How To Redefine Your Search Intent Strategy For 2020

Written by dale-bonsor | Published 2020/01/30
Tech Story Tags: seo-optimization | digital-marketing | seo | marketing | what-is-search-intent | search-intent-explained | google's-micromoments | startups

TLDR Google has significantly improved the way they serve a user’s query, without solely leaning on traditional ranking factors. Google coined their own variation of this theory, known as micro-moments, in the early 2010s, which covered the following four ‘intent rich moments’ We don’t believe they hold much use for the Digital Marketing professional these days. The current standard is through three, or sometimes four, basic fundamental sub-categories: Navigational, Informational, Transactional, Commercial (Sometimes) and Commercial.via the TL;DR App

If you follow news from the digital marketing community, particularly over the past few years or so, one of the most commonly touched upon topics is that of ‘Search Intent’, and it’s been covered by some of the big guns in the industry.
Neil Patel, Rand Fishkin and Brian Dean, to name but a few, have all covered this topic to varying degrees over the past few years.

Why Are We Talking About Search Intent So Much?

These days, Google has significantly improved the way they serve a user’s query, without solely leaning on traditional ranking factors.
It’s because of this that we’re talking more and more about search intent, as old school ranking factors such as metadata, links, and other necessary SEO tactics, are no longer carrying the same dominance that we saw during the early to mid-part of the past decade.
In this blog, we’re going to talk about why we are not convinced that the currently accepted landscape of search intent will help to create better content and user-experience. We’ll also talk about how we believe it should be done instead.

The Current Search Intent Model Was Defined Way Back in 2002

The most common way that we define search intent is through three, or sometimes four, basic fundamental sub-categories:
  • Navigational
  • Informational
  • Transactional
  • Commercial (Sometimes)
This approach was first seen in a 2002 research piece (which you can find here) from IBM Researcher Andrei Broder.
The paper describes each as follows as the ‘taxonomy of web searches’:
  • Navigational – ‘The immediate intent is
    to reach a particular site.’
  • Informational – ‘The intent is to acquire
    some information assumed to be present on one or more web pages.’
  • Transactional – ‘The intent is to perform
    some web-mediated activity.’
In the early 2010s, Google coined their own variation of this theory, known as micro-moments, which covered the following four ‘intent rich moments’:
  • I Want to Know Moments – ‘When a user is
    exploring or researching but isn’t necessarily ready to buy.’
  • I Want to Go Moments – ‘When a user is looking for a local business or considering making a purchase in a nearby store.’
  • I Want to Do Moments – ‘When a user is looking for help to get something done or wants to try something new.’
  • I Want to Buy Moments – ‘When a user wants to make a purchase and needs help deciding what to purchase or how to buy it.’
While slightly more user-friendly, Google’s micro-moments is really just a spin on what Broder put forward years earlier.
Although these classifications are still very useful when helping beginners understand how search variations can produce different results, we don’t believe they hold much use for the Digital Marketing professional these days.
But why is that?

They’re Too Broad

As professionals in the industry, we already know that understanding what someone is looking for will help us produce more exciting and useful content. The problem comes when you take the current standard and try to use it in real-world scenarios.
When trying to determine the difference between format-defined
informational searches, such as ‘cute cat videos’, or branded informational searches, like ‘London Underground routes’, your only choice when using the current system is to label them both as ‘informational’ searches.
This isn’t especially helpful when trying to map your content for either of those phrases since it’s hard to define precisely what the user is looking for.

No Consideration for ‘Overlapping Intent’

We also need to consider that some searches will certainly overlap into more than one category. For example, if someone searches ‘eBay shoe deals’, would you categorise that as a navigational search, in that the user is trying to reach the eBay website, or a transactional sale, as the user is clearly trying buy shoes?
Attempting to pigeon-hole intent into one category, rather than considering overlapping intent, means that you’re potentially missing an array of opportunities to create more content.

Encourages Assumption

The current method for assigning intent to keywords involves adding modifiers, such as the ones below, that we assume will generate specific interest.
This would include moving through your list and adding a particular
keyword into the transactional, informational or navigational column.
So, for example, we could take a specific keyword, add ‘sale’, ‘deals’ or ‘for sale’ to it, drop it in the transactional column and move on.
However, if we encounter a query, such as the ‘London Underground route’ from earlier, for example, we mustn’t just mark it as informational and move on. This could mean different things to different people; are people looking for maps, timetables, or even the history of the underground?
If we encounter a query that is not clearly defined to the three current categories, we need to mark it as overlapping intent. More than this, though, we need to do some research, what is Google’s response to this search query:
Here we see a selection of images, map results, journey planners and there’s also a selection of news stories further down the page.
What this tells us is that we’re not going to rank for informational intent with such strong competition, so we need to change tact and create another kind of content piece that has a better chance of competing – but at the moment we only have two other options to choose from.
Without taking the time to undertake this research, it’s all too easy to jump in and create a piece of informational copy – by looking at what’s around us, we’ve essentially decided we need to change course and think of another strategy.

Thinking Like a Search Engine

The individuals in the marketing community are not search engines, and not one of us is trying to decide what results a user needs to see – that’s the job of the search engines.
The goal we should instead be trying to achieve is to forget about the real intent of every user, and instead, try to understand the kind of content search engines want to provide based on what they know about a user’s intent. We’ve been careful not to mention ‘user intent’ in this post, but rather ‘search intent’, for this very reason.
On a basic level, we need to get better at understanding whether the content we’re delivering and the format we’re delivering it in, is in line with what Google wants to present to its users.

How Should We Be Classifying Search Intent?

We think that it’s far more useful to categorise search intent in a way that closely coordinates with how Google presents information, since this will help your research before creating any content.
By showing you these expanded classifications, it gives you more scope in your content creation, and while you can’t optimise for every kind of intent every time, it can still help you in the following ways:
  • Streamline keyword research
  • Discover new opportunities and content gaps that
    you could serve
  • Categorise overlapping intent
  • Understand how and why Google is putting specific
    results in front of people
Here are the intent types we should be focusing on:

Investigative Intent

Investigative intent consists of words and phrases that bring up results that include Wikipedia, definition boxes, people also ask boxes, scholarly articles, blog posts, featured snippets, videos and other SERP features that point to the fact that a user is trying to find insight or the answer to a question.

Instant Intent

This is similar to investigative intent; however, these are questions that require an immediate response, that we wouldn’t usually click on to research it further – the user is just looking for a quick answer.
These include answer boxes, calculators, sports scores, and
train times.

Transactional Intent

Transactional intent is easy to spot since Google will display shopping
boxes and other purchase led features.
Other typical results for a transactional keyword includes results heavy
with ecommerce stores like Amazon, eBay, Etsy and other stores related to the niche of the search.


Local Intent

Local intent search results will be filled with local packs, maps, geographic markers and local places of interest.

Visual Intent

Visual intent is someone looking for images and is easy to spot in the
search results, as the user will be presented with image carousels, thumbnails and websites such as Pinterest – if you see this it’s certainly worth undertaking image SEO or starting a Pinterest board.

Audio Visual Intent

We’ve classified images and videos as their own intents, as Google offers pictures and videos differently.
Videos are presented in carousels, thumbnails, and within the search results, since video is becoming such an important ranking signal.

News Intent

When someone is looking for the latest news, they’ll see top story boxes, the latest tweets, and consistent use of dates within the organic results, the latter of which indicates that there is a tremendous amount of content being produced on that topic.
From this, we can conclude that Google will see higher interaction with the article, the more recent it is.

Brand Intent

Brand intent searches are pretty much exactly what they sound like, and the user is likely to see a homepage links, ‘domain clustering’, in which several pages from the same website appear in the SERP, and any of the latest news relating to the brand.

Overlapping Intent

We’ve covered overlapping extent previously and we’ll see overlapping intent presented in search in several different ways. As we’ve mentioned, these can be very tough to rank for since you’re trying to compete with more than one kind of intent.
For example, if you’re writing a piece of general historical content about the Battle of Waterloo with investigative intent in mind, you’ve got very little chance of ranking, unless your article refocuses on a very niche part of the battle.

How Can We Define Overlapping Intent?

The biggest challenge for us search engine professionals in the modern-day is how common it is to find a search term that has numerous intent options. So, as professionals, we need to find a way to show overlapping intent.
We can do this by developing a scoring method for each type of intent.
Let’s take the example of the ‘Battle of Waterloo’ again, once we’ve Googled
this term we can begin to determine what signals we see for each intent type, for example:
Further down the page, we see:
In this search result, we’ve seen an overlap between four of our eight
intent types: Investigative, Audio-visual, Visual and Instant.
Now we’ve recognised what we’re working with; we could create a simple
table to indicate how prominent each type is from one to three. It’s worth
noting here that although audio-visual intent is quite noticeable, it does not appear at the top of the search result; therefore, the mark we give it should be less, for example:
Here, we’ve chosen to assign two ticks to instant and visual intent
given that they appear at the top of the search, but we’ve only assigned audio-visual one tick due to the reason we’ve already mentioned. The clear winner though was investigative intent, since Google displayed Wikipedia pages, in-depth articles and people also ask boxes.
From here you might conclude that a general piece of content will not be
enough to rank, so what you could do instead is decide to focus on something more granular, such as a profile on the Prussian military general Gebhard Leberecht von Blücher who led his troops against Napoleon.
You could then add plenty of visual and audiovisual content and answer the question succinctly in the first paragraph to target those snippets from the previous example.

What Happens When Intent Changes?

As we’ve discovered search intent changes all the time, and
when it does, it is more than capable of impacting your content.
When this does happen, your ranking tools and Google
analytics data will give you your first indication that something is amiss.
This is a perfectly regular occurrence in the day-to-day
work of an SEO, and sometimes we just have to roll with punches, and in this case, it simply means you need to change your content.
The most obvious answer will be that a competitor has taken
your content, improved it and has managed to sneak ahead of you. Sometimes though, it’ll be less noticeable, and in this case, you’ll need to undertake the intent test score again to see in more detail what you might be missing.

Takeaways

Google and other search engines have evolved beyond comparison since the early days of search. This has meant that people are smarter and savvier about the way they browse the internet, and search engines have needed to adapt to this change.
Understanding search intent has given search engines a much better understanding of what people are looking for, which begs the question, as search engine professionals, why are we leaning on a method of understanding search intent which was first defined way back in 2002?
This neither takes into account how much the search engines have changed, nor does it allow us to create the kind of content that people are actually keen to see.
By embracing a new way of thinking, we can create much better content, that has a much better chance of ranking in the search engines. But more than that, we can create content that engages and informs.
Dale Bonsor is a content expert and marketing executive at quibblecontent.co.uk

Written by dale-bonsor | Dale Bonsor is a content expert and marketing executive at quibblecontent.co.uk
Published by HackerNoon on 2020/01/30