It shouldn't be forgotten that Google integrates over 200 variables in its algorithm in order to sort
the results as they appear in the search web pages.
It is the duty of every good NCO specialist to consider and work on these factors to give just a few
examples.
I mentioned the loading speed the relevance of the title tag the age of the domain.
The quality of incoming back links the extension of the domain.
The social signals the web page content length and the performance of click through rate.
Fortunately not all FCO factors have equal weight but there are some that matter more than others.
And this is why FCO interventions focus on just a few dozen variables.
We can say that Google works on three fundamental principles inspired by the 200 factors in order to
decide what should be shown first.
Second and so on trust.
How can the site be trusted if a page has good content with the links from other quality sites.
It will obviously be easier to rank authority in the past.
The authority of a website was measured by page rank which also took into account the popularity in
terms of back links.
But today there are several factors that make a site authoritative and other metrics were born such
as the Moores domain authority relevance.
It is essential to show users the most relevant content in order to answer their questions.
And this is the reason why we talk about relevance.
Having back links from web pages themed with the same topic certainly contributes in a positive manner.
Personally I love to focus on the last one relevance because in my experience interventions of this
type require less time than the other to authority and trust and they are more feasible even when in
particularly competitive markets.
What has changed with rank brain if you are a beginner I anticipate immediately that this section will
be a little bit tricky for you but I suggest you try to deal with it.
In short Google rank brain is a constantly updated and improved machine learning algorithm used by Google
since 2016 in order to sort the search results.
Basically in the past Google algorithm was constantly optimized by programmers and human personnel through
verification feedback and approval.
Now with the advent of rank brains artificial intelligence the algorithm optimizes itself in complete
autonomy evaluating the public behavior based on the search results and adjusting the rules accordingly.
Rank brain has two main objectives.
Understanding the keywords and measuring how people interact with the results thus interpreting their
satisfaction.
Going straight to the core of things nowadays Google is able to interpret the search intent including
for example that where to sleep well in Milan has the same meaning as where you can sleep well in Milan.
In the past we often use the so-called keyword cannibalization which means that we could create two
distinct pages each optimized for a keyword.
Today it is preferable to work on a single medium tail key word.
For example sleeping in Milan rather than on multiple long tail keywords for example where you sleep
well in Milan thus allowing for other keywords which present the same search intent to appear to we
have just seen that doing SEO at the time of rank brain actually forces us not to forget about the user
experience and the user behavior because the algorithm is constantly influenced by these two from a
practical point of view.
It is important to have a good click through rate CPR on Google search pages and an adequate bounce
rate because they are strong indicators regarding the user's interest in our web page just to give you
an idea.
You could have a good click through rate C TR focusing on optimizing the title tag with a bit of copywriting
while for the bounce rate you need to make sure you have relevant content in terms of quality instead
in terms of graphics.
It may be worthwhile to include internal links to other resources on your Web site we'll see everything
in detail in the next chapters so you don't need to worry if the section seem too technical I'd like
to see myself as a curious person because I always see some learning potential everywhere.
I think it is useful but also interesting to know about the history of search engines in order to understand
the evolution that we have seen in the last 30 years.
As we speak of search engines nowadays we think of Google almost exclusively but we must remember that
there are several others such as being Yahoo.
And so on which certainly convey just a small traffic fraction compared to big G.
But they still fall within the definition of a search engine.
On a technical level a search engine has some fundamental characteristics crawler.
The system automatically browses the worldwide web by visiting a myriad of web pages and Web sites in
order to find information and content indexing the web pages returned by the search results are being
analyzed based on their titles and other meta data in order to be subsequently organized better for
the purpose of being quickly consulted in the future information retrieval.
A user enters a keyword in the search form and the engine returns the results ordered according to a
specific algorithm.
In 1990 the first search engine was Archie query form which dealt with finding FTB Web sites in order
to create an index of downloadable files.
In 1994 the Infoseek project seemed to be a real revolution as it allowed webmasters to send a page
directly to the index.
It was born the same year as the famous Yahoo search in 1996.
Besides the Alta Vista search engine the back rub appeared thanks to the work of Larry Page and Sergei
Brin.
It was a sort of forerunner to Google as it already used bank links in its own algorithm finally.
In 1998 the M.S. Search and Google search engines were launched.
The latter released its first significant update called Boston in 2003 while in 2005 there was already
the advent of no follow links to fight the so-called spammy blogs.
Various Google updates followed afterwards such as panda Penguin and hummingbird.
In order to fight the increasing spam in 2009 Amazon's search undertook a rebranding operation that
gave birth to today's Bing.
While in the following year Google Instant was born with the aim of providing results in real time.
Already while typing the keyword in 2000 and eleven schema dot org was launched which offered structured
data to search engines.
It is still used today for previews of cooking Web pages and product reviews through the famous rich
snippets as an example.
In 2015 rank brain was released an update that included the machine learning within the results ranking
process in 2017.
Google began to punish the websites which contained pop ups and similar that damaged browsing.
Subsequently the Fred update was also released with the aim of penalizing those sites that favored monetization
over the user experience.
Finally we cannot forget the widespread dissemination of vocal searches in 2019 thanks to some devices
such as Google Home and Amazon Echo which have become more and more mass products.