1. The science behind the intent
  2. Google & search intent
  3. Queries with multiple meanings
  4. Do – Know – Go
  5. Go (navigation queries)
  6. Defining intent is one thing, user travels another
  7. The intention can change, results and relevance can change too
  8. Machine learning and intent classification

In the earlier days of Google, the search engine relied heavily on plain text data and backlinks to build rankings through regular monthly updates (known as Google Dance).

As of those days, Google Search has become a sophisticated product with a variety of algorithms designed to advertise content and results that meet a user's needs.

To a certain extent, a lot of SEO is a numbers game. We focus on:

  • Leaderboards.
  • Search volume.
  • Organic traffic.
  • On-site modifications.


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This is because these metrics are usually judged by SEO professionals – and for the most part can be measured on competitor websites (using third-party tools).

Customers want to rank higher and see their organic traffic increase. The association will also improve leads and sales.

When we choose target keywords there is a tendency and attraction to find the ones with the highest search volume, but much more important than the keyword's search volume is the intent behind it.

There is also a tendency to ignore search phrases or keywords with little or no search volume based on the misconception that they do not offer "SEO value". However, this is very niche-dependent.

This is an important part of the equation that is often overlooked when creating content. It's great that you want to rank a certain term, but not only does the content need to be relevant, it needs to meet the user's intent.


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In addition to explaining the various search intent categorizations, this chapter also explains:

  • How the intent relates to the content and website experience is what we produce.
  • How the search engines determine user intent from a simple query.

The science behind the intent

In 2006, a study conducted by the University of Hong Kong found that on a primary level, search intent can be broken down into two search targets.

  • Specifically, a user is looking for information about the keywords they are using.
  • A user is looking for more general information on a topic.

A further generalization can be made and the intentions can be broken down according to how specific the seeker is and how exhaustive the seeker is.

Certain users will have a narrow search intent and will not stray from it, whereas an exhaustive user may have a larger scope on a particular subject or subjects.

The search engines are also making strides in understanding both search intentions. Google's Hummingbird and Yandex 'Korolyov and Vega are just two examples of this.

Google & search intent

Many studies have been done to understand the intent of a query. This is reflected in the types of results displayed by Google.

Paul Haahr from Google gave a great presentation in 2016 examining how Google returns results from a ranking engineer's perspective.

The same “high demands” scale can be found in the quality rating guidelines for Google Search.

In the presentation, Haahr explains basic theories about how when a user searches for a specific store (e.g., Walmart), they are most likely looking for their nearest Walmart store, not the brand's Arkansas headquarters.


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The guidelines for evaluating search quality reflect this. Section 3 of the Guidelines describes the “Guidelines for Meeting the Rating Requirements” and how they are used for content.

The scale ranges from Fully Meets (FullyM) to Fails to Meet (FailsM) and contains indicators for whether the content is porn, foreign languages, not loaded or disturbing / offensive.

Not only do reviewers criticize the websites they display in web results, but also the special content result blocks (SCRB), also known as rich snippets, and other search features that appear in addition to the “10 blue links”.

One of the more interesting sections of these guidelines is 13.2.2, titled: Examples of Queries That Can't Fully Satisfy Results.

In this section, Google states that "Ambiguous queries without clear user intent or dominant interpretation" cannot achieve full satisfaction.

The example given is the query (ADA), which can be either the American Diabetes Association, the American Dental Association, or a programming language developed in 1980. Since the Internet or the query are not interpreted in a dominant manner, no final answer can be given.


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Queries with multiple meanings

Due to the multitude of languages, many inquiries have more than one meaning – for example (Apple) can either be a brand for electrical appliances or a fruit.

Google addresses this problem by classifying the query based on its interpretation.

The interpretation of the query can then be used to define the intent. Query interpretations are divided into the following three areas:

Dominant interpretations

The prevailing interpretation is what most users mean when they search for a particular query.

Google searchers are specifically advised that the prevailing interpretation should be clear, especially after further online research.

Common interpretations

Each query can have several common interpretations.

The example that Google gave in its guidelines is (mercury) – which can mean either the planet or the element.

In this case, Google cannot provide a result that fully meets a user's search intent. Instead, results are obtained that differ in both interpretation and intent (to cover all bases).


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Minor interpretations

Many queries are also interpreted less frequently, and these can often be locale-dependent.

Do – Know – Go

Do, Know, Go is a concept that allows search queries to be broken down into three categories: Do, Know, and Go.

These classifications then, to some extent, determine the type of results Google delivers to its users.

Do (transaction queries)

When a user executes a "Do" query, they want to take a certain action, e.g. B. the purchase of a certain product or the booking of a service.

These are important, for example, for ecommerce websites where a user might be looking for a specific brand or item.

Device action queries are also a form of query and are becoming increasingly important as we interact with our smartphones and other technologies.

Ten years ago, Apple released the first iPhone that changed the way we relate to our handheld devices.

The smartphone was more than just a phone. It opened our access to the internet on our terms.


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Of course, before the iPhone we had 1g, 2g and WAP – but it was really 3g that emerged around 2003 and the birth of widgets and apps that changed our behavior.

Device action queries and mobile search

Mobile search outperformed desktop search in the vast majority of industries worldwide in May 2015. According to a 2017 study, 57% of traffic comes from mobile and tablet devices.

Google has moved with the times too – the two mobile-friendly updates and the upcoming mobile-first index are obvious indicators of that.

Due to the improved accessibility of the Internet, we can also carry out searches based on real-time events more frequently.

Because of this, Google currently estimates that 15% of the queries it handles on a daily basis are new and have never been seen before.

This is partly due to the new accessibility of the world and the increasing penetration rates of smartphones and the internet worldwide.

Mobile is not only gaining in importance when it comes to searching, but also when interacting with the online sphere.


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In a number of countries including the US, UK, Brazil, Canada, China and India, we spend more than 60% of our online time on a mobile device.

An important understanding of mobile search is that users may not fulfill their query through that device either.

In my experience, when working in a number of industries, many mobile searches tend to focus more on research and information and switch to desktop or tablet at a later date to complete a purchase.

As per Google's search quality rating guidelines:

"Since cell phones can be difficult to use, SCRBs can help cell phone users get their jobs done very quickly, especially with certain questions about 'Know Simple', 'Visit in Person' and 'Do'."

Mobile is also an important part of Google's search quality guidelines. The entire second section is devoted to this topic.

Knowledge (information requests)

A "knowledge" query is an information query in which the user would like to learn more about a certain topic.


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Knowledge queries are closely related to micro-moments.

In September 2015, Google published a guide on micro-moments that occur due to the increasing prevalence of smartphones and accessibility on the Internet.

Micro moments occur when a user has to fulfill a particular request there and then, and these often carry a time factor with them, e.g. B. checking the train times or the share prices.

With users now able to access the Internet anywhere, anytime, the expectation is that brands and real-time information will be available anywhere, anytime.

Micro moments also develop.

Knowledge queries can vary from simple questions (how old is Tom Cruise) to much broader and complex questions that don't always have a simple answer.

Knowledge queries are almost always informative.

Knowledge / information requests are neither commercial nor transactional in nature. While there may be some aspect of product research, the user is not yet in the transaction stage.

A mere request for information can range from (how long does the trip to London take) to (Gabriel makes imdb).


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To some extent, these are not seen in the same way as direct transactional or commercial queries – especially from e-commerce websites. Still, they offer some utility that Google is looking for.

For example, if a user wants to go on vacation, they can start by searching for (Winter Sun Holidays Europe) and then limit themselves to specific destinations.

Users will continue to investigate the target. If your website gives them the information they're looking for, chances are they'll ask you too.

Selected snippets and clickless searches

Large snippets and special content blocks for content (i.e. exhibited snippets) have been a major part of search engine optimization for a while, and we know that appearing in an SCRB area can generate a large amount of traffic to your website.

On the flip side, showing up in position zero can mean that a user hasn't clicked on your website, which means you don't get the traffic and the opportunity to explore the website or count for ad impressions.


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However, appearing in these positions is very important in terms of CTR and can be a great opportunity to introduce new users to your brand / website.

Go (navigation queries)

"Go" queries are typically branded or well-known entity queries where a user wants to go to a specific website or location.

If a user were specifically looking for Adidas, Puma's operation would not meet the requirements.

If your customer wants to rank a competitor's brand term, they need to be asked why Google should display their website when the user is clearly looking for the competitor.

Defining intent is one thing, user travels another

The customer journey has long been an important activity in planning and developing marketing campaigns and websites.

While it is important to map personas and plan how users will navigate the website, understanding how a user searches and what stage of their own journey they are at is important.


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The word "trip" often has straight-path connotations, and many basic user trips typically follow the path "landing page> form or homepage> product page> form".

We assume that users know exactly what they want to do, but mobile and voice search has given a new dynamic to our daily lives and shaped our daily decisions in unparalleled ways.

These micro-moments directly challenge our understanding of the user journey.

Users no longer search in one single way. Due to the development of Google over the past few years, there is not a single search results page.

Based on the search results displayed by Google and the analysis of proprietary data from the Google Search Console, Bing Webmaster Tools and Yandex Metrica, we can determine at what stage the user is.

The intention can change, results and relevance can change too

Another important point to note is that search intent and the results that Google displays can also change quickly.

An example of this was the Dyn DDoS attack that took place in October 2016.


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Unlike other previous DDoS attacks, coverage of the Dyn attack was mainstream – the White House even issued a statement on it.

Prior to the attack, searching for terms like (ddos) or (dns) led to results from companies like Incapsula, Sucuri and Cloudflare.

These results were all technical and unsuitable for the newly discovered audience that discovered and explored these terms.

What was once a query with commercial or transactional intent quickly became informative.

Within 12 hours of the attack, search results changed and became news results and blog articles explaining how a DDoS attack worked.

For this reason, it is important to optimize not only for keywords that drive conversion traffic, but also for keywords that offer the user added value and current relevance for the domain.

Machine learning and intent classification

If over time a large number of websites produce different content and influence user search behavior through marketing and other means, the output intent for a query changes.


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Machine learning becomes more effective over time and, when combined with other algorithms, can change search results pages – and prompt Google to experiment with SCRBs and other SERP features.

Selected image source: Paulo Bobita


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