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What is Google Search and How does it work?

Search Engine algorithms are based on a simple premise: searchers want an answer to their queries. For any search, there are hundreds or thousands of sites that offer a potential link or insight related to the query. As a result, search engines need to accomplish three goals:

  • Disqualify all the sites that aren’t relevant.
  • Return a list of sites that are relevant.
  • Rank and prioritize those sites in order of importance to identify which sites are the most relevant.

Just when you think you’ve grasped the specific details of Google’s algorithm, it’s important to note that changes occur all the time. By understanding the historical trends in what’s changed and staying on top of how things are evolving, website owners stand the best chance of developing and implementing strategies that lead to great long-term rankings.

Navigating Google’s current landscape requires not only a general understanding of search engine algorithms and how they operate but specifics of recent updates. In the last few years, Google has implemented a number of changes that have hit site owners particularly hard. These have focused on three key areas: content, usability, the quality of links, and the importance of mobile and how we search. Here’s a closer look at each of these updates and what you need to know to be up to speed.  Google now uses over 200 factors in ranking your website.



New Google SEO Factors (200) – We broke them down in their corresponding Categories: 

Google Algorithm Updates
Google Domain Authority Ranking Factors
Google PageRank Factors
Google Site Ranking Factors
Google Social Media Ranking Factors
Google Domain Ranking Factors
Google Ranking Factors for User Interaction
Google Special Algorithm Factors
Google On-Site WebSpam Factors
Google Off-Site WebSpam Factors
Google Brand Ranking Factors

This Chart illustrates the breakdown of the New Google Algorithm Factors according to 72 of the leading SEO experts surveyed at the most recent of Moz’s biennial SEO meeting.


(Click to Enlarge & Back to Escape)



Trust/Authority of the Host Domain  23.87%

Domain Authority is a score (on a 100-point scale) predicts how well a website will rank on search engines. Use Domain Authority when comparing one site to another or tracking the “strength” of your website over time.

Over 40 signals are included in this calculation.  Your website’s Domain Authority score will often fluctuate.  For this reason, it’s best to use Domain Authority as a competitive metric against other sites as opposed to a historic measure of your internal SEO efforts.

Note – It’s easier to grow your score from 20 to 30 than it would be to grow from 70 to 80.

Link Popularity of the Specific Page  22.33%

Link popularity is a term used to describe the amount of links to a webpage from the rest of the internet. If popularity is high on a particular page or website and many people are linking to your page, then it must contain content and information that people find useful.

Anchor Text of External Links to the Page  20.26%

Anchor text is the visible, clickable characters and words that hyperlinks to another location on the web. In the phrase

Ex. https://www.mollify.biz> Digital Marketing Organization

Digital Marketing Organization is the Anchor Text

Search engines use this anchor text to help determine the subject matter of the linked page. In the example above, the Anchor Text will tell the search engine that when users search for Digital Marketing, Mollify is a relevant site for that search.

When breadcrumb navigation is enabled on a website, it creates anchor text links on every page of the website which link back to the homepage of the site.

On-Page Keywords Usage

Keyword placement is much more important than frequency.  Posting “Online Marketing” once in the tittle tag on your website and once in the header has much more significance than stuffing the word into the body copy 10 times.

Google breaks your site down into key areas, with meta information and headers taking top priority, body copy taking secondary priority, and sidebars and footers taking the last priority.

When Google now scans your site for information, it no longer pulls out the keyword phrases it thinks are relevant and pairs them to user queries. Instead, Google interprets the data on your website, and begins to form its own conclusions about your website and your business.

Hosting Data

Your hosting provider can affect your Search Engine Optimization: performance (speed), availability (up-time), security and SEO awareness.

Clickthrough Rate and Traffic
  (CTR)  6.29%

Clickthrough Rate is a measured by dividing the number of times a link appears on a search engine results page by the number of times it is actually clicked on by a visitor. For example, if a link appears one hundred times, referred to as 100 hundred impressions, and it is clicked on twenty times, the click-through rate of that particular link would be twenty percent.

The CTR is calculated by as follows: (No. of clicks/No. of Impressions) x 100.
20 Clicks/100 Impressions = .20 x 100 = 20% Clickthrough Rate

The CTR shows the total percentage of people clicking on your results on the Search Engine Results Page (SERP).

Properly optimizing your description tags will increase your clickthrough rate for organic searches.  Descriptions that list the target keywords or keyword phrases, as well as descriptions that are well written and concise can draw a visitors to click on that particular link more frequently.

Learning the average CTR for different positions in the organic listing helps you understand where most of the traffic goes.  It’s of vital importance to rank 1st – 3rd or at the very least, first page for your main key terms.

Social Graph Matrics

What are they looking at?

Google seems to want to look at what people are posting on social channels including text, links, images, and videos. They are also looking for connections between users. Some examples given include;

  • explicit acquaintance relationship (e.g., designation as friends, colleagues, fans, blog feed followers, etc.),
  • an implicit acquaintance relationship (e.g., friends in common, messages sent between users, viewing another user’s profile page, etc.),
  • a common group membership (e.g., membership in a group related to a particular interest, membership in a group related to a particular geographic area, etc.),
  • participation in a common activity (e.g., users posting messages to the same forum, users playing an online game together, etc.), etc.

When trying to establish the relationship of links of and between users, they might look at;

  • Users that share a link may be likely to have common interests and may be likely to post content to their profile pages related to similar topics.
  • Links for a user with a profile page containing content known to pertain to a particular subject of interest can indicate that the profile pages of other linked-to users are likely to also contain content that pertains to the particular subject of interest.
  • Links among users of a social network can be used to propagate classifications (e.g., advertisement-related content, illegal content, inappropriate content for minors, etc.) for content that has already been identified as pertaining to a particular subject of interest to other content for which a classification is unknown.

When establishing connections they may do this on a common set of interests. The more common content shared between ‘friends’ on a network, the tighter the implicit relationship can be considered. This can then be used for classification of the users. Keep in mind that even when Google does ‘personalization‘, it isn’t on a user-by-user basis, but actually on a set of users classified to be related topically (by searching activities). This seems to be a large part of the approach when considering social elements as well.

They discuss in some of the patents the differences between explicit and implicit connections;

  • Explicit; designation as friends, colleagues, fans, blog feed followers, etc.
  • Implicit; friends in common, messages sent between users, viewing another user’s profile page, etc.
  • Common groups; membership in a group related to a particular interest, membership in a group related to a particular geographic area, etc.
  • Common activities; e.g., users posting messages to the same forum, users playing an online game together, etc.