-First Segment-
Google RankBrain Algorithm: Transition from Static to Dynamic Algorithm
Google RankBrain software is a self-updating algorithm. Google employs it to understand and evaluate search queries so to generate the most relevant search results.
RankBrain algorithm enables the search engine to learn by itself then improve search results without human interference.
Before the emergence of RankBrain, humans would have to experiment by making manual changes in the algorithm. If that change produces better search results, the change will get implemented, else the previous algorithm would remain in place.
The design of the RankBrain algorithm allows it to automatically fine-tune itself. So RankBrain would first slightly reform the algorithm. That reform would cause a change to the ranks of different parameters for each keyword. Then it makes another change and reviews the search results. This process continues.
Now RankBrain would monitor the user-friendliness of the new search results. If it notices an improved user activity, then the change in the algorithm would take full effect. Otherwise, the previous algorithm will remain effective.
Besides RankBrain, Google engineers will also evaluate the new search results. So the continuous back and forth approach between humans and RankBrain helps Google produce a more people-friendly search result.
-Second Segment-
Working Procedure of Google RankBrain
RankBrain algorithm performs two major functions:
Let’s have a look at how they play out....
How RankBrain Decodes Search Phrases on Google
Before RankBrain, Google would look for an exact phrase match for the search keyword into its server. In this way, Google failed to identify any match for brand new keywords or entirely new search queries.
To overcome this hurdle RankBrain tries to understand all the possible meanings of each search phrase. Much like humans do. To do this, RankBrain strives to figure out a correlation between entirely new keywords and already known keywords.
Google also tries to understand user intent. To do this, it employs “Word2vec” technology that treats search phrases or keywords as concepts rather than just words or phrases.
Determining User Friendliness of Search Results
Now we realize that RankBrain adapts the algorithm on its own to new realities and employs innovative techniques at understanding keywords.
However, the bigger issue is how RankBrain would know if there are improvements in the search results?
RankBrain would closely monitor the user experience signals (known as UX signals) for the search results, especially the following:
So RankBrain would then present the user with search results that it deems most closely related to the keyword. If it observes a higher interaction from the user for the search result, RankBrain will boost ranking for the page.
If RankBrain observes a drop in user interaction, it will drop ranking for that page then fill the gap with the next page.
-Third Segment-
RankBrain Friendly Keyword Research
To adapt to the RankBrain algorithm, we have to change the traditional ways of keyword research. Here is the clue.
Exclude Long Tail Keywords
Earlier we tend to create many pages and optimize each page for a particular keyword. The old Google would then rank each page for the respective keyword.
We already know that Google looks at keywords as concepts and tries to understand the intent behind search queries. So, RankBrain generates identical search results for all keywords with similar meanings.
This process eliminates the need for separately optimizing each long-tail keyword. Instead, more effective is to optimize medium trail keywords.
It eliminates the need to separately optimize each long-tail keyword. Rather it is more productive to optimize medium trail keywords.
Medium tail keywords have more search volume than long-tail keywords but, this search volume is not impressively competitive like single keywords.
So, when a page is optimized around a medium tail keyword, RankBrain will rank the page for that keyword plus plenty of similar keywords.
-Fourth Segment-
Optimization of Titles to Gain Higher Clickthrough Rate (CTR)
Once a page has a proper rank, the next thing will be how to get more people to click on the title. Here are a few things to consider to improve CTR.
-Fifth Segment-
Optimization of Content for Better Bounce Rate and Dwell time
Once a title successfully boosts CTR, the next thing will be to improve the dwell time so that Google understands that the content is user-friendly.
Role of Dwell Time as a Ranking Signal
Google RankBrain uses dwell time as a vital signal to determine ranking for a page. If a user spends more time on a page, RankBrain upgrades its rank. If a user stays on a page for less time, RankBrain will degrade its ranking.
However, Google still relies on off-page signals (such as backlinks) also integrates machine processes that count on off-page signals.
Google is developing processes to factor in on-page issues such as the following:
Extensive analysis of Google search results indicates that there is a direct relation between page ranking and bounce rate.
Here Are Few Tips That Will Reduce Bounce Rate and Boost Dwell Time
-Sixth Segment-
Virtuous Strategies for RankBrain Optimization
The following are some prompt strategies that help to optimize a site for the RankBrain algorithm.
Brand awareness acts as a major CTR driver
Plug “Content Gaps” Using LSI keywords
LSI (Latent Semantic Indexing) keywords are phrases or words that are conceptually similar to the main subject of the content.
LSI keyword gives RankBrain the necessary context to properly understand the content of a page.
If the main subject of a page is algorithm the LSI keyword will be like the followings:
As the Google RankBrain algorithm frequently encounters these keywords in the content, it becomes confident that the page is about the algorithm.
Hopefully you have enjoyed this guide.
Try some of the tricks in your next article then see the result for yourself!
End note: Up to this time, Google has deployed many algorithms such as Google Panda, Google Penguin, and Google Hummingbird.
Related Reading