With the amount of information available on the web, finding what you need would be nearly impossible without some help sorting through it. Google ranking systems are designed to do just that: sort through hundreds of billions of webpages in our Search index to find the most relevant, useful results in a fraction of a second, and present them in a way that helps you find what you’re looking for.
These ranking systems are made up of not one, but a whole series of algorithms. To give you the most useful information, Search algorithms look at many factors, including the words of your query, relevance and usability of pages, expertise of sources, and your location and settings. The weight applied to each factor varies depending on the nature of your query—for example, the freshness of the content plays a bigger role in answering queries about current news topics than it does about dictionary definitions.
To help ensure Search algorithms meet high standards of relevance and quality, we have a rigorous process that involves both live tests and thousands of trained external Search Quality Raters from around the world. These Quality Raters follow strict guidelines that define our goals for Search algorithms and are publicly available for anyone to see.
To return relevant results for your query, we first need to establish what information you’re looking forーthe intent behind your query. Understanding intent is fundamentally about understanding language, and is a critical aspect of Search. We build language models to try to decipher what strings of words we should look up in the index.
This involves steps as seemingly simple as interpreting spelling mistakes, and extends to trying to understand the type of query you’ve entered by applying some of the latest research on natural language understanding. For example, our synonym system helps Search know what you mean by establishing that multiple words mean the same thing. This capability allows Search to match the query “How to change a lightbulb” with pages describing how to replace a lightbulb. This system took over five years to develop and significantly improves results in over 30% of searches across languages.
Beyond synonyms, Search algorithms also try to understand what category of information you are looking for. Is it a very specific search or a broad query? Are there words such as “review” or “pictures” or “opening hours” that indicate a specific information need behind the search? Is the query written in French, suggesting that you want answers in that language? Or are you searching for a nearby business and want local info?
A particularly important dimension of this query categorization is our analysis of whether your query is seeking out fresh content. If you search for trending keywords, our freshness algorithms will interpret that as a signal that up-to-date information might be more useful than older pages. This means that when you’re searching for the latest “NFL scores”, “dancing with the stars” results or “exxon earnings”, you’ll see the latest information.
Next, algorithms analyze the content of webpages to assess whether the page contains information that might be relevant to what you are looking for.
The most basic signal that information is relevant is when a webpage contains the same keywords as your search query. If those keywords appear on the page, or if they appear in the headings or body of the text, the information is more likely to be relevant. Beyond simple keyword matching, we use aggregated and anonymized interaction data to assess whether search results are relevant to queries. We transform that data into signals that help our machine-learned systems better estimate relevance.
These relevance signals help Search algorithms assess whether a webpage contains an answer to your search query, rather than just repeating the same question. Just think: when you search for “dogs”, you likely don’t want a page with the word “dogs” on it hundreds of times. With that in mind, algorithms assess if a page contains other relevant content beyond the keyword “dogs” — such as pictures of dogs, videos, or even a list of breeds.
It’s important to note that, while our systems do look for these kind of quantifiable signals to assess relevance, they are not designed to analyze subjective concepts such as the viewpoint or political leaning of a page’s content.
Beyond matching the words in your query with relevant documents on the web, Search algorithms also aim to prioritize the most reliable sources available. To do this, our systems are designed to identify signals that can help determine which pages demonstrate expertise, authoritativeness, and trustworthiness on a given topic.
We look for sites that many users seem to value for similar queries. For example, if other prominent websites link to the page (what is known as PageRank), that has proven to be a good sign that the information is well trusted. Aggregated feedback from our Search quality evaluation process is used to further refine how our systems discern the quality of information.
Spam algorithms play an important role in establishing whether a page is low-quality and help Search ensure that sites don’t rise in search results through deceptive or manipulative behavior. Google’s webmaster guidelines outline the techniques that characterize such low-quality spam sites, including buying links that pass PageRank or sneaking invisible text onto the page.
Content on the web and the broader information ecosystem is constantly changing, and we continuously measure and assess the quality of our systems to ensure that we’re achieving the right balance of information relevance and authoritativeness to maintain your trust in the results you see.
When ranking results, Google Search also evaluates whether webpages are easy to use. When we identify persistent user pain points, we develop algorithms to promote more usable pages over less usable ones, all other things being equal.
These algorithms analyze signals that indicate whether all our users are able to view the result, like whether the site appears correctly in different browsers; whether it is designed for all device types and sizes, including desktops, tablets, and smartphones; and whether the page loading times work well for users with slow Internet connections.
Since website owners can improve the usability of their site, we work hard to inform site owners in advance of significant, actionable changes to our Search algorithms. For example, in January 2018 we announced that our algorithms would begin to consider the “page speed” of sites, six months before the changes went live. To aid website owners, we provided detailed guidance and tools like PageSpeed Insights and Webpagetest.org so site owners could see what (if anything) they needed to adjust to make their sites more mobile friendly.
You can find more information on the tools and tips Google provides to site owners here .
Information such as your location, past Search history and Search settings all help us to tailor your results to what is most useful and relevant for you in that moment.
We use your country and location to deliver content relevant for your area. For instance, if you’re in Chicago and you search “football”, Google will most likely show you results about American football and the Chicago Bears first. Whereas if you search “football” in London, Google will rank results about soccer and the Premier League higher. Search settings are also an important indicator of which results you’re likely to find useful, such as if you set a preferred language or opted in to SafeSearch (a tool that helps filter out explicit results).
In some instances, we may also personalize your results using information about your recent Search activity. For instance, if you search for “Barcelona” and recently searched for “Barcelona vs Arsenal”, that could be an important clue that you want information about the football club, not the city.
Search also includes some features that personalize results based on the activity in your Google account. For example, if you search for “events near me” Google may tailor some recommendations to event categories we think you may be interested in. These systems are designed to match your interests, but they are not designed to infer sensitive characteristics like your race, religion, or political party.
You can control what Search activity is used to improve your Search experience, including adjusting what data is saved to your Google account, at myaccount.google.com. To disable Search personalization based on activity in your account, turn off Web & App Activity.