Posted by matthew_jkay
Keyword research has been around as long as the SEO industry
has. Search engines built a system that revolves around users
entering a term or query into a text entry field, hitting return,
and receiving a list of relevant results. As the online search
market expanded, one clear leader emerged — Google — and with
it they brought AdWords (now Google Ads), an advertising platform
that allowed organizations to appear on search results pages for
keywords that organically they might not.
Within Google Ads came a tool that enabled businesses to look at
how many searches there were per month for almost any query. Google
Keyword Planner became the de facto tool for keyword research in
the industry, and with good reason: it was Google’s data. Not
only that, Google gave us the ability to gather further insights
due to other metrics Keyword Planner provided: competition and
suggested bid. Whilst these keywords were Google Ads-oriented
metrics, they gave the SEO industry an indication of how
competitive a keyword was.
The reason is obvious. If a keyword or phrase has higher
competition (i.e. more advertisers bidding to appear for that term)
it’s likely to be more competitive from an organic perspective.
Similarly, a term that has a higher suggested bid means it’s more
likely to be a competitive term. SEOs dined on this data for years,
but when the industry started digging a bit more into the data, we
soon realized that while useful, it was
not always wholly accurate. Moz, SEMrush, and other tools all
started to develop alternative volume and competitive metrics using
data to give marketers more insights.
Now industry professionals have several software tools and data
outlets to conduct their keyword research. These software companies
will only improve in the accuracy of their data outputs. Google’s
data is unlikely to significantly change; their goal is to sell ad
space, not make life easy for SEOs. In fact, they’ve made life
using volume ranges for Google Ads accounts with low activity.
SEO tools have investors and customers to appease and must
continually improve their products to reduce churn and grow their
customer base. This makes things rosy for content-led SEO,
Well, not really.
The problem with historical keyword research is
1. SEOs spend too much time thinking about the decision stage of
the buyer’s journey (more on that later).
2. SEOs spend too much time thinking about keywords, rather than
categories or topics.
The industry, to its credit, is doing a lot to tackle issue
number two. “Topics over keywords” is something that is
not new as
I’ll briefly come to later. Frameworks for
topic-based SEO have started to appear over the last few years.
This is a step in the right direction. Organizing site content into
categories, adding appropriate internal linking, and understanding
that one piece of content can rank for several variations of a
phrase is becoming far more commonplace.
What is less well known (but starting to gain traction) is point
one. But in order to understand this further, we should dive into
what the buyer’s journey actually is.
What is the buyer’s journey?
The buyer’s or customer’s journey is not new. If you open
marketing text books from years gone by, get a college degree in
marketing, or even just go on general marketing blogs you’ll see
it crop up. There are lots of variations of this journey, but they
all say a similar thing. No matter what product or service is
bought, everyone goes through this journey. This could be online or
offline — the main difference is that depending on the product,
person, or situation, the amount of time this journey takes will
vary — but every buyer goes through it. But what is it, exactly?
For the purpose of this article, we’ll focus on three stages:
awareness, consideration, & decision.
The awareness stage of the buyer’s journey is similar to
problem discovery, where a potential customer realizes that they
have a problem (or an opportunity) but they may not have figured
out exactly what that is yet.
Search terms at this stage are often question-based — users
are researching around a particular area.
The consideration stage is where a potential consumer has
defined what their problem or opportunity is and has begun to look
for potential solutions to help solve the issue they face.
The decision stage is where most organizations focus their
attention. Normally consumers are ready to buy at this stage and
are often doing product or vendor comparisons, looking at reviews,
and searching for pricing information.
To illustrate this process, let’s take two examples: buying an
ice cream and buying a holiday.
Being low-value, the former is not a particularly considered
purchase, but this journey still takes place. The latter is more
considered. It can often take several weeks or months for a
consumer to decide on what destination they want to visit, let
alone a hotel or excursions. But how does this affect keyword
research, and the content which we as marketers should provide?
At each stage, a buyer will have a different thought process.
It’s key to note that not every buyer of the same product will
have the same thought process but you can see how we can start to
formulate a process.
The Buyer’s Journey – Holiday Purchase
The above table illustrates the sort of queries or terms that
consumers might use at different stages of their journey. The
problem is that most organizations focus all of their efforts on
the decision end of the spectrum. This is entirely the right
approach to take at the start because you’re targeting consumers
who are interested in your product or service then and there.
However, in an increasingly competitive online space you should try
and find ways to diversify and bring people into your marketing
funnel (which in most cases is your website) at different
I agree with the argument that creating content for people
earlier in the journey will likely mean lower conversion rates from
visitor to customer, but my counter to this would be that you’re
also potentially missing out on people who will become customers.
Further possibilities to at least get these people into your funnel
include offering content downloads (gated content) to capture
user’s information, or remarketing activity via Facebook, Google
Ads, or other retargeting platforms.
Moving from keywords to topics
I’m not going to bang this drum too loudly. I think many in of
the SEO community have signed up to the approach that topics are
more important than keywords. There are quite a few resources on
this listed online, but what forced it home for me was Cyrus Shepard’s Moz
article in 2014. Much, if not all, of that post still holds
What I will cover is an adoption of HubSpot’s Topic
Cluster model. For those unaccustomed to their model,
HubSpot’s approach formalizes and labels what many search
marketers have been doing for a while now. The basic premise is
instead of having your site fragmented with lots of content across
multiple sections, all hyperlinking to each other, you create one
really in-depth content piece that covers a topic area broadly (and
covers shorter-tail keywords with high search volume), and then
supplement this page with content targeting the long-tail, such as
blog posts, FAQs, or opinion pieces. HubSpot calls this “pillar”
and “cluster” content respectively.
The process then involves taking these cluster pages and linking
back to the pillar page using keyword-rich anchor text. There’s
nothing particularly new about this approach aside from formalizing
it a bit more. Instead of having your site’s content structured
in such a way that it’s fragmented and interlinking between lots of
different pages and topics, you keep the internal linking within
its topic, or content cluster. This video
explains this methodology further. While we accept this model may
not fit every situation, and nor is it completely perfect, it’s a
great way of understanding how search engines are now interpreting
At Aira, we’ve taken this
approach and tried to evolve it a bit further, tying these topics
into the stages of the buyer’s journey while utilizing several
data points to make sure our outputs are based off as much data as
we can get our hands on. Furthermore, because pillar pages tend to
target shorter-tail keywords with high search volume, they’re often
either awareness- or consideration-stage content, and thus not
applicable for decision stage. We term our key decision pages
“target pages,” as this should be a primary focus of any
activity we conduct.
We’ll also look at the semantic relativity of the keywords
reviewed, so that we have a “parent” keyword that we’re
targeting a page to rank for, and then children of that keyword or
phrase that the page may also rank for, due to its similarity to
the parent. Every keyword is categorized according to its stage in
the buyer’s journey and whether it’s appropriate for a pillar,
target, or cluster page. We also add two further classifications to
our keywords: track & monitor and ignore. Definitions for these
five keyword types are listed below:
A pillar page covers all aspects of a topic on a single page,
with room for more in-depth reporting in more detailed cluster blog
posts that hyperlink back to the pillar page. A keyword tagged with
pillar page will be the primary topic and the focus of a page on
the website. Pillar pages should be awareness- or
A great pillar page example I often refer to is HubSpot’s Facebook
marketing guide or
Mosi-guard’s insect bites guide (disclaimer: probably don’t
click through if you don’t like close-up shots of insects!).
A cluster topic page for the pillar focuses on providing more
detail for a specific long-tail keyword related to the main topic.
This type of page is normally associated with a blog article but
could be another type of content, like an FAQ page.
Good examples within the Facebook marketing topic listed above
are HubSpot’s posts:
For Mosi-guard, they’re not utilizing internal links within
the copy of the other blogs, but the “older posts” section at the
bottom of the blog is referencing this guide:
Normally a keyword or phrase linked to a product or service
page, e.g. nike trainers or seo services. Target pages are
decision-stage content pieces.
Track & monitor
A keyword or phrase that is not the main focus of a page, but
could still rank due to its similarity to the target page keyword.
A good example of this might be seo services as the target page
keyword, but this page could also rank for seo agency, seo company,
A keyword or phrase that has been reviewed but is not
recommended to be optimized for, possibly due to a lack of search
volume, it’s too competitive, it won’t be profitable, etc.
Once the keyword research is complete, we then map our keywords
to existing website pages. This gives us a list of mapped keywords
and a list of unmapped keywords, which in turn creates a content
gap analysis that often leads to a content plan that could last for
three, six, or twelve-plus months.
Putting it into practice
I’m a firm believer in giving an example of how this would
work in practice, so I’m going to walk through one with
screenshots. I’ll also provide a template of our keyword research
document for you to take away.
1. Harvesting keywords
The first step in the process is similar, if not identical, to
every other keyword research project. You start off with a batch of
keywords from the client or other stakeholders that the site wants
to rank for. Most of the industry call this a seed keyword list.
That keyword list is normally a minimum of 15–20 keywords, but
can often be more if you’re dealing with an e-commerce website
with multiple product lines.
This list is often based off nothing more than opinion: “What
do we think our potential customers will search for?” It’s a
good starting point, but you need the rest of the process to follow
on to make sure you’re optimizing based off data, not
2. Expanding the list
Once you’ve got that keyword list, it’s time to start
utilizing some of the tools you have at your disposal. There are
lots, of course! We tend to use a combination of Moz Keyword Explorer, Answer the Public, Keywords Everywhere, Google
Search Console, Google Analytics, Google Ads, ranking tools, and
The idea of this list is to start thinking about keywords that
the organization may not have considered before. Your expanded list
will include obvious synonyms from your list. Take the example
ski chalet rental
ski chalet hire
ski chalet [location name]
There are other examples that should be considered. A client I
worked with in the past once gave a seed keyword of “biomass
boilers.” But after keyword research was conducted, a more
colloquial term for “biomass boilers” in the UK is “wood
burners.” This is an important distinction and should be picked
up as early in the process as possible. Keyword research tools are
not infallible, so if budget and resource allows, you may wish to
consult current and potential customers about which terms they
might use to find the products or services being offered.
3. Filtering out irrelevant keywords
Once you’ve expanded the seed keyword list, it’s time to
start filtering out irrelevant keywords. This is pretty
labor-intensive and involves sorting through rows of data. We tend
to use Moz’s Keyword
Explorer, filter by relevancy, and work our way down. As we go,
we’ll add keywords to lists within the platform and start to try
and sort things by topic. Topics are fairly subjective, and often
you’ll get overlap between them. We’ll group similar keywords
and phrases together in a topic based off the semantic relativity
of those phrases. For example:
ski chalet rental
ski chalet hire
ski chalet [location name]
luxury catered chalet
catered chalet rental
catered chalet hire
catered chalet [location name]
cheap ski accommodation
budget ski accommodation
ski accomodation [location name]
Many of the above keywords are decision-based keywords —
particularly those with rental or hire in them. They’re showing
buying intent. We’ll then try to put ourselves in the mind of the
buyer and come up with keywords towards the start of the buyer’s
best ski resorts
ski resorts europe
ski resorts usa
ski resorts canada
top ski resorts
cheap ski resorts
luxury ski resorts
skiing beginner’s guide
family winter holidays
This helps us cater to customers that might not be in the frame
of mind to purchase just yet — they’re just doing research. It
means we cast the net wider. Conversion rates for these keywords
are unlikely to be high (at least, for purchases or enquiries) but
if utilized as part of a wider marketing strategy, we should look
to capture some form of information, primarily an email address, so
we can send people relevant information via email or remarketing
ads later down the line.
4. Pulling in data
Once you’ve expanded the seed keywords out, Keyword
Explorer’s handy list function enables your to break things down
into separate topics. You can then export that data into a CSV and
start combining it with other data sources. If you have SEMrush API
Dave Sottimano’s API Library is a great time saver;
otherwise, you may want to consider uploading the keywords into the
Keywords Everywhere Chrome extension and manually exporting the
data and combining everything together. You should then have a
spreadsheet that looks something like this:
You could then add in additional data sources. There’s no
reason you couldn’t combine the above with volumes and
competition metrics from other SEO tools. Consider including
existing keyword ranking information or Google Ads data in this
process. Keywords that convert well on PPC should do the same
organically and should therefore be considered. Wil Reynolds talks
particular tactic a lot.
5. Aligning phrases to the buyer’s journey
The next stage of the process is to start categorizing the
keywords into the stage of the buyer’s journey. Something we’ve
found at Aira is that keywords don’t always fit into a predefined
stage. Someone looking for “marketing services” could be doing
research about what marketing services are, but they could also be
looking for a provider. You may get keywords that could be either
awareness/consideration or consideration/decision. Use your
judgement, and remember this is subjective. Once complete, you
should end up with some data that looks similar to this:
This categorization is important, as it starts to frame what
type of content is most appropriate for that keyword or phrase.
The next stage of this process is to start noticing patterns in
keyphrases and where they get mapped to in the buyer’s journey.
Often you’ll see keywords like “price” or ”cost” at the
decision stage and phrases like “how to” at the awareness
stage. Once you start identifying these patterns, possibly using a
variation of Tom
Casano’s keyword clustering approach, you can then try to
find a way to automate so that when these terms appear in your
keyword column, the intent automatically gets updated.
Once completed, we can then start to define each of our keywords
and give them a type:
- Pillar page
- Cluster page
- Target page
- Track & monitor
We use this document to start thinking about what type of
content is most effective for that piece given the search volume
available, how competitive that term is, how profitable the keyword
could be, and what stage the buyer might be at. We’re trying to
find that sweet spot between having enough search volume, ensuring
we can actually rank for that keyphrase (there’s no point in a
small e-commerce startup trying to rank for “buy nike
trainers”), and how important/profitable that phrase could be for
the business. The below Venn diagram illustrates this nicely:
We also reorder the keywords so keywords that are semantically
similar are bucketed together into parent and child keywords. This
helps to inform our on-page recommendations:
From the example above, you can see “digital marketing agency”
as the main keyword, but “digital marketing services” &
“digital marketing agency uk” sit underneath.
We also use conditional formatting to help identify keyword page
And then sheets to separate topics out:
Once this is complete, we have a data-rich spreadsheet of
keywords that we then work with clients on to make sure we’ve not
missed anything. The document can get pretty big, particularly when
you’re dealing with e-commerce websites that have thousands of
5. Keyword mapping and content gap analysis
We then map these keywords to existing content to ensure that
the site hasn’t already written about the subject in the past. We
often use Google Search Console data to do this so we understand
how any existing content is being interpreted by the search
engines. By doing this we’re creating our own content gap
analysis. An example output can be seen below:
The above process takes our keyword research and then applies
the usual on-page concepts (such as optimizing meta titles, URLs,
descriptions, headings, etc) to existing pages. We’re also
ensuring that we’re mapping our user intent and type of page
(pillar, cluster, target, etc), which helps us decide what sort of
content the piece should be (such as a blog post, webinar, e-book,
etc). This process helps us understand what keywords and phrases