In marketing, you have to jump at your opportunities, which sometimes requires a quick jump. Changes in consumer behavior as a result of the pandemic are now encouraging this leap in terms of search engine optimization (SEO). As a marketer, you now have two years of pandemic-influenced online search behavior. This means you should update your online content keyword strategy…now!
In doing so, you will discover that certain measurement techniques face 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 raise the question of whether keyword density is a real value for a business strategy. This article will answer that, looking at the pros and cons of this value and how you should reimagine density analysis for an SEO strategy.
The view of keywords in SEO history
Keyword analysis is a long-standing tactic for planning the right combination of words that links potential customers’ online search queries to the pages of websites or apps that answer those queries. Marketers use SEO to manage this connection by measuring keyword density and looking at word placement within a website page. Achieving a keyword density of 1% to 2% was an assurance that a website page would attract a target audience who used that keyword in a search query.
Fast forward to 2022. Under the shadow of incremental search engine algorithmic improvements to incorporate more natural use of speech, SEO strategists must now consider the more dynamic associations that link pages to search engine results. research. To meet this need, advanced SEO tools have introduced more sophisticated ways to draw conclusions from keyword density metrics. For example, Yeast introduced a derived metric, keyphrase density. A keyphrase is two or three closely aligned words, like hot apple cider. The phrase is meant to reflect words used naturally in conversation.
Advances in research and website design have reduced the analytical value of reporting on single SEO metrics over time. A single metric can be indicative of a behavior, but analysts need to connect that information to a larger picture of customer behavior online. This is why the value of certain metrics, like bounce rate, which I covered in a previous article, are considered less valuable or useless.
So while keyword density continues to be a valuable metric for an SEO strategy, it only explains a ratio of word usage on any given page. Marketers these days look at multiple pages to get a picture of a website’s search performance.
Marketers are creating more content, leading to more page builds. As a result, their content faces potential keyword cannibalism, the ability for pages to compete for search query traffic from a given keyword. They need tactics with metrics that can help explain the reasoning behind a choice of words rather than an audit. Why words are chosen and how they fit into your page content design is what makes your pages visible to search queries.
Related Article: How to Improve SEO with Keyword Mapping
The opportunity to revitalize keywords and SEO metrics
The influence of COVID-19 provides an opportunity to revitalize the value of keyword density into meaningful strategy. The pandemic has introduced new considerations for how people search for information, such as supply chain issues that have triggered pent-up demand for products and services.
As a result, people are searching for potential future purchases more frequently than the “old normal,” giving your online content more opportunity to educate future customers who will come to your business to discuss a purchase. Search Engine Journal reported that interest in search has increased during the pandemic, driving increased interest in reviewing and updating content among companies looking to stay relevant to new search behaviors.
If you are responsible for your site’s SEO, you now have the ability to look at two years of search behavior to examine past search trends for changes in keyword usage or the introduction of new phrases. Behavior change will determine the choice of supporting keywords and tactics for your SEO strategy.
Related Article: 7 Tips for Choosing the Right SEO Agency
Keyword Selection for a Post-Pandemic Customer Experience
So what are you doing to make good choices? You start by comparing the keywords in your content to recent search trends, then you decide how to update your content. Your keyword choices should meet the specific needs of the audience. What phrases do they use when spending time online? What problems do they constantly mention?
You then look at which keyword queries are bringing people to your pages. These can reveal which pages should be checked for keyword density.
For example, in the Google Search Console performance report, you can filter clicks and impressions for each page by keyword. This can provide insight into what drew people to your web page and point out what isn’t engaging.
A workaround is to import GSC data into an R programming script. You can then use the functions to examine the number of keywords 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 examples below, I created a few lines to count the number of times the keyword “analytics” appeared on reported pages, and some other code to show a pattern.
Creating a Keyword Map
Of course, using a keyword too often in a website page is still a huge red flag. Search engines consider very high keyword density percentages to be keyword stuffing, the excessive use of a phrase in blog posts or on pages. Most traders know this.
Ultimately, you should use keyword density to identify the usage of your target keywords on any given page and compare the results with the words people are using in their search. You can also use it to compare pages that use the same keywords, then create a keyword map to decide your best content and metadata fits. You can learn more about keyword mapping in this article on keyword mapping.
There is another more advanced keyword analysis technique called Term Frequency–Inverse Document Frequency (TF-IDF). It is basically an algorithm that looks at the word count against multiple pages of a given document. Most early examples show how to measure the frequency of a word in a novel or non-fiction text. But thanks to APIs, analysts learn to apply the same analysis to social media posts and other digital texts. In fact, TF-IDF is the basis of 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 through your content is paramount. Making good keyword decisions that connect metrics like keyword density to a larger SEO strategy might seem like a small start, but it’s a very smart start to measuring search… the start of a customer experience journey.