The concept of TF-IDF may be new to some, but Text Tools has taken this advanced, algorithmic SEO technique and made it accessible to beginner content creators. With Text Tools, the technical mumbo jumbo is taken care of for you, and you get easy to read data – delivered.

 

TF-IDF is an easy enough concept to get your brain around, so let’s get down to the basics before we break down exactly how this software works. Here’s what it stands for:

 

Term
Frequency

Infrequent
Term
Frequency

 

Basically, what this means is that TF-IDF will take your chosen keyword and compare it to the rest of the terms in your document, generally ignoring irrelevant stop words like ‘the’, ‘of’, ‘it’, etc.. From there, you get a generated list of words that are semantically related to the word you entered – in a nutshell, words that might come up in topics related to your subject.

 

What this information gives you is a jumping off point to maximize the reach of your content by drawing in a wider range of subtopics, and a larger audience as a result. Many content strategists caution about ‘niching down’ too much, and Text Tools helps you avoid that by providing you with a wider variety of target keywords.

 

As a result, your content covers more ground, and you get more traffic from a wider audience to your posts and pages.

 

Aside from just enriching the content you’re already putting together, Text Tools is a great way to dream up new blog post ideas. Take that list of semantically related keywords, and use it to put together a rich content calendar that produces posts your audience wants to read.

 

Let’s take a look at a breakdown of exactly what using Text Tools looks like.

 

First, we start over here on the ‘TF-IDF’ tool under ‘Semantic Analysis’. Let’s use the term ‘content’ and see what Text Tools comes back with.

 

TF-IDF semantic keyword analysis

 

Hooray, our request went through! Now we wait for the email to arrive with our results.

 

TF-IDF semantic keyword analysis results

 

Within about three minutes, I have an email confirming that my report is ready. I click on the link, and get this big chart.

 

TF-IDF semantic keyword analysis graph

 

Along the x-axis, we have our list of semantically related keywords. Let’s zoom in on those and take a look. At the top of the chart, I move the little bar to show 20 terms at a time.

 

TF-IDF semantic keyword analysis graph

 

Ah, that’s better! Now we can see the top 20 semantically related keywords  to ‘content’. ‘2017’ is first in the lineup, followed by ‘privacy’, ‘contact’, ‘terms’, and so on. These terms are listed in the order of their relevance, with the y-axis giving us the terms’ actual TF-IDF weighted value.

 

Below the chart, we have our color key that coordinates links with the terms in the chart.

 

TF-IDF semantic keyword analysis graph

 

These are our competitors, and this is what they’re content is also covering that we should be thinking about adding to our own. If we hover over one of those links, Text Tools kindly highlights the line in the chart for us, so we can get a clear picture of the data we’re working with.

 

TF-IDF semantic keyword analysis graph

 

Lastly, if we’re to get an idea of how we can outrank our competition and cover the ground they’re missing, we need to utilize Text Tools in one other way. Let’s hover over one of the spikes in this graph and see what happens.

 

TF-IDF semantic keyword analysis graph

 

You can see here that when we hover over ‘events’ in this graph, we get a little list of URLs that pops up. On the left of that list in bold, we have a number that represents the weight of the term ‘events’, or the term’s TF-IDF (it’s all coming together now, huh?).

 

With this information, we can see that Dictionary.com has no mention of ‘events’ in their top-ranking page for ‘content’, but that Content Marketing World scored pretty well with it. All the same, a TF-IDF weight of around 2 isn’t very high, so these pages aren’t doing particularly well for this keyword.

 

More information than you need? The next cool thing you can do with this information is reduce it down to the bare essentials. Just go into the list of URLs in the color-coded section under the graph, and click on any that you don’t want to show up in your chart. You can hide them and make them reappear at will, cleaning up the data and making it easier to sort through.

 

Now let’s take a look at a different set of data. At the top of the graph, let’s click on the tab that says ‘Compare’.

 

At the bottom of that chart, there’s an area to either paste your own text, or enter a page URL to analyze the text and determine how effective your keyword usage is. This is a great way to make sure you’re not keyword stuffing, but still using enough of your target keywords to reach your audience.

 

 

Use the color coded key at the bottom of the graph to analyze your new data.

 

TF-IDF term comparison guide

 

As you can see from this analysis from one of my blog posts at my professional services site, most of these keywords fall right within the average range, with some creeping into the max range.

 

TF-IDF semantic keyword analysis comparison

 

At the bottom of the screen below the text box, we have this list of suggested keywords to help me optimize my content even further to help this page rank higher.

 

TF-IDF semantic keyword analysis comparison

 

Lastly, we have the ‘Data’ tab, where we can download the information we’ve gathered from Text Tools into neat files to send and share with collaborators. You’ll get a comprehensive list of the term data you’ve gleaned in a nice spreadsheet that you can revisit offline.

 

TF-IDF Suggest Terms

 

The ‘Suggest Terms’ tool is reminiscent of Google’s Keyword Planner, but without as much aggregated data. This simple tool takes your primary keyword and generates a list of semantically related keywords for you to sort through.

 

TF-IDF keyword suggestions

 

From there, you can dig even deeper into your results, and get TF-IDF reports on the terms, or look into even more keyword suggestions for the list the software generates for you.

 

It may sound really technical – it is, after all, computer science – but TF-IDF is made simple with Text Tools. This program uses a user-friendly interface to bridge the gap between this type of technical SEO and the content creator, giving you the ability to do in-depth research with an easy to use tool.

 

Text Tools breaks down the data for you, and gives you the pertinent information first. Use it to refine existing content, round out your editorial calendar, or strategically try to top your competitor’s rankings.

 

Whatever your endgame, Text Tools gives you the information you need to make it happen, and is a fantastic tool for ensuring you’re not overdoing it with keyword stuffing and blatant placement. These in-depth analyses will give you the insights you need to help you stay five steps ahead of the competition.

 

You don’t need to fight dirty to dominate the SERPs – get Text Tools now to create content that conquers all on its own.