Link Relevance Score (LRS)

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What is LRS

LRS, or Link Relevance Score, is a metric that summarizes the relevance analysis of web pages, in a clear and manageable way. LRS will correspond to a link authority metric.

The idea behind the LRS is based on the overall idea of being able to quantify the relevance of a link (link opportunity) between two pages.

How is the LRS structured?

The Link Relevance Score is divided into four validation stages, which ensure that a relevant basis can be created for two pages and at the same time ensure that the two pages are not identical.

Validation stages:

Domain to domain

Based on the entire domain, it is analyzed, among other things, which main topics the site is centralized around.

This is done to ensure the overall understanding of the purpose of the domain, as there may be pages where the individual pages may have its own purposes that do not necessarily address the overall purpose of the domain, which we will get into later.

Based on how specific the text is on the specific topics, each topic will be assigned a numeric value, which will be taken into account when the Link Relevance Score is calculated.

This value is then compared with the values of other relevant domains, to then determine a score based on the two domains’ relevance to each other.

Page to page

In the same way as the overall topic of the domain is analyzed, the individual pages’ topics are also analyzed as well as the relationship between the pages, to ensure that the two linking pages are included in the same topic/niche.

The quantification of the pages’ topics and the comparison of the pages are assessed in the same way as the domain to domain process.

Page to domain

At this stage, it is assessed to what extent the two linked pages have a relevance to the overall topic of each other’s domains.

This is typically where link opportunities are considered to be of high or low relevance. Pages that do not have high relevancy with the linking site’s domain can often not score a particularly high Link Relevance Score. This is based on the fact that two pages can be linked well, even though there is no connection between page to a domain, but this often gives a low overall weighting.

Link to page

The final validation stage addresses whether the link text/anchor text has an overall relevance between the two linking pages.

This stage has different branches.

Two pages that do not yet link to each other:

Here, the possibility of linking is assessed, where the textual content is taken into account. There must be a connection in the text that is linked (the anchor text) between the two pages.

It is possible that it can be both a text that is already on the page or a textual summary of a sentence or paragraph that will be used to calculate the relevance of the link text. 

Pages that link already:

For pages that already link to each other, the link text will be analyzed and will be taken into account in relation to the other validation stages, to assess whether there is a relevance between the link text and the page being linked to.

Without the “link to page” context, it is not possible to link between the pages as it is thus not possible to maintain a satisfactory relevance relationship between two pages.

Which data is used to calculate the LRS?

Different types of data are used to calculate the Link Relevance Score.

Mainly the results from the text analysis are used, but other SEO-related factors are also taken into account when the system has to evaluate the possibility of two pages links to one another.

As described in the section on how LRS is structured, text data from the individual pages and the combined text analysis of the domain is calculated.

Some of the data points that are taken into account in the calculation:

The main topic/topics for the whole domain.

The topic/topics of the individual pages.

Paragraphs, sentences and words topics for the whole page.

Semantic connection and relevance between paragraphs and words.

SEO related weighting factors, such as title tag, headings, and text/word placement on the page.

The page importance in relation to the whole site.

Mathematical scaling factors, such as damping factor and weighted averages.

Which use cases can LRS be used for

One of the disadvantages that typically accompanies qualitative data is that it is difficult to compare with other data and often requires a subjective interpretation.

Link Relevance Score, however, offers many advantages as it manages to quantify, qualitative data and present it in a manageable way, which should help marketers to get even better results at their job of link building.

LRS can be used in many ways and you may find that you can use it in your very own way with your case. These examples below come from use cases, which we often experience LRS being used for:

Review existing link profile based on relevance.

If you already have a number of backlinks and want to minimize the risk of being hit by an algorithmic penalty from the search engines, you can advantageously review your own website’s link profile and look for backlinks with low LRS.

Easily review and sort link options.

When you use the Tabtimize’s Backlink Engine function or other tools that can display link opportunities, then you will be able to easily sort these, according to their LRS, and thus their relevance to your site.

If you use Tabtimize’s Backlink Engine function, then you can also specify your search for relevant link options with other sorting options, such as specific words, topics, SERP position, word count, and much more.

Assess competitors’ relevance profile.

A good way to make sure you have a more relevant link profile than your competitors is to analyze your competitors’ link relevance profile.

Do they have a more relevant profile than you? – What types of backlinks give them the highest relevance and can you replicate it or even surpass it?

Assess the potential of possible new upcoming links based on relevance.

Backlinks can come from many different sources. You may have worked on PR, social media, or anything else that can give you some good organic backlinks.

The question then is: Do these links benefit your link relevance profile and do they come from relevant sources?

You can get the answer to this before you choose to create relationships through, for example, PR and social media or help you select the most relevant to your case

Use LRS as a KPI and increase your page’s own relevance profile.

There are already many KPIs that marketers need to be aware of. However, it will really make sense to keep an eye on your website’s LRS, as an indicator of a good link profile.

Evaluate upcoming links’ own relevance profile.

This task can be quite a comprehensive task, but it would give you great gains in the long run.

If you make sure that the pages you get links from, themselves consist of a relevant link profile, it will give you two huge benefits:

1. If the page from which you need a link itself has a relevant link profile, then the probability that it will receive relevant traffic from its own backlinks is high and thus it increases the possibility that you will benefit from the relevant traffic, channeling relevant traffic to your site.

2. The link you get comes from a source that itself has a relevant link profile, which tells the search engines that this is a healthy link that is highly likely to benefit both sides and should be given a high weighting.

Analyze and ensure relevance from external link providers.

Link building is a time-consuming process and many may find themselves forced to outsource that part of their SEO.

However, you can advantageously ensure that the content that is written also benefits your website. Also, you can use LRS to assess which websites you want the content to be linked from, as the domain that will be linked to your site might have a non-relevant overall topic that possibly could hurt the overall link relevance profile.

You can also use LRS as a KPI for your link providers and make sure they maintain a high quality in their service.

Julian Singh

Julian is the founder of Tabtimize. He has more than 7 years of SEO experience and loves helping companies use AI to raise their SEO potential.

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