The SEO Industry
As long as the SEO industry has been around, so has keyword research. A system that has search engines built around around the term or query that users depict. Users query information into a text entry field, hit return and receive a list of relevant results.
As the online search market expanded, Google emerged as the King of The Castle. The clear leader.
Google is now synonymous with “search”.
Google bought with it AdWords (now Google Ads), an advertising platform that allowed organization to appear on search results pages for keywords that organically that might not.
Google Ads came with a tool that enabled businesses to look at how many search there were per month for almost any query.
The de facto tool for keyword research in the industry is Google Keyword Planner. It only makes sense since it is 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.
While these keywords were Google Ads-oriented metrics, they provided the SEO industry an indication of how competitive a keyword was.
The reason is quite clear. 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.
Conversely, a term that has a higher suggested bid means it is more likely to be a competitive term.
For years, SEOs dined on this data. 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 Clickstream data to give marketers more insights.
Industry professionals, now 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. It is not intended to make life easy for SEOs.
Conversely, they have made life harder by 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, right?
The problem with historical keyword research is twofold:
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.
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.
Much less known, but starting to gain traction is point one. However; in order to understand this better, you should dive into what the buyer’s journey actually is.
What is the buyer’s journey?
The customer’s or buyer’s journey is not new. Old textbooks about marketing, from many years ago, or if you have a college degree in marketing, or even just to on general marketing blogs, you will see it crop it.
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. However; every buyer goes through it.
But what is it exactly?
For the purpose of what we want to get across, we will focus on three stages: awareness consideration and 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 even 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. It is at this point where they have begun to look for potential solutions to help solve the issue they face.
The decision stage is where most organizations focus their attention. Consumers are normally ready to buy at this stage. They are often doing product or vendor comparisons. They are looking at reviews and searching for pricing information.
In order to illustrate this process, let’s take two examples, buyting an ice cream and buying a vacation.
In the case of the ice cream, since it is of such low value, it is not considered a purchase. But the journey still takes place. Buying the vacation is more to consider.
It can take several weeks or months for a consumer to decide on what destination they want to visit. Much less decide on the hotel or excursions.
But how does this affect keyword research and the content which we as marketers should provide?
A buyer will have a different thought process at each stage. It is 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 – Vacation Purchase
The table illustrates the kind of queries or terms that consumers may use at different stages of their journey. The issue is that most organizations focus all of their efforts on the decision end of the spectrum.
This is the right approach to take at the start. Because you are targeting consumers who are interested in your product or service then and there.
However; in an more competitive online space, you should try to find ways to diversity. This would allow you to bring people into your marketing funnel (which usually is your website) at different stages.
Creating content for people earlier in the journey will likely mean lower conversion rates from visitor to customer. I totally agree with that argument. But a counter to this would be that you are also potentially missing out on people who will become customers.
Further possibilities t at least get these people into your funnel include offering content downloads (gated content) to capture user’s information. Or re marketing activity via Facebook, Google Ads, or other re-targeting platforms.
Moving from Keywords To Topics
In an effort to not sound redundant, I’m going to scale this back a little. Many in 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 was Cyrus Shepard’s Moz article in 2014. Much of that post still holes true today.
I will cover is an adoption of HubSpot’s Topic Cluster model. For those of you 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. It is one really in-depth content piece that covers a topic area broadly.
It also covers shorter-tail keywords with high search volume and supplements this page with content targeting the long-tail. Like blog posts, FAQs or opinion pieces. HubSpot call this “pillar” and “cluster” content respectively.
Source: Matt Barby/HubSpot
Then the process take the cluster pages and linking back to the pillar page using keyword rich anchor text. There is nothing particularly new about this approach. Except formalizing it a bit more.
Instead of having your site’s content structured in such a way that it is fragmented and interlinking between lots of different pages and topics. You keep the internal linking within its topic, or content cluster.
We accept that this model may not fit every situation. Nor is it completely perfect. However; it is a great way of understanding how search engines are now interpreting content.
We are trying to evolve it a bit further. By 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 keywrods with high search volume, they are often either awareness or consideration stage content. Therefore; not applicable for the decision stage. These decision pages are termed “target pages”.
As this should be a primary focus of any activity we conduct.
We will also look at the semantic relativity of the keywords reviewed. So that we have a “parent” keyword that we are 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 is 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 signle 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 consideration stage content.
A great pillar page is HubSpot’s Facebook marketing guide or Mosi-guard’s insect bites guide.
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.
For Mosi-guard, they are not utilizing internal links within the copy of the other blogs.
Normally a keyword or phrase linked to a product or service page. For example, Nike trainers or SEO services. Target pages are decision-stage content pieces.
HubSpot’s target content is their social media software page. With one of Mosi-guard’s target pages being their natural spray product.
Track & Monitor
While a keyword or phrase may not be the main focus of apge, 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, etc.
A keyword or phrase that has been reviewed but it not recommended to be optimized for, possibly due to a lack of search volume. It is too competitive. It won’t be profitable.
When the keyword research is complete, then map our keywords to existing website pages. This gives us a list of mapped keywords and a list of mapped and umapped keywords. Which in turn creates a content gap analysis that often leads to a content plan that could last for three, six or twelve months or more.
Putting it into practice.
It is always best to give an example of how this would work in practice. So let’s walk through one with screenshots. This will 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 are 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 is a good starting point. But you need the rest of the process to follow on to make sure you are optimizing based off data, not opinion.
2. Expanding the list
Now that you have that keyword list, it is time to start utilizing some of the tools. You have many at your disposal.
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 SEMrush.
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.
There are many examples that you should consider. Think about 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 allow it, you may want to consult current and potential customers about the terms they want to use. So you can find the products or services being offered.
3. Filtering out irrelevant keywords
Now that you have expanded the seed keyword list, it is time to start filtering out irrelevant keywords. This is labor-intensive. It involves sorting through rows of data.
We tend to use Moz’s Keyword Explorer. Then filter by relevancy and work our way down. As we go, we will add keywords to lists within the platform and start to try and sort things by topic.
Topics are fairly subjective and often you will get overlap between them. We will group similar keywords and phrases together in a topic based off the semantic relativity of those phrases.
Many of the above keywords are decision based keywords. Particularly those with rental or hire in them. They are showing buying intent. We will then try to put ourselves in the mind of the buyer and come up with keywords towards the start of the buyer’s journey.
This help cater to customers that may not be in the frame of mind to purchase. They may just be doing research. It means that we cast the net wider. Conversion rates for these keywords are unlikely to be high. At least for purchases or inquirers.
However; if utilized as part of a wider marketing strategy, we should look to capture some form of information. Basically an email address. So we can send people relevant information via email or re-marketing ads later down the line.
4. Pulling in data
Once you have expanded the seed keywords out, Keyword Explorer’s handy list function enables you 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 access, 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.
Then manually exporting the data and combing everything together. You should then have a merged spreadsheet that looks like this:
You then can add in additional data sources. There is no reason you could not combine the above with volumes. And also 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.
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. Remember, this is subjective
Once complete, the result should be data that looks similar to this:
This categorization is important. It starts to frame what type of content is most appropriate for that keyword or phrase.
Next in the process, is to start noticing patterns in keyphrases and where they get mapped to in the buyer’s journey. You will often see keywords like “price” or “cost” at the decision stage and phrases like “how to” at the awareness stage.
When you begin to start identifying these patterns, 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.
When it is completed, you can then begin to define each of the keywords and give them a type:
Track & monitor
Then you can use this document to start thinking about what type of content is most effective. This is for the piece given the search volume available. And how competitive that item is. As well as how profitable the keyword could be, and what stage the buyer might be at.
We are trying to find that sweet spot between having enough search volume, ensuring we can actually rank for that keyphrase. There is no point in a small e-commerce startup trying to rank for “buy Nike trainers”. You will realize how important and profitable that phrase could be for the business.
The below Venn diagram by aira illustrates this nicely:
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:
You can notice in the example above, you can see “digital marketing agency” as the main keyword. However; “digital marketing services” & “digital marketing agency uk” sit underneath.
We also use conditional formatting to identify keyword page types:
To separate topics out sheets:
Now that this is complete, we have a data rich spreadsheet of keywords. Keywords that we then work with clients on. To ensure we have not missed anything.
The documents can get really big. Especially when you are dealing with e-commerce websites that have thousands of products.
5. Keyword mapping and content gap analysis
We then map these keywords to existing content to ensure that the site has not already written about the subject in the past. We often use Google Search Console data to do this. This way we understand how any existing content is being interpreted by the search engines.
This way, we are creating our own content gap analysis. The output example can be seen below:
The process as shown above, takes our keyword research and applies the usual on page concepts. Like optimizing meta titles, URLs, descriptions, headings, etc.
We are also ensuing that we are mapping our user intent and type of page, like pillar, cluster, target, etc. Which helps to decide what kind of content the piece should be. For instance, a blog post, webinar, e-book, etc. This process helps to understand what keywords and phrases the site is not already being found for. Or is not targeted to.