Applying keyword density to your search engine optimization strategy



In marketing, you must seize your opportunities, which sometimes requires a flying leap. The shifts in consumer behavior brought about by the pandemic are encouraging this leap in search engine optimization (SEO) today. As a marketer, you now have two years of pandemic-influenced search behavior online. That means you should update your keyword strategy in online content… now!

In doing so, some measurement techniques will experience a new order in the pantheon of marketing analytics. Keyword density is a proven audit of how often a keyword appears on a page. Now, more sophisticated tools are raising the question of whether keyword density is a real value for a business strategy. This post will answer that by looking at the pros and cons of this value and how you should re-imagine density analysis for an SEO strategy.

Viewing keywords in SEO history

Keyword analysis is a long-established tactic for planning the right word association that links online searches from potential customers to website or app pages that answer those queries. Marketers use SEO to manage this connection by measuring keyword density and examining word placement on a website page. Achieving 1% to 2% keyword density was a guarantee that a website page would attract an intended audience using that keyword in a search query.

Fast forward to 2022. In the shadow of search engines’ gradual algorithmic refinement to incorporate more natural language usage, SEO strategists must now consider more dynamic associations linking pages to search engine results. To address this need, advanced SEO tools have introduced ways to draw more nuanced inferences from keyword density metrics. For example, Yoast introduced a derived metric called Keyphrase Density. A key phrase consists of two or three words that are close together, such as B. hot apple cider. The phrase is intended to reflect words that are naturally used in a conversation.

Advances in search and website design have reduced the analytical value of reporting on individual SEO metrics over time. A single metric can indicate behavior, but analysts need to connect that information to a larger picture of online customer behavior. That’s 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 the ratio of word usage on a given page. Today’s marketers examine multiple pages to get an idea of ​​a website’s search performance.

Marketers create more content and drive more page builds. As a result, their content is subject to potential keyword cannibalism, the potential for pages to compete with each other for search traffic from a specific keyword. You need tactics with the metrics that can help explain the rationale for a choice of words, rather than an audit. Why words are chosen and how they fit into the design of your page content makes your pages discoverable for search queries.

Related article: How to improve SEO with keyword mapping

The ability to revitalize keywords and SEO metrics

The impact of COVID-19 presents an opportunity to revive the value of keyword density in a meaningful strategy. The pandemic has reconsidered how people search for information, such as B. Problems in the supply chain that have created a backlog of demand for products and services.

As a result, people are researching potential future purchases more often than they would otherwise “normally”, which creates more opportunities for your online content to inform future customers who are coming to your business to discuss a purchase. Search Engine Journal pointed out that search interest has skyrocketed during the pandemic, leading to greater interest in revamping and updating content from companies looking to stay relevant to new search behaviors.

If you’re responsible for your website’s SEO, you now have the opportunity to examine two years of search behavior to examine past search trends for shifts in keyword usage or the introduction of new phrases. The changed behavior determines the choice of keywords and supporting tactics for your SEO strategy.

Related article: 7 Tips for Choosing the Right SEO Agency

Choosing keywords for a post-pandemic customer experience

So what do you do to make good decisions? You start by comparing the keywords in your content to current search trends, and then make the decision on how to update your content. Your keyword selection should address the specific needs of the target audience. What expressions do they use when spending time online? What problems do they keep mentioning?

You then examine which keyword queries are driving people to your pages. These can show which 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 drew people to your website page and signal what isn’t attracting interest.


A downside of Google Search Console is that you can get itemized variations of a phrase in the reports. Some words and phrases appear repeatedly but are treated separately. For example, in one of the older posts on the Zimana site blog, the phrase JavaScript appears repeatedly in various forms of the phrase “What is a JavaScript heap?” This variant can cause additional work related to an essentially common query.

keyword density

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

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

In the examples below, I’ve created a few lines to count the number of occurrences of the keyword “Analytics” in the reported pages, and additional code to show a pattern.

number of consoles

console sum

Creating a keyword map

Of course, overuse of a keyword on a website page remains a big red flag. Search engines consider very high Keyword Density percentages as keyword stuffing, the excessive use of a phrase in blog articles or on pages. Most marketers know that.

Ultimately, you should use keyword density to identify the use of your target keywords on a given page and compare the results to words people are using in their searches. You can also use it to compare pages that use the same keywords and then create a keyword map to determine your best content and metadata tweaks. 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 the word count across multiple pages within a given document. Most early examples show how to measure the frequency of a word in 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 text. In fact, TF-IDF is the basis for semantic search in search engine algorithms. TF-IDF can be a great technique to understand not only keyword frequency but also the semantics of its usage.

How you speak to your customers with your content is paramount. Making good decisions based on keywords that combine metrics like keyword density with a larger SEO strategy may feel like a small start, but it’s a very smart start for measuring search… the beginning of a customer experience journey .


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