Discover how to harness the potential of ChatGPT for advanced keyword research in SEO with our comprehensive guide.
There is an enormous wealth of information out there online, so finding what you’re searching for would be virtually impossible if there wasn’t some help available to make sorting it a simpler process.
The Google ranking system has been designed for this specific purpose. It sorts through countless web pages in its Search index so it can find results that are both useful and relevant in under a second, presenting those results in ways that allows searchers to find precisely what they’re looking for.
Google’s ranking system is composed of a set of algorithms. In order to find information that is most useful to the searcher, search algorithms consider numerous factors, from the words used in the initial search query, to relevance, page usability, source expertise, settings, and location.
The weight that is applied to every factor will vary depending on your query’s nature. As an example, if you’re asking a question about a current news topic, fresher, newer content will have a larger role to play in answering your query. On the other hand, if you’re asking for a dictionary definition of a word, freshness of content has less of a role to play.
In order to ensure search algorithms adhere to high quality and relevance standards, Google has put a very rigorous process in place involving live testing as well as countless external highly trained Search Quality Raters across the globe.
These professionals have strict guidelines to follow which define Google’s Search algorithm goals and which have been made available to the public so that anyone can see them.
Here are some of the most important factors which determine the results that will be returned for each query:
So that the most relevant results can be returned for a query, Google first needs to establish the information which you’re seeking, i.e. the intent lying behind the query. To gain an understanding of intent involves understanding language. This is a vital element of search. Google builds language models which aim to decipher the word strings that should be looked up in its page index.
The steps involved range from the fairly simple, such as interpreting a spelling mistake, right up to the more complex, such as understanding a query type by applying recent research about understanding natural language. Google has a synonym search which aids Search in knowing what the searcher means by establishing multiple words have an identical meaning.
Thanks to this capability, search can match queries like “how do I change my light bulbs?” with pages that describe ways of replacing light bulbs. This system has taken more than half a decade to develop but it has meant a significant improvement has been achieved in returning results in more than 30% of all searches in different languages.
Search algorithms aren’t only about synonyms. They’re also about trying to gain an understanding of the information category that a searcher is trying to find. Is the query a broad one or very specific? Has words like “pictures”, “opening hours”, or “review” been entered?
These could indicate a need for specific information in the searcher’s query. Has the query been written in Spanish, implying that answers in this language are required? Is the searcher trying to find a business nearby and so are they seeking local information?
One especially vital element of query categorisation involves Google’s analysis into whether the query is looking for new content. If the query involves trending keywords, Google’s freshness algorithms interpret this as an indicator that recent information will likely be of more use to the searcher than old pages. As an example, if you perform a search for “latest World Cup results”, “BP earnings”, or “premiership scores” you will be shown the most up-to-date details.
Once Google’s algorithm has understood a searcher’s query intent, it must find pages that are most relevant. SEO is very important for this. Google also implements anonymised and aggregated interaction data. This means that the page’s relevance is explored beyond just mentions of keywords.
The entire topic and content must have relevance to the query in order for it to be deemed as the most relevant result by the algorithms. Content must also be of the highest quality with authority, expertise and trustworthiness built in to be deemed relevant.
Google’s algorithm also aims to promote pages that are more usable over those that aren’t as user-friendly. Therefore, sites that appear and load correctly on all web browsers, which have compatibility with a range of device sizes and types, and which have a speedy loading time, even for those users who have a slower internet speed will be deemed as more relevant by Google.
This is a ranking factor that has a relationship with relevance but bears the searcher’s personal setting and the context in mind. As an example, if an American searcher wants to find football results, they’ll be shown NFL results.
However, when a British searcher looks for football results, they’ll be shown Premier League soccer results. Google’s algorithm is also able to identify preferences and patterns based on the user’s previous searches, providing results accordingly.
The Google algorithm has a dynamic nature, and it’s constantly being adjusted to make sure it’s useful at all times. Sometimes, it undergoes major core updates which have a significant impact on existing rankings.
This can lead to some sites getting a higher ranking while others drop down. This makes it hard for web developers and site owners to work out what they need to do to ensure a high ranking. However, when the above factors are taken into account, it’s likely your page will continue to rank well.
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