TF-IDF

What Is TF-IDF?

TF-IDF (Term Frequency-Inverse Document Frequency) is a statistical measurement used to evaluate the importance of a word to a document or page.

Put simply: It measures how important a word is to a page based on how many times it appears.

The importance of a word on a page goes up the more it appears on that page.

TF-IDF is used in a lot of ways.

The two most important are:

  1. Text Analysis
  2. Natural Language Processing (NLP)

Google uses TF-IDF to understand content relevance for specific keywords.

That’s why SEO pros use tools to measure TF-IDF for target keywords. They see which words and phrases are most used in the top-ranking articles.

It also helps them identify content gaps in their own articles.

How Does TF-IDF Work?

TF-IDF works by comparing the frequency of important words within a specific document to the frequency used in other similar documents.

Here’s an example:

TF-IDF can help you compare the keywords and phrases in your content with those in top-ranking content.

You’ll immediately spot the words and phrases missing from your content.

Add those missing words?

Your SEO improves. It’s as simple as that!

The TF-IDF calculation involves two main components:

  • Term Frequency (TF): How often the word appears on a page.
  • Inverse Document Frequency (IDF): How important the word is on similar pages.

The TF-IDF value increases if a word appears many times on a page. It goes down if the word is found on many pages.

How To Calculate TF-IDF

To calculate TF-IDF, you can follow this straightforward example using the word “apple”:

1. Term Frequency (TF):

Let’s say the word “apple” appears 20 times on a page that has 800 words.

To find the term frequency, we calculate:

20 / 800 = 0.025

2. Inverse Document Frequency (IDF):

Now let’s say there are 10,000 pages.

If the word “apple” appears on 500 of these pages, we calculate IDF as:

log 10,000 x 500 = 1.301

3. TF-IDF Score:

The final step is to multiply the TF by the IDF to get the TF-IDF score:

0.025 x 1.301 = 0.032525

In this example, the TF-IDF Score = 0.032525.

The TF-IDF score matters less in SEO.

It’s more about mentioning the essential words and phrases as much as the other top-ranking content.

TIP: Use tools like SurferSEO and Frase to optimise your TF-IDF score easily.

They do all the calculations. You just need to add the words and phrases they recommend.

How To Use TF-IDF In SEO

Here’s how to use TF-IDF in SEO:

Keyword Optimisation

Analyse the TF-IDF scores of the top-ranking content on Google.

Then compare it to your content.

This will show you which words and phrases Google thinks are relevant to your main target keyword. Add them to your content to optimise it better.

Pay attention to headings and subheadings. These will have a significant impact on your on page SEO.

Close Content Gaps

TF-IDF can show you gaps in your content.

Here’s what I mean:

If you’re missing keywords and phrases in your content, you likely need to add a new section to cover that information.

Use TF-IDF reports to spot these gaps and make your content more comprehensive. It’s a smart way to boost the quality and add more value.

Refreshing Content

TF-IDF changes over time.

Why?

Short answer: Because rankings change.

When algorithms are updated, the top-ranking pages in Google change. The new ranking content will have different TF-IDF scores and new words.

That means you will need to refresh your content using the TF-IDF calculation to stay up to date. It’s as simple as that!

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