How People Search: Understanding User Intent

In Google’s earlier days, the search engine relied heavily on plain text data and backlinks to establish rankings through periodic monthly refreshes (known as the Google Dance).

Since those days, Google search has become a sophisticated product with a plethora of algorithms designed to promote content and results that meet a user’s needs.

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

• Rankings.
• Search volumes.
• Organic traffic levels.
• Onsite conversions.

That’s because these metrics are what we are typically judged by as SEO professionals – and for the most part, can be measured across competitor websites (through third-party tools).

Clients want to rank higher and see their organic traffic increasing and, by association, leads and sales will also improve.

When we choose target keywords, there is the tendency and appeal to go after those with the highest search volumes, but much more important than the keyword’s search volume is the intent behind it.

There is also a tendency to discount any search phrase or keyword that has a low or no, search volume based on the fallacy of it offering no “SEO value,” but this is very niche dependent.

This is a key part of the equation that is often overlooked when content is produced, it’s great that you want to rank for a specific term, but the content has to not only be relevant but also satisfy the user intent.

This chapter will explain not only the different categorizations of search intent but also:

• How intent relates to the content and website experiences, we choose to produce.
• How the search engines establish user intent based on a simple query input.

The Science Behind Intent

In 2006, a study conducted by the University of Hong Kong found that at a primary level, search intent can be segmented into two search goals.

• A user is specifically looking to find information relating to the keyword(s) they have used.
• A user is looking for more general information about a topic.

A further generalization can be made, and intentions can be split into how specific the searcher is and how exhaustive the searcher is.

Specific users have a narrow search intent and don’t deviate from this, whereas an exhaustive user may have a wider scope around a specific topic or topics.

The search engines are also making strides in understanding both search intent. Google’s Hummingbird and Yandex’s Korolyov and Vega are just two examples of these.

Google & Search Intent

There have been a lot of studies conducted into understanding the intent behind a query, and this is reflected by the types of results that Google displays.

Google’s Paul Haahr gave a great presentation in 2016, looking at how Google returns results from a ranking engineer’s perspective.

The same “highly meets” scale can be found in the Google Search Quality Rating Guidelines.

In the presentation, Haahr explains basic theories on how if a user is searching for a specific store (e.g., Walmart), they are most likely to be looking for their nearest Walmart store, not the brand’s head office in Arkansas.

The Search Quality Rating Guidelines echo this. Section 3 of the guidelines details the “Needs Met Rating Guidelines” and how to use them for content.

The scale ranges from Fully Meets (FullyM) to Fails to Meet (FailsM) and has flags for whether or not the content is porn, foreign language, not loading, or is upsetting/offensive.

The raters are not only critical of the websites they display in web results but also the special content result blocks (SCRB), aka 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 Cannot Have Fully Meets Results.

Within this section, Google details that “Ambiguous queries without a clear user intent or dominant interpretation” cannot achieve a Fully Meets rating.

The example given is the query [ADA], which could be either the American Diabetes Association, the American Dental Association, or a programming language devised in 1980. As there is no dominant interpretation of the internet or the query, no definitive answer can be given.

Queries with Multiple Meanings

Due to the diversity of language, many queries have more than one meaning – for example, [Apple] can either be a consumer electrical goods brand or a fruit.

Google handles this issue by classifying the query by its interpretation.

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

Dominant Interpretations

The dominant interpretation is what most users mean when they search for a specific query.

Google search raters are told explicitly that the dominant interpretation should be clear, even more so after further online research.

Common Interpretations

Any given query can have multiple common interpretations.

The example given by Google in their guidelines is [mercury] – which can mean either the planet or the element.

In this instance, Google can’t provide a result that Fully Meets a user’s search intent but instead, produces results varying in both interpretation and intent (to cover all bases).

Minor Interpretations

A lot of queries will also have less common interpretations, and these can often be locale-dependent.

Do – Know – Go

Do, Know, Go is a concept that search queries can be segmented into three categories: Do, Know, and Go.

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

Do (Transactional Queries)

When a user performs a “do” query, they are looking to achieve a specific action, such as purchasing a specific product or booking a service.

These are important to e-commerce websites, for example, where a user may be looking for a specific brand or item.

Device action queries are also a form of do query and are becoming more and more important, given how we interact with our smartphones and other technologies.

Ten years ago, Apple launched the first iPhone, which changed our relationship with our handheld devices.

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

Obviously, 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 behaviors.

Device Action Queries & Mobile Search

Mobile search surpassed desktop search globally in May 2015 in the greater majority of verticals. In fact, a 2017 study indicates that 57% of traffic comes from mobile and tablet devices.

Google has also moved with the times – the two mobile-friendly updates and the impending mobile-first index being obvious indicators of this.

Increased internet accessibility also means that we are able to perform searches more frequently based on real-time events.

As a result, Google is currently estimating that 15% of the queries it’s handling on a daily basis are new and have never been seen before.

This is in part due to the new accessibility that the world has and the increasing smartphone and internet penetration rates being seen globally.

Mobile is gaining increasing ground not only in how we search but in how we interact with the online sphere.

In a number of countries, including the United States, United Kingdom, Brazil, Canada, China, and India, more than 60% of our time spent online is through a mobile device.

One key understanding of mobile search is that users may not also satisfy their query via this device.

In my experience, working across a number of verticals, a lot of mobile search queries tend to be more focused on research and informational, moving to desktop or tablet at a later date to complete a purchase.

According to Google’s Search Quality Rating Guidelines:

“Because mobile phones can be difficult to use, SCRBs can help mobile phone users accomplish their tasks very quickly, especially for certain Know Simple, Visit­ in ­Person, and Do queries.”

Mobile is also a big part of Google Search Quality Guidelines, with the entirety of section two dedicated to it.

Know (Informational Queries)

A “know” query is an informational query, where the user is wanting to learn about a particular subject.

Know queries are closely linked to micro-moments.

In September 2015, Google released a guide to micro-moments, which are happening due to increased smartphone penetration and internet accessibility.

Micro-moments occur when a user needs to satisfy a specific query there and then, and these often carry a time factor, such as checking train times or stock prices.

Because users can now access the internet wherever, whenever, there is the expectation that brands and real-time information are also accessible, wherever, whenever.

Micro-moments are also evolving.

Know queries can vary between simple questions [how old is tom cruise] too much broader and complex queries that don’t always have a simple answer.

Know queries are almost always informational in intent.

Know/Informational queries are neither commercial or transactional in nature. While there may be an aspect of product research, the user is not yet at the transactional stage.

A pure informational query can range from [how long does it take to drive to London], to [gabriel macht imdb].

To a certain extent, these aren’t seen in the same importance as directly transactional or commercial queries – especially by e-commerce websites. Still, they do provide user value, which is something Google looks for.

For example, if a user wants to go on holiday, they may start with searching for [winter sun holidays europe] and then narrow down to specific destinations.

Users will research the destination further, and if your website is providing them with the information they’re looking for, then there is a chance they may also inquire with you as well.

Featured Snippets & Clickless Searches

Rich snippets and special content results blocks (i.e., featured snippets) have been a main part of SEO for a while now, and we know that appearing in a SCRB area can drive huge volumes of traffic to your website.

On the other hand, appearing in position zero can mean that a user won’t click through to your website, meaning you won’t get the traffic and the chance to have them explore the website or count towards ad impressions.

That being said, appearing in these positions is powerful in terms of click-through rate and can be a great opportunity to introduce new users to your brand/website.

Go (Navigational Queries)

“Go” queries are typically brand or known entity queries, where a user is looking to go to a specific website or location.

If a user is specifically searching for Adidas, serving them Puma as a result wouldn’t meet their needs.

Likewise, if your client wants to rank for a competitor brand term, you need to make them question why would Google show their site when the user is clearly looking for the competitor.

Defining Intent Is One Thing, User Journeys Another

For a long time, the customer journey is a staple activity in planning and developing both marketing campaigns and websites.

While mapping out personas and planning how users navigate the website is important, it’s necessary to understand how a user searches and at what stage of their own journey they are at.

The word journey often sparks connotations of a straight path, and a lot of basic user journeys usually follow the path of 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 introduced a new dynamic to our daily lives and shape our day-to-day decisions in a way like no other.

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

Users no longer search in a single manner, and because of how Google has developed in recent years, there is no single search results page.

We can determine the stage the user is at through the search results that Google displays and by analyzing proprietary data from Google Search Console, Bing Webmaster Tools, and Yandex Metrica.

The Intent Can Change, Results & Relevancy Can Too

Another important thing to remember is that search intent and the results that Google displays can also change – quickly.

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

Unlike other DDoS attacks before it, the press coverage surrounding the Dyn attack was mainstream – the White House even released a statement on it.

Before the attack, searching for terms like [ddos] or [dns] produced results from companies like Incapsula, Sucuri, and Cloudflare.

These results were all technical and not appropriate for the newfound audience discovering and investigating these terms.

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

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

This is why it’s important to not only optimize for keywords that drive converting traffic but also those that can provide user value and topical relevance to the domain.

Machine Learning & Intent Classification

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

Machine learning becomes more effective over time, and this, coupled with other algorithms, can change search results pages – as well as lead Google to experiment with SCRBs and other SERP features.

Featured Image Credit: Paulo Bobita