=Paper=
{{Paper
|id=Vol-3885/paper17
|storemode=property
|title=Development of Websites Ranking Algorithm Based on SEO Metrics
|pdfUrl=https://ceur-ws.org/Vol-3885/paper17.pdf
|volume=Vol-3885
|authors=Irakli Basheleishvili,Giorgi Kapanadze,Sergo Tsiramua
|dblpUrl=https://dblp.org/rec/conf/ivus/BasheleishviliK24
}}
==Development of Websites Ranking Algorithm Based on SEO Metrics==
https://ceur-ws.org/Vol-3885/paper17.pdf
Development of Websites Ranking Algorithm Based on
SEO Metrics*
Irakli Basheleishvili1,∗,†, Giorgi Kapanadze1,† and Sergo Tsiramua2,†
1
Akaki Tsereteli State University, Kutaisi, 4600, Georgia
2
University of Georgia, Tbilisi, 0171, Georgia
Abstract
The paper deals with the development of websites ranking algorithm and its web application
based on search optimization metrics data. The application provides web page search
optimization analysis and website ranking based on it, which will allow both entities and
companies to select the best websites to post information about their products or services.
The algorithm is based on Entropy Weight and TOPSIS methods of multi-criteria decision
analysis.
Keywords
Website, ranking, algorithm, SEO, Entropy, TOPSIS.
1. Introduction
The development of the Internet and web technologies has led to a growing demand for online
sales. Online sales are an effective and convenient way for businesses to increase brand awareness,
credibility with potential customers, and sales [1]. Through the Internet and web technologies, both
entities and companies sell their products and services, moreover, companies create their websites for
online sales, which is associated with high costs, therefore, entities, and small and medium-sized
companies find it difficult to pay this cost. To solve this problem, many sites allow businesses to post
information about their products or services so that they are easily accessible to end users. Today
there are many such websites, their excess creates the need for companies to make the right choice in
site selection. Internet users collect text, sentences, and combinations of words in the search engine,
and therefore trust the site that they see first from the options offered by the browser. A general
criterion for selecting a website for a business is that the site is easily searchable and visible to the
user, which is responsible for search engine optimization (SEO) [2]. Sites that rank high in search
engines are considered to meet high quality and reliability standards, thus increasing the credibility of
that business [23, 24].
Through good SEO, a business can direct its services or products to not one, but at the same time,
several target audiences and, if this process is carried out effectively, simultaneously and equally
reach those users who may be interested in its products. Many SEO metrics can be used to determine
how advanced a website is in search engines.
The use of the above helps us to select a highly rated site for our business, which is an actual issue
for business today. The issue's urgency stems from the great practical importance of solving the
problem.
Based on the relevance of the mentioned problem, the goal of our work is to develop a ranking
algorithm, which will enable the subject or company to select the best website for their business.
Through the application offered by us, companies or entities will be able to choose a website for
their business, without specialist consultation, which is related to financial costs.
*
IVUS2024: Information Society and University Studies 2024, May 17, Kaunas, Lithuania
1,∗
Corresponding author
†
These author contributed equally.
Irakli.basheleishvili@atsu.edu.ge (I. Basheleishvili); kapanadze.giorgi2@atsu.edu.ge (G. Kapanadze); s.tsiramua@ug.edu.ge (S.
Tsiramua)
0000-0002-4429-7577 (I.Basheleishvili); 0009-0002-8663-7012( G. Kapanadze); 0009-0006-7338-5177 (S. Tsiramua)
©️ 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
Thus, the novelty of the research lies in the development of the website ranking algorithm and its
software, thus we finally get a software tool that makes the process of selecting websites for business
efficient and easy.
2. SEO metrics
SEO metrics are a way to measure your search engine optimization performance and make
corrective changes based on metrics [11, 12, 13]. When creating a website, if key metrics are not
considered, the website's ability and search engine ranking will be overlooked. Key metrics are
extremely important and directly impact Google's ranking factors. One of the reasons why search
engine optimization can be effective is to control the metrics data and measure everything. SEO
metrics provide key insights into how your organic search strategy is performing [12, 13, 14, 25]. In
addition, SEO metrics can be called vital data points of a website to create a better strategy or to
drastically improve an existing strategy. Simply put, if we can't measure it, we can't manage that data.
Without detailed monitoring, it is impossible to discover the website's potential and increase both
organic search traffic and revenue. At the same time, potential threats to existing businesses can be
overlooked by digital marketing radars. Moreover, many search engine metrics are ready to perform
large-scale marketing opportunities. The search engine is usually always changing, so Google is
always ready to update its search algorithm. With all of the above in mind, it's important to regularly
monitor SEO metrics to ensure that the website is properly optimized to deliver benefits[1, 2]. To
monitor any changes to the site through organic search, it is necessary to focus on the key metrics that
have the most impact on the search engine, and ultimately the business [14, 15].
In our research, we have chosen the main metrics that provide important information about the
website as evaluation criteria, namely [11, 12, 13]:
Organic Traffic - This is the visitors who come to the website from various free sources,
simply put it is free traffic. These sources include search engines such as Google, Yahoo or
Bing. A brand of digital marketing whose goal is to improve organic traffic can be called
search engine optimization. Organic Traffic is the most important form of traffic a website
can receive. All this is much more important than paid traffic or traffic from social media
networks.
Keyword ranking - This is a web page's ranking, and position, in search results for specific
words. Most web pages have multiple keywords when navigating to different pages. Search
results will vary based on what Google has deemed to be most relevant for that particular
search word or phrase. When a user searches for a specific keyword, the ranking URL will be
the web page listed for that keyword. A single web page can rank for a relevant search term
and phrase.
SERP Visibility - This metric represents the estimated monthly traffic received by monitoring
the keywords in the project. It is defined as the ratio of the search volume of the query to the
click-through rate of the current ranking position. Output value This is a metric that reflects
the change in ranking according to its potential.
Click-Through Rate - This is a ratio that shows how often people clicked on hyperlinks
compared to who viewed those links. Click-through rate (CTR) can be used to measure how
well your keywords and ads are performing on a web page. CTR is calculated by the number
of times an ad is clicked on a web page divided by the number of times the ad is displayed:
clicks ÷ views = CTR. For example, if we had 5 clicks and 100 views, then the CTR of the web
page would be 5%.
Bounce Rate - Is an important metric to measure user engagement on each page of a website.
It shows which pages are more interesting for visitors and which pages can be improved. It is
the number of visitors to a given web page who leave the web page after viewing one page.
For example, a user enters a web page, only browses it, and leaves without any clicks,
transactions, or any action.
Website Authority Over Time - This is an SEO concept that involves the overall "power" of a
particular domain. Power, in this case, is the ability, the probability, of how a web page's links
are ranked in search engines. Its indicator is measured on a scale from 1 to 100. A brand-new
website always starts with one authority score and this score slowly increases as the site
generates more and more authoritative links over time. Websites with a high DA (Domain
Authority) score have a better chance of ranking in search engines and getting more organic
traffic.
Page Speed - This is the loading speed, which measures how quickly the content of a web
page loads. From an SEO point of view, fast page speed is essential. Loading speed depends on
many factors, such as web hosting and application size. Web page loading speed is also
different for desktop and mobile versions of a web page.
Conversion Rate - An SEO conversion rate is the percentage of a specific action taken by
organic website visitors. To calculate it, we need to divide the number of users who perform
this action during a specific period by the total number of visitors to the website. The CRO
process involves understanding how users move through a website, what actions they take,
and what prevents them from achieving their goals [1, 11, 12, 13].
3. Related work
[3] In the paper, the authors propose a ranking algorithm for e-commerce websites that uses the
Fuzzy Topsis(Technique for Order of Preference by Similarity to Ideal Solution) method, the algorithm
is based on user ratings. The approach proposed therein focuses on the evaluation of e-commerce
websites by users, with linguistic variables representing fuzzy triangular numbers. The weights of
evaluation criteria are also determined by linguistic variables. Alternatives (websites) are ranked
using the TOPSIS method. In the mentioned approach, the ranking result of the websites is completely
dependent on the evaluation of the users.
[4] The paper deals with the use of SEO metrics in the evaluation of the quality of Wikipedia
articles. It presents the results of an analysis of various SEO indicators related to multilingual
Wikipedia and its reference.
[5] The paper proposes a technique for increasing the ranking of websites using grazing
optimization. [6] The paper proposed ranking of B2C websites using AHP(analytic hierarchy process)
and Fuzzy TOPSIS methods, in which evaluation criteria and their weights are determined by a
human-expert. [7] The paper proposes the evaluation of e-commerce websites using the Fuzzy
Hierarchical TOPSIS method.
Thus, there are many scientific studies related to the evaluation and ranking of websites, for which
multi-criteria decision analysis methods are actively used. In most of them, websites are evaluated by
a human expert, which may not always give you an objective result.
4. Defining the problem
The problem is choosing high-ranking websites for businesses to post information about their
services and products. The problem is similar to a multi-criteria decision problem: Given a set of
websites S= { s 1 , s 2 , s 3 , … , s m }and a set of evaluation criteria C={c 1 , c 2 , c 3 , … , c n } - which are SEO
metrics.
For each site s i, we must determine the value of the metric c j , and then we must determine the
decision matrix, based on which we must calculate the weights of the evaluation criteria and rank the
websites, to select the best one. The decision matrix has the following form:
Table 1
decision matrix
Keywo
Organi
rsion Rate
Authority
Conve
Bounc
Rankings
Click-
Visibility
Through
SERP
c Traffic
Page
Page
e Rate
Speed
Time
Over
Rate
rd
WebSite 1 x 11 x 12 x 13 x 14 x 15 x 16 x 17 x 18
WebSite 2 x 21 x 22 x 23 x 24 x 25 x 26 x 27 x 28
WebSite 3 x 31 x 32 x 33 x 34 x 35 x 36 x 37 x 38
WebSite 4 x 41 x 42 x 43 x 44 x 45 x 46 x 47 x 48
WebSite 5 x 51 x 52 x 53 x 54 x 55 x 56 x 57 x 58
.. ..
... ... ... ... ... ... ...
. .
WebSite m xm1 xm2 xm3 xm 4 xm5 xm6 xm7 xm8
Decision Matrix [21, 22] is a fundamental tool based on multiple criteria and used to compare
alternatives. Simply put, it is a powerful tool used to evaluate various options and make the best
choice based on pre-defined criteria. It is a structured approach to comparing options by assigning
weights to criteria and evaluating each alternative against those criteria, with the result being clear
and objective. To support and strengthen the fundamental decision, a matrix is used by assigning
weights to the criteria, which makes it more accurate and efficient.
The value of x ij in the decision matrix is determined through a special API. As can be seen from the
decision matrix, the criteria for evaluating websites are search engine optimization metrics.
5. Ranking algorithm
The ranking algorithm is based on the Entropy Weight and TOPSIS methods of multi-criteria
decision analysis [8, 10, 19, 20]. The Entropy Weight method [16, 17] is used to calculate the weight
values of the evaluation criteria, the use of the mentioned method is due to the specificity of the
problem because in our case the values of the evaluation criteria are not determined by human
experts. Thus, the biggest advantage of the Entropy Weight method is to avoid the interference of
human factors on the weight of the indicators, which enhances the objectivity of the evaluation
results.
TOPSIS is a multi-criteria expert method that is a mechanism for evaluating, ranking, and selecting
alternatives. The TOPSIS method has many advantages in the multidimensional space of data
processing. It is easy to use and programing. The number of steps remains the same regardless of the
increase in the number of attributes. The disadvantage of the method is that the use of Euclidean
distance does not take into account the ratio of attributes[19, 20].
The algorithm includes the following stages:
Step 1. Determination of the decision matrix - to determine the decision matrix, the user must
define the alternatives (websites), using a special API, we must evaluate the given alternatives
according to the criteria.
Step 2. Calculation of evaluation criteria weights:
Step 2.1 Normalization of the decision matrix by means of the following formula:
x (1)
r ij = m ij
∑ x ij
i=1
Step 2.2 Calculate the entropy using the following formula:
m (2)
e j =−h ∑ r ij ln r ij , j=1 , … , n
i=1
1
where h= , m is the number of alternatives.
ln ( m )
Step 2.3 Calculate the vector of weights using the following formula:
1−e j (3)
W j= n
∑ (1−e j )
j=1
Step 3. Ranking of alternatives:
Step 3.1 normalize the matrix using the following formula:
x ij (4)
r ij =
√
m
∑ x ij2
i=1
Step 3.2 Determine the weighted normalized matrix using the following formula:
V ij =w j∗r ij (5)
Step 3.3 Define positive ideal and negative ideal solutions as follows:
A positive ideal decision: +¿ }¿
(6)
+¿ , …, v ¿
n
+¿ , v 2 ¿
+¿={v 1 ¿
V
where
v
{+¿=
max ( v ij ) If criterion j has a positive impact
min ( v ij ) If criterion j has a negative impact
¿
i=1, m, j=1,n
j
Negative Ideal Decision: −¿ }¿
(7)
−¿ , …, v ¿
n
−¿ , v 2 ¿
−¿={v 1 ¿
V
vj
−¿=
{ min ( v ij ) If criterion j has a positive impact
max ( v ij ) If criterion j has a negative impact
¿
i=1, m, j=1, n
Step 3.4 Determine the distance to the ideal positive and ideal negative decision for each
alternative:
√ (8)
n
+¿= ∑ ( v −v ) ¿
¿ 2
ij j
di j=1
√ (9)
n
−¿= ∑ ( v ij −v 'j ) ¿
2
di j=1
Step 3.5 Calculate the alternative closest to the ideal decision. which is calculated by the following
formula:
d−¿
i
(10)
R i = −¿+d ¿ ¿ +¿
di ¿ i
6. Review of a practical example
Let's consider a practical example to better demonstrate the work of the algorithm. As an example,
we use five real websites that we want to rank, we evaluate the SEO metrics of these sites according to
real values, by means of which the decision matrix is determined. The names of the websites in the
decision matrix have been changed for privacy reasons. Page Speed is a criterion with a negative
impact.
Table 2
Decision matrix
Conversion
Page Speed
Through Rate
Keyword
Organic
Over Time
Bounce
Authority
Rankings
Click-
Visibility
SERP
Page
Traffic
Rate
Rate
WebSite 1 3% 51, 00 55, 00 10, 67 % 72, 90 % 70 1,5 MS 5, 8 %
WebSite 2 3,1 % 60, 00 56, 00 11 % 60, 50 % 68 2,4 MS 5, 5 %
WebSite 3 2% 64, 00 47, 00 9, 23 % 50, 10 % 49 3 MS 4, 9 %
WebSite 4 1,3 % 20, 00 30, 00 4% 28, 10 % 20 3,1 MS 4%
WebSite 5 0,4 % 18, 00 20, 00 2% 27, 10 % 19 4 MS 2%
As a result of normalization of the given decision matrix, we get the following matrix (Table 3):
Table 3
Normalized decision matrix
Over Time
Bounce
Conver
Keywo
Organi
Authority
Rankings
sion Rate
Click-
Visibility
Through
SERP
c Traffic
Page
Page
Speed
Rate
Rate
rd
WebSite 1 0,31 0,24 0,26 0,29 0,31 0,31 0,11 0,26
WebSite 2 0,32 0,28 0,27 0,30 0,25 0,30 0,17 0,25
WebSite 3 0,20 0,30 0,23 0,25 0,21 0,22 0,21 0,22
WebSite 4 0,13 0,09 0,14 0,11 0,12 0,09 0,22 0,18
WebSite 5 0,04 0,08 0,10 0,05 0,11 0,08 0,29 0,09
By deleting the normalized matrix, we calculate the entropy, which is given in the table below
(Table 4):
Table 4
Calculation of entropy
Keywo
Organi
rsion Rate
Authority
Conve
Bounc
Rankings
Click-
Visibility
Through
SERP
c Traffic
Page
Page
e Rate
Speed
Over
Rate
rd
0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9
0 3 6 1 5 2 7 7
Calculate the weights of the evaluation criteria given in the table below (Table 5):
Table 5
Weights of evaluation criteria
Convers
Organic
d Rankings
Keywor
Over Time
Authority
Click-
Visibility
Through
Boun
SERP
ion Rate
Page
Page
ce Rate
Traffic
Speed
Rate
0,20 0,14 0,08 0,18 0 0,16 0,05 0,06
W
269 946 085 276 ,09 564 814 830
After determining the weights, we can move to the stage of ranking the websites, for this we need
to normalize the matrix presented in Table 2, which has the following form (Table 6):
Table 6
Normalized decision matrix
Convers
Organic
d Rankings
Keywor
Over Time
Bounce
Authority
Click-
Visibility
Through
SERP
ion Rate
Page
Page
Traffic
Speed
Rate
Rate
WebSite 1 0,607 0,486 0,559 0,579 0,639 0,621 0,230 0,558
WebSite 2 0,627 0,572 0,569 0,597 0,530 0,604 0,368 0,529
WebSite 3 0,404 0,610 0,478 0,501 0,439 0,435 0,460 0,472
WebSite 4 0,263 0,191 0,305 0,217 0,246 0,178 0,475 0,385
WebSite 5 0,081 0,171 0,203 0,108 0,238 0,169 0,613 0,193
Let's define a weighted normalized decision matrix, which has the following form (Table 7):
Table 7
Weighted normalized decision matrix
Organic
d Rankings
Keywor
Over Time
Bounce
Conver
Authority
sion Rate
Click-
Visibility
Through
SERP
Page
Page
Traffic
Speed
Rate
Rate
WebSite 1 0,123 0,073 0,045 0,106 0,059 0,103 0,013 0,038
WebSite 2 0,127 0,085 0,046 0,109 0,049 0,100 0,021 0,036
WebSite 3 0,082 0,091 0,039 0,091 0,040 0,072 0,027 0,032
WebSite 4 0,053 0,028 0,025 0,040 0,023 0,029 0,028 0,026
WebSite 5 0,016 0,026 0,016 0,020 0,022 0,028 0,036 0,013
Determine positive ideal and negative ideal decision, using them to calculate the distance to ideal
positive and ideal negative decision for each alternative. by means of which we can determine the
decision closest to the ideal decision (Table 8):
Table 8
Ranking result
di- di+ Ri Rank
WebSite 1 0,17 0,02 0,9 2
WebSite 2 0,18 0,01 0,92 1
WebSite 3 0,13 0,06 0,68 3
WebSite 4 0,05 0,15 0,24 4
WebSite 5 0,00 0,18 0,00 5
From the data presented in the table(Table 4), it is clearly seen that WebSite 2 is the best option out
of the five listed websites.
7. Algorithm Implementation
The algorithm presented in the paper is implemented by our web application, which has a
responsive design, so that it can be used both on a computer and a mobile device. The Web API back
end of the web application is developed on the .NET platform, and the front end is developed using
Angular.
To use the application, users must register and authenticate, Because the application uses a paid
API (Application Programming Interface).
Therefore, users who are not authorized to the service cannot use the application. A fragment of
the application is given below in Figure 1, on which the user writes the address of the desired website
in the Web Page URL input and presses the Inspection button. Using the API service, the application
determines the relevant website search engine optimization metrics data, which will be added to the
decision matrix. The user of the application will similarly search all the websites from which he wants
to select the best one. (see Figure. 1)
Figure 1. Website search and analysis results
By clicking on the ranking button, the application will implement the algorithm and show the
ranked websites according to the ranking, which clearly shows the best website (Figure. 2).
Figure 2. Ranked list of sites
8. Conclusion
As a result of the research presented in the paper, an algorithm and a web application have been
developed, which realizes the mentioned algorithm. The developed algorithm ensures evaluation of
selected websites according to SEO metrics and their ranking. We have taken eight basic SEO metrics
as evaluation criteria for websites, which provide important information about the sites, but this does
not mean that the presence of eight criteria is necessary for the algorithm to work, therefore the
algorithm allows to increase or decrease the number of evaluation criteria. A web application is a
flexible tool for businesses to ease the website selection process and select the best site to display
information about their products or services.
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