Theoretically, any piece of content is “rankable” on a highly competitive keyword. However, what often goes unspoken is the sheer scale of effort and the timeline required to achieve this goal.
Not every company possesses the luxury of patience, waiting to see their content rise to the first page of search results. Quite often I receive questions about outcomes shortly after the campaign begins, sometimes as early as one to two months in.
This is precisely why I advocate for what I like to call the 'sprint strategy' at the very beginning of an SEO campaign. This approach not only accelerates results but also lays the foundation for the campaign, driving commercial value to your site much sooner.
By identifying and prioritizing on keywords that we can rank for more quickly, we're able to distribute our time and resources in the most effective manner possible.
Metrics to determine prioritization
In SEO, what makes it so interesting is that everyone places different emphasis on various metrics in their decision-making process. Personally, two metrics are exceptionally pivotal to determining which keywords deserve our immediate attention.
They are ‘Search Volume’ and ‘Keyword Competition.
Search Volume is the measurement of the monthly search query count for a specific keyword or phrase across search engines. It provides insight into the potential traffic that could be channeled to both you and your competitors.
Keyword Competition - sometimes known as "Keyword Difficulty" - is a metric that measure the difficulty of achieving a high ranking for a keyword or query. This figure is crucial because it influences our strategy for content creation and optimization.
A link-centric approach to refine keyword difficulty
By learning how SEMRush and Ahrefs formulate their own keyword difficulty indexes, I distilled the essence of their calculations, keeping only components related to links.
Let me share with you the criteria I employ to measure the difficulty of ranking the keyword to the first page.
- the number of search results with a domain rating lower than a (_).
- the distribution of referring domains among the search results.
Further reading: Domain Rating: What It Is & What It’s Good For
You will notice the underscore from the first criterion - it represents a variable number that you have to determine based on your website’s domain rating (DR).
There isn’t a universal figure thats guarantee whether you content is “rankable”. The strategy is to identify the number of domains whose DR is comparable to your own.
For instance, if your site sits at DR 20, you might set your threshold at 32. Conversely, if your site is starting with a DR of 0, targeting domains with a DR up to 20 could be your approach.
Sidenote: it’s crucial to understand that Ahref’s domain rating operates on a logarithmic scale. This means the gap between DR 70 and DR 71 is significantly greater than that between DR 20 and DR. 21.
In other words, the competition among domains with a DR 0 and DR 20 is considerably less intense than between DR 20 and DR 40.
As for referring domains, this metric counts the unique domain backlinks to a specific page - not the entire website.
This implies that if you’re preparing a new page targeting a keyword, it’s the relative backlink efforts needed to rank the page on SERP first page.
Grab the low hanging fruit
A low hanging fruit literally refers to the fruit on lower parts of a tree that's easier to grab.
It also metaphors tasks that can be easily achieved while bringing a substantial result.
In the context of SEO, it refers to the keywords that boast high search volume yet face a minimal competition.
Before selecting keywords to prioritize, it’s essential. to have curated a list of keywords with search volume included that are relevant to your business and objectives of the SEO campaign.
The prioritization takes also the SERP first page results into account. Export the SERP data of the curated keywords.
This dataset now includes the domain rating and referring domains for each result positioned on the first page for each keyword.
With this information in hand, you can aggregate the data with Google Appscript.
Let’s consider a case where a site begins with a DR 0. I’d start by eliminating keywords that show 0 results with a DR of or less than 20.
The rationale is straightforward - the greater the number of results with a DR lower than your target, the easier it ranks on the first page.
Next, I segment the keyword list into four quartile groups based on the search volume distribution: P0, P25, P50 and P75.
Within each quartile, I further sort the keywords by their respective DR.
You should end up a categorized list that looks something like this:
- P75 to P100: high search volume group
- P50 to P75: moderately high search volume group
- P25 to P50: moderately low search volume group
- P0 to P25: low search volume group
The prioritization of keywords for targeting is then refined by considering the DR within each quartile group.
Wrapping Up
Thank for for sticking with me to the end. Again, it’s my personal methodology for prioritizing keywords. There’re way more metrics to consider to formulate a comprehensive SEO strategy. i.e. selection of topics and search intents.
Should you have any questions or comments, feel free to connect with me on X and Linkedin.
Thank you once again for your time :)