Top 5 Organic Search Ranking Signals
1. Domain Age and Rate of Linking
Google’s patent called “Document scoring based on document inception date” (patent number US8521749B2) states that Google will often used the date they first crawled a site as the “age” of the site.
The patent also states that Google looks at the number of links pointing to a site, and calculate the average rate of new links being generated. The more links over a period of time, the more likely the content is to rank highly.
For SEOs, it’s therefore important to have your domain registered early, with “empty” content, in order to be indexed by Google. This will register “site age” while no content is yet necessary to begin ranking. This patent also stresses the importance of effective link-building.
2. Use of Keywords
Matt Cutts, an American software engineer, wrote a letter for librarians detailing how Google crawled the web. He explained that when users search for particular words, in the newsletter dubbed as “keywords,” Google would find those words instrumental in determining the search results.
While this newsletter was sent out in the early 2000’s, the weight of Keywords carries on due it’s fundamental usage in Search Engine’s. Towards 2020 Google has shifted towards the use of surrounding text, LSI keywords, or relevant phrases to enhance search results. For example, searching “near me,” is a synonym for “nearby,” which is also relevant to “within 500m.” Each of these is primarily relevant to Local SEO.
3. Page Speed
Google’s patent “Using site speed in web search rankings” states that the site speed is determined by averaging the load time on a range of devices. This would mean that having a good Desktop load speed score, but a poor Mobile load speed score would not aggregate to a good rating overall.
A method of improving this would be through technical SEO. Technical SEO focuses on a variety of front-end, and back-end factors that influence how users, and Search Engines interact with your site. One subsection of technical SEO involves the optimization of web load speed overall, as to improve the ranking of a site.
4. Context Terms on a Page
Words have multiple associated “entities.” For example, the word “bank” could refer to a place where money is stored, the edge of a river, or the action of a plane. Each of these would be considered different “entities” with different “attributes.” Google patented “User-context-based search engine” (US9449105B1), with the intent of using surrounding text to identify the meaning behind specific entities.
This patent was filed and deployed in 2006, and much more recently Google has developed this further by creating Augmented Search Queries. A 2018/2019 deployment which involves the manipulation of user search queries, to provide “hybrid” search results.
5. Language Models using Ngram’s
The use of language on a website can be analyzed through a Google tool called Ngram. Ngram’s are used to create language models of a site, which is then analyzed to determine a “quality score” for the site.
Ngram’s belong to the fields of “computational linguistics” and probability. An ngram is a sequence of n terms from a given text, in which n is associated to something like syllables, letters, words, or base pairs. In Google’s algorithms, it appears to be word driven in a bigram/trigram system. This helps in the construction of language models that are flexible and easily scalable.
The closer the score is to “high-quality” when compared to a training set that Google provides it’s algorithm, the better the site may rank. This was patented as “Predicting site quality” by Google in 2017.
