Post by sumiseo558899 on Nov 7, 2024 2:22:31 GMT -5
"Analyze your competitors and do better" is a well-known SEO principle. Studying similar sites of the same subject allows you to analyze trends in the niche, identify features and evaluate the potential of the project.
In SEO, competitor analysis in search engine results is widely used. At the beginning of promotion, it helps to select the most successful of comparable competitors in a basic, general way and assess the traffic potential, and later – to analyze both individual landing pages and general project elements in detail, by cluster.
In the first case, general parameters of content writing service
competing projects are collected: the age of the site, the number of external links, the range (number of pages) and its presentation (listings, tables, landing structure pages), etc.
In the second, common elements are sought among the most successful pages of competitors and the possibility and necessity of placing these elements on the pages of the promoted project is considered.
The specialist examines individual correlations – connections where the impact of individual factors is manifested only as a tendency (on average) during mass observation of actual data – and their strength. Based on these connections, hypotheses are built, which are subsequently tested and implemented on the site.
An example of conducting an analysis of landing pages by a cluster of search queries
We take a ready-made semantic cluster, for example: Cockroach extermination
Getting rid of Yandex services (they do not fit the site format and page format), we get a list of the most successful competitors in this cluster. The numbers next to the URL are the number of cluster queries for which this URL is present in the Yandex TOP
You can evaluate any group of factors: cross-cutting elements, detailed on-page optimization, links, approach to forming meta tags. You can also evaluate commercial factors in the context of the entire site: the presence of pages that are mandatory in the subject, for example, Guarantees, Certificates and licenses, Employees, Examples of work, etc.
Let's look at an example of on-page optimization of landing pages:
news
The number of blocks and their composition will depend on the subject of the site.
From the table above, you can draw a conclusion about the priority of the presence of certain page elements and arrange possible edits in order of importance:
The Q&A section was ranked higher than the Our Clients section due to the ability to include LSI phrases (topic-setting phrases) in the text of this section, while the Our Clients section often only contains images (company logos).
This example shows the main blocks without going into detail. A detailed examination could focus on issues such as:
composition of the price table, availability of prices not only for apartments, but also for cottages;
availability of not only text but also video reviews;
the ability to enlarge certificates by clicking (lightbox);
the presence of a real, atypical USP in the benefits block;
etc.
Disclaimer: the examples above are intentionally based on a free service. In reality, it doesn't matter which specific service you use. The main thing is to understand the principles of operation and the scheme for generating the final results.
Both types of analysis are applicable when developing a new website:
General analysis is applicable to determine the structure of the site and the potential of the project.
A detailed analysis of clusters also helps at the MVP design stage to create prototypes of landing pages, identify common, cross-cutting blocks and the necessary commercial pages of the site.
However, like any statistical evaluation method, such analysis has its own characteristics that need to be taken into account in order to avoid “blindly copying all the solutions that competitors have in the TOP.”
Limitations of Conducting Correlation Competitive Analysis
Correlation and causation
The apparent simplicity of correlation analysis encourages one to make a false intuitive conclusion about the presence of a cause-and-effect relationship between the factors under consideration and the site’s position in search results.
In fact, a correlation may be present, but a relationship may be absent.
Also, the correlation of two quantities may indicate the presence of a common cause for them, although the quantities themselves are not interconnected.
Example: most of the competitors in the TOP may have the main key in the domain, but the success of these sites in SEO promotion may well be related to the age of these sites.
Simple logic: in competitive topics, most domains with direct inclusion of the main key have long been sold out, therefore, the age of these domains will be impressive and can have a strong impact on the presence in the TOP, and the presence of the keyword itself is just a "nice bonus". At the same time, in less competitive topics, the opposite picture can be observed: the presence of keywords in the domain will play a greater role than the age of the domain.
Weak correlation coefficients, negative correlation, presence of correlations with differences in intent
The presence of a weak correlation with the presence in the TOP-10 (if we look not only at the TOP-10, but consider the factor within the TOP-50) may indicate that, say, in the TOP-30 the factor is already a generally accepted practice. But this does not at all indicate the optionality or non-priority of the development of this factor.
The presence of a negative correlation , on the contrary, may indicate the "conservatism" of the topic, indicating that a factor that has long been worked out in most topics has not yet been widely implemented here. This, in turn, also does not indicate a low priority for the development of this factor.
The difference in intents can greatly limit the standard calculation of the correlation coefficient. If we take a query with an implicit intent, where 50% of the TOP will be informational, and 50% commercial - this is not a reason to consider the presence of a "buy in 1 click" button with a positive coefficient of 0.5. Here we will have to either count within 5 commercial competitors, or add commercial competitors to 10 pieces from the second page of the search results.
How to live on? Experiment!
Despite the previous statement and all the limitations described in the article, correlation analysis is an important tool in the work of an SEO specialist.
In SEO, competitor analysis in search engine results is widely used. At the beginning of promotion, it helps to select the most successful of comparable competitors in a basic, general way and assess the traffic potential, and later – to analyze both individual landing pages and general project elements in detail, by cluster.
In the first case, general parameters of content writing service
competing projects are collected: the age of the site, the number of external links, the range (number of pages) and its presentation (listings, tables, landing structure pages), etc.
In the second, common elements are sought among the most successful pages of competitors and the possibility and necessity of placing these elements on the pages of the promoted project is considered.
The specialist examines individual correlations – connections where the impact of individual factors is manifested only as a tendency (on average) during mass observation of actual data – and their strength. Based on these connections, hypotheses are built, which are subsequently tested and implemented on the site.
An example of conducting an analysis of landing pages by a cluster of search queries
We take a ready-made semantic cluster, for example: Cockroach extermination
Getting rid of Yandex services (they do not fit the site format and page format), we get a list of the most successful competitors in this cluster. The numbers next to the URL are the number of cluster queries for which this URL is present in the Yandex TOP
You can evaluate any group of factors: cross-cutting elements, detailed on-page optimization, links, approach to forming meta tags. You can also evaluate commercial factors in the context of the entire site: the presence of pages that are mandatory in the subject, for example, Guarantees, Certificates and licenses, Employees, Examples of work, etc.
Let's look at an example of on-page optimization of landing pages:
news
The number of blocks and their composition will depend on the subject of the site.
From the table above, you can draw a conclusion about the priority of the presence of certain page elements and arrange possible edits in order of importance:
The Q&A section was ranked higher than the Our Clients section due to the ability to include LSI phrases (topic-setting phrases) in the text of this section, while the Our Clients section often only contains images (company logos).
This example shows the main blocks without going into detail. A detailed examination could focus on issues such as:
composition of the price table, availability of prices not only for apartments, but also for cottages;
availability of not only text but also video reviews;
the ability to enlarge certificates by clicking (lightbox);
the presence of a real, atypical USP in the benefits block;
etc.
Disclaimer: the examples above are intentionally based on a free service. In reality, it doesn't matter which specific service you use. The main thing is to understand the principles of operation and the scheme for generating the final results.
Both types of analysis are applicable when developing a new website:
General analysis is applicable to determine the structure of the site and the potential of the project.
A detailed analysis of clusters also helps at the MVP design stage to create prototypes of landing pages, identify common, cross-cutting blocks and the necessary commercial pages of the site.
However, like any statistical evaluation method, such analysis has its own characteristics that need to be taken into account in order to avoid “blindly copying all the solutions that competitors have in the TOP.”
Limitations of Conducting Correlation Competitive Analysis
Correlation and causation
The apparent simplicity of correlation analysis encourages one to make a false intuitive conclusion about the presence of a cause-and-effect relationship between the factors under consideration and the site’s position in search results.
In fact, a correlation may be present, but a relationship may be absent.
Also, the correlation of two quantities may indicate the presence of a common cause for them, although the quantities themselves are not interconnected.
Example: most of the competitors in the TOP may have the main key in the domain, but the success of these sites in SEO promotion may well be related to the age of these sites.
Simple logic: in competitive topics, most domains with direct inclusion of the main key have long been sold out, therefore, the age of these domains will be impressive and can have a strong impact on the presence in the TOP, and the presence of the keyword itself is just a "nice bonus". At the same time, in less competitive topics, the opposite picture can be observed: the presence of keywords in the domain will play a greater role than the age of the domain.
Weak correlation coefficients, negative correlation, presence of correlations with differences in intent
The presence of a weak correlation with the presence in the TOP-10 (if we look not only at the TOP-10, but consider the factor within the TOP-50) may indicate that, say, in the TOP-30 the factor is already a generally accepted practice. But this does not at all indicate the optionality or non-priority of the development of this factor.
The presence of a negative correlation , on the contrary, may indicate the "conservatism" of the topic, indicating that a factor that has long been worked out in most topics has not yet been widely implemented here. This, in turn, also does not indicate a low priority for the development of this factor.
The difference in intents can greatly limit the standard calculation of the correlation coefficient. If we take a query with an implicit intent, where 50% of the TOP will be informational, and 50% commercial - this is not a reason to consider the presence of a "buy in 1 click" button with a positive coefficient of 0.5. Here we will have to either count within 5 commercial competitors, or add commercial competitors to 10 pieces from the second page of the search results.
How to live on? Experiment!
Despite the previous statement and all the limitations described in the article, correlation analysis is an important tool in the work of an SEO specialist.