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How to Use Keyword Density in a Modern SEO Strategy

7 minute read
Pierre DeBois avatar
In marketing you must jump at your opportunities, sometimes requiring a flying leap.

In marketing you must jump at your opportunities, sometimes requiring a flying leap. Consumer behavior changes from the pandemic are encouraging that leap in search engine optimization (SEO) terms today. As a marketer, you now have two years of pandemic-influenced search behavior online. That means you should be updating your keyword strategy in online content...now!

In doing so, you will find some measuring techniques faces a new order in the pantheon of marketing analytics. Keyword density is a tried-and-true audit of how frequent a keyword appears on a page. Now more sophisticated tools raise the question if keyword density is a true value to a business strategy. This post will answer that, looking at the pros and cons of that value and how you should re-imagine density analysis for an SEO strategy.

The View of Keywords in SEO History

Keyword analysis is a long-standing tactic for planning the right word association that links online search queries from potential customers to website or app pages that answer those queries. Marketers use SEO to manage that connection through measuring keyword density and examine word placement within a website page. Achieving a keyword density of 1% to 2% was insurance that a website page would attract an intended audience who used that keyword in a search query.

Fast forward to 2022. Under a shadow of gradual algorithmic refinements to search engines to incorporate more natural speech usage, SEO strategists now must account for more dynamic associations that link pages to search engine results. To meet that need, advanced SEO tools introduced ways to draw more sophisticated conclusions from keyword density metrics. For example, Yoast introduced a derivative metric, keyphrase density. A keyphrase is two or three closely aligned words, such as hot apple cider. The phrase is meant to reflect words used naturally in a conversation.

Advances in search and website design have lessened the analysis value of reporting on singular SEO metrics over time. A single metric may be indicative of a behavior, but analysts must link that information to a larger picture of online customer behavior. It's the reason why the value of some metrics, like bounce rate, which I covered in a previous post, are considered less valuable or unnecessary.   

So, while keyword density continues to be a valuable metric for an SEO strategy, it only explains a ratio of word usage on a given page. These days marketers are cross-examining multiple pages to get a picture of a website's search performance. 

Marketers are making more content, driving more page creation. Consequently, their content faces potential keyword cannibalism, the potential for pages to compete against each other for search query traffic from a given keyword. They need tactics with the metrics that can help explain the reasoning of a word choice rather than an audit. Why words are chosen and how they fit into the design of your page content is what makes your pages discoverable to search queries.

Related Article: How to Improve SEO Through Keyword Mapping

The Opportunity to Revitalize Keywords and SEO Metrics

The influence of COVID-19 brings an opportunity to revitalize the value of keyword density into a meaningful strategy. The pandemic has introduced new considerations for how people search for information, such as supply-chain issues which have triggered pent-up demand for products and services.

As a result, people are researching potential future purchases more frequently than the "old normal," bringing more opportunities for your online content to educate future customers who will come to your firm to discuss a purchase. Search Engine Journal indicated that search interest spiked during the pandemic, driving higher interest in revising and updating content among companies looking to remain relevant to the new search behaviors.

If you are responsible for SEO of your site, you now have an opportunity to examine two years of search behavior to examine past search trends for shifts in keyword usage or introduction of new phrases. The changed behavior will determine the choice of keywords and supporting tactics for your SEO strategy.

Related Article: 7 Tips for Selecting the Right SEO Agency

Selecting Keywords for a Post-Pandemic Customer Experience

So, what do you do to make good choices? You start with comparing the keywords in your content to recent search trends and then make the decision of how to update your content. Your keyword choices should speak to the audience's specific needs. What phrases do they use while spending time online? What problems do they constantly mention?

You then examine what keyword queries are drawing people to your pages. These can reveal what pages should be checked for keyword density.

For example, in the performance report in Google Search Console, you can filter clicks and impressions for each page by keyword. This can give an overview of what has been drawing people to your website page and signal what is not receiving interest.

performance

Learning Opportunities

One downside in Google Search Console is that you can receive variations of a phrase broken down in the reports. Some words and phrases appear repeatedly but are treated separately. For example, in one of the older posts in the Zimana site blog, the phrase JavaScript appears repeatedly in varying forms of the phrase "What is a JavaScript heap?" This variation can create some extra labor around what is essentially one shared query.

keyword density

A workaround for this is to import GSC data into an R programming script. You can then use the functions to examine the keyword count per pages. 

To do this you would use the SearchconsoleR library. SearchconsoleR uses the Google Search Console API to import the data into R programming. You can then apply additional libraries to sort the data.

In the below examples, I created a few lines to count the number of times the keyword "analytics" appeared on the pages reported, and another code to show a pattern.

console count

console sum

Creating a Keyword Map

Of course, using a keyword too frequently in a website page remains a huge red flag. Search engines consider very high keyword density percentages as keyword stuffing, the overuse of a phrase in blog articles or on pages. Most marketers know this.

Ultimately you should use keyword density to identify the usage of your target keywords on a given page and compare the results with words that people are using in their search. You can also use it to compare pages that are using the same keywords, then create a keyword map to decide your best content and metadata adjustments. You can learn more about keyword mapping in this post on keyword mapping

There is another more advanced keyword analysis technique called Term Frequency–Inverse Document Frequency (TF-IDF). This is essentially an algorithm that examines word count against several pages within a given document. Most early examples show how to measure the frequency of a word within a novel or nonfiction text. But thanks to APIs analysts are learning how to apply the same analysis to social media posts and other digital texts. In fact TF-IDF is the basis for semantic search in search engine algorithms. TF-IDF can be a great technique for understanding not only the keyword frequency, but the semantics of its usage.

How you speak to your customers through your content is paramount. Making good decisions from keywords that connect metrics like keyword density to a larger SEO strategy may feel like small start, but it is a very smart start for measuring search...the start of a customer experience journey.