An ex-employee leaked all 1,922 ranking factors for the 4th biggest search engine.
Since Yandex is a clone of Google, it is likely that Google uses the same ranking factors as Yandex.
The Yandex search engine and web portal are both owned by Yandex. Yandex provides internet search and other services such as maps, navigators, public transportation, taxis, weather, news, music, TV programs, translation, and online shopping. Cloud storage and email services are free.
Here are Yandex’s top 17 ranking factors
- Page Rank
- Page Rank Bonus
- Text Relevance Priority 1
- FI_LINK_RELEV_ALL_WORDS
- FI_LONG
- YaBar
- FI_ROOT
- FI_GEO
- SubqueryThMatch
- TRboost
- TrafgraphOutAll_share_d
- HasLR
- TRUnmapped
- AddTime
- QueryURLClicksPCTR
- Adv
- FI_TEXT_PAIR
1. Page Rank
Websites with more links pointing to them are considered more important and will show up higher in search results.
2. Page Rank Bonus
“PrBonus,” is a factor used to prioritize search results.
If you were to search for “best restaurants” the factor PrBonus would be used to give priority to webpages that have the keyword “best” and “restaurants” in it, and also have more links pointing to it.
3. Text Relevance Priority 1
It looks at whether all of the words in the query appear somewhere in the article, even better if in the same sentence.
E.g. If the query is “red apple” and the document contains the sentence “I love eating red apples”, TRp1 would have a value of 1.
4. FI_LINK_RELEV_ALL_WORDS
This relevance factor used to determine if all of the words in a query are present in a single link.
For example, if the query is “red shoes”, a webpage with a link that says “Buy red shoes here” would score high on this factor.
5. FI_LONG
This factor is based on how long the document is.
E.g. If you searched for “how to make a pizza” and one website had a short recipe while another website had a long recipe with pics & step-by-step instructions, the second website would have a higher score for this.
6. YaBar
This looks at how often people go to a certain website and how much they use it.
For example, if lots of people often go to a website about cars, YaBar would think that website is very important for people searching for cars.
7. FI_ROOT
If you have a website about dogs and you have a page about different breeds of dogs. That page will have a high “FI_ROOT” factor.
But if you have a page about cars on the same website, that page will have a low “FI_ROOT” factor because it is not related to dogs.
8. FI_GEO
This is a factor that checks if the user’s location and the website’s location are in the same country.
For example, if a user is searching from Russia and the website they are looking at is also from Russia, this factor would give a score of 1.
If not, it’ll get 0.
9. SubqueryThMatch
An example of this would be searching for “baseball” and the website being about “baseball” as well, so it would get a score of 1. If not, it would get a score of 0.
10. TRboost
This factor makes other factors stronger when the text is relevant but there aren’t many links.
Let’s say you search for a website about dogs and the website has a lot of information about dogs but not many links, this factor would make the website show up higher.
11. TrafgraphOutAll_share_d
E.g. If you were searching for information about dogs, the program might look at how often websites about dogs link to a particular webpage about dogs.
If many websites about dogs link to that webpage, it would be considered more relevant.
12. HasLR
This looks at relevancy based on referring domains.
For example, a website about dogs would have a high link relevance score if it has many links to other websites about dogs, but a low score if it has mostly links to websites about cats.
13. TRUnmapped
This is a factor that helps to measure how relevant a document is to a specific search query.
This is calculated by taking the Text Relevance and dividing it by the number of words in the search query & then adjusting it using a method called “remapTR”.
14. AddTime
This helps decide how old a webpage is. The older the webpage is, the higher the AddTime score will be.
It’s calculated by taking the time the webpage was added and putting it on a scale of 0 to 1, so that pages that are 3 or more years old will have a score of 1.
15. QueryURLClicksPCTR
If you search for “puppy” & one result goes to a website about puppies, and another goes to a website about kittens, the link that goes to the website about puppies will have a higher score because more people are clicking on it when they search for puppy.
16. Adv
This factor is called “Adv” and it is used to check if a website has advertising on it.
If a website has advertising, this factor will be set to “true”. If it doesn’t have any advertising, this factor will be set to “false”.
They didn’t specify whether this has an impact.
17. FI_TEXT_PAIR
This looks at the number of sentences in the document that contain words from the query
If you search for “big red apple” and a website’s text includes the phrases “big red apple” and “red apple”, that website would score higher than one that only includes one.
