subject in Malaysia's commercial and academic
worlds, particularly in SMEs, this research outcome
will be able to generate sufficient incentives to merit
future recognition and implementation.
Based on the study's findings and conclusions,
future research should develop more SEO criteria
based on academic industry-related studies of SEO
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in Malaysia's SMEs, focusing on the most effective
SEO strategies. It is recommended that the research
be conducted with a larger sample size that
accurately represents the genuine population of
SMEs in Malaysia who employ SEO tactics. It is
recommended that future research use a mixed
method approach, which combines quantitative and
qualitative methods to learn more about the topic of
the research. Data, yet effective in obtaining reliable
responses.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution as well as
editing and internally reviewing this paper. Aw
Yoke Cheng has also contributed as the
corresponding author of this paper.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
The authors thank INTI International University,
Malaysia, for providing financial support to publish
this paper.
Conflict of Interest
The authors have no conflict of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.92
Wong Chee Hoo, Chong Kim Loy,
Aw Yoke Cheng, Donna Tunong Sigar,
Zamzul Khairi Bin Zulkifli, Joannie Jomitol
E-ISSN: 2224-2899
1007
Volume 20, 2023