How SEO Works - Breaking Down Google Algorithm

Though there is no one who can predict how Google Algorithm works but Moz released an infographic based on the opinions of SEO experts. Though it was taken some years back, it laid down the foundation to understand Google Algorithm.

We will be going through it in detail and look at it from the current perspective in this post.

Understanding Ranking Factors In Google Algorithm

The final ranking of any page or website is derived from the following features. This chart basically conveys how much each SEO activity contributes to the page getting listed on Top Page in Google

After reading this post, you will also get an overall idea of all SEO activities that you will need to perform and how much each of them matters

1. Domain-Level Link Authority Features

The features discussed under this are very similar to those used to calculate the Domain Authority Some of the features include -
  • Quality of links to the domain
  • Number of times the domain is linked
The experts back then believed that the Domain-Level link authority features contributed a whooping 21% in deciding the final rank. The scenario is not different today. For any search that you perform the top spots are held by domains having high Domain Authority.

2. Page-Level Link Features

These include external links to your pages. The quality of links, the number of links, the authority and quality of link sources, anchor text distribution and other Page-level link sharing metrics.

These contributed 19% in deciding the rank back then and then the scenario is kind of similar today. 

So, overall you can see the importance of link building activities and why should you spend some time on it. 

The Domain Authority and Page Authority combined contributes to around 40% 

3. Page-Level Keywords and Content Features

Apart from the basic factors like  -

  • Total Raw Keyword Usage: How many times the keyword is used, the inclusion of keyword in title tags, URL and search description etc
This also includes advanced machine learning algorithm features that Google uses to scale and track content. Some of the advanced models used are -

  • Topic Modeling Algorithms
  • Semantic Modeling Algorithms
So, these machine learning algorithms basically add another dimension in your SEO efforts. It is believed to differentiate between fluff and useful content.

These are believed to contribute around 15% to the ranking. Nothing much seems to have changed over the years apart from the fact the algorithms have gotten more complex over years

4. Page-Level Keyword Agnostic Features

These include page-level metrics like -
  • Length of the content
  • How fast a page loads
  • Readability of the content
  • Uniqueness
  • To what level Google might be analyzing the content and images on your Page
In the current scenario, the relevancy of these factors is decreasing as compared to when the opinion poll was conducted.

5. Domain-Level Brand Features

This includes activities related to branding -
  • Is the domain name associated with a brand name? (Eg.
  • Does the brand get a lot of mention
  • Does the domain name itself gets mentioned a lot (a lot of people writing about it)

This is something that is on the rise. With Google giving a lot of preference to brands if you are a marketer then you should start working on branding activities. The latest Google Algorithm clearly mentions the additional support that it is looking to provide brands.

6. User Usage and Traffic Query Data

This revolves around how much organic traffic your website is getting and how people are using your website

The following questions will give you an idea about it
  • Are a lot of people visiting your website? 
  • Are a lot of people searching for your domain name?
  • What is the status of engagement metrics like bounce rate, average time spent on website etc
The experts believed that these metrics contributed around 8% to the ranking. In the current scenario, the contribution is not so much different. It rose some time back, but from a calculated guess I place it around 10%

7. Social Metrics

This includes all your social shares on Facebook, Twitter, Instagram, Pinterest. Kindly note this does not include links shared on Private Facebook Groups. 

It is more about the links shared by other people on their profile or with their friends.

This contributes to only about 7% of the ranking in general. It is often assumed that the search engines find it slightly difficult to read the social media indexes as compared to other websites and hence it was never a major contributor to rankings

8. Domain-Level Keyword Usage

This pertains to having the niche related keyword in the domain name. For example, if you are a mobile case seller, then it was believed that you should have the words mobile-case in your domain name, something like

But currently, this is a ranking metric that has ever been on the decline. You can have a very different domain name and there is not much need to have the main keyword in the domain URL.

At the time of the survey, it contributed around 7%, but in the current scenario, I think it would be around 4-5%.

9. Domain-Level Keyword Agnostic Features

This includes the following in general -

  • Length of the domain name
  • Extension of the domain name (.com, .org, .in etc)
  • Http response time 
The contribution towards the ranking is similar to what it was.

Key Takeaways

Though the above factors are only indicators of what may be affecting the rankings, there are some major learnings that we get from these-

  • There is no single dominant factor
  • Backlinks are still a big deal at both Domain and Page Levels
  • If you are not building a brand on the web, it is going to hurt your SEO
  • Social links still perceive to have a very minor effect on SEO
  • Keyword-based domain names no longer contribute to ranking

Hope you guys might have picked up a cue from this article. You can also start working on these features on your own website.

Feel free to reach out to me in the comments section

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