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Keyword Density Case Study

I hear a lot of SEO blogs saying that keyword density should be around 1% to 3%, but many of them, at least the ones I’ve seen, do not provide data to prove this.

I for one do not like to take things at face value, so to see if this is accurate or not, I created a small study to see if it is.

For the sake of your time, I found that the rule is somewhat accurate, but I do think it is worth reading the results to gain some insights on why it is not a hard and fast rule.

Here’s the study I set up:

Procedures

  1. I took 20 web pages in the financing/loan niche that rank on page 1 for their main keyword.
  2. I then used a tool to find the word count of each page.
  3. I then counted the number of occurrences of the main keyword on each page.
  4. I next divided the total word count by the number of occurrences to find the keyword density.
  5. Lastly, I recorded the data in a spreadsheet.

Here’s a screenshot of my spreadsheet:

spreadsheet of keyword density study, Raj clark

Okay now let’s see what I found:

Data 

Here’s a chart showing the word count for each webpage.

Chart showing the word count

Here’s a chart showing the keyword occurrences.

Chart showing the keyword occurances

And this chart shows the keyword density for each webpage.

Chart showing the keyword densities

Analysis

As you can see in the data, most of the websites had a density of about 0.5 – 1%

With some web pages like “Cosmetic” and “Surrogacy surgery” financing almost having a 0% keyword density despite having a small word count. 

While web pages like “garbage” and “plumbing” financing had high word counts but still low keyword densities.

I think this is fascinating because this really shows that there is no set rule. 

As long as the content makes sense, is relevant and actually is helpful, it can rank regardless of how many “main keywords” it has.

Again, this backs up what we are seeing with Google’s new Helpful content algorithm update where they are prioritizing content that is written for humans and not search engines.

Questions about the data’s validity

Here are some questions/thoughts that you may have about the accuracy of the data:

Why did you choose that niche?

You might be wondering why I chose the financing/loan niche over others. 

I chose this niche because of its popularity and I knew I’d be able to find a lot of main keyword variations with close to the same intent.

I believed that it would keep my data my uniform because using too many different niches may skew the data because they may have vastly different word counts, intents or keyword counts.

Are the word counts accurate?

One thing to note about the word count tool was that it is somewhat accurate because it does take note of words that are not technically part of the webpage. 

Like navigations, footers, side bars, or ads.

I also had to use several because all of them did not return a good data point, or data at all. 

Also some of the tools had vastly different word counts so I chose the one that best matched the data.

Here’s the tools I used, please note; I am not affiliate with any of them

  • SEOptimer Website Word Count Tool
  • Word Counter: Web Page Word Counter
  • The Hoth: Word Count Tool

How did you determine the webpage’s main keyword?

To determine what the webpages’ main keyword was I looked at their Title Tag, Meta ​description, and H1.

If the keyword appeared in all three places I determined that the webpage was more than likely trying to rank for that keyword specifically.

Conclusion

As you can see from the data, there is no hard and fast rule when it comes to deciding on the right amount of keywords to use on a website.

It is more about writing content that your audience is searching for, providing them with that content and then just using the keywords to help them find it.

In other words, just because you use a lot of keywords does not mean you will rank higher.

If you found my study helpful, consider sharing it around. Also check out my post on keyword stuffing on how to fix your content if your density is too high.

So long!

 

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