You have a bulky list of 1000+ keywords; the next step is to turn this list into something useful.

We start with term analysis. What the does that mean?

We separate each keyword into distinct component words that include that keyword so that we can see which words are most common.

Take an example of the keyword “best natural protein powder” it has 4 words best, natural, protein, and powder. By separating these keywords into their components part we will be able to analyze more easily that which terms are being used commonly in our keyword dataset.

Sampling of 3 keywords:

• best natural protein powder
• how to make natural deodorant
• most powerful natural anti inflammatory

By looking at the above sampling you will notice that the term natural is common in al three of these keywords. If this term is common throughout our long list of keywords, it will be highly important when we start clustering our keywords

To make this task easy you need a frequency counter. The best tool for this is  Write Words’ Word Frequency Counter.

It is really simple; you just have to paste your list of keywords and click submit, and Voila!

Ignore the preposition terms like “to”, “For” and “is” and copy and paste your list terms into a sheet.

You won’t always get the most value just by looking at individual words. Sometimes a phrase of two or three words gives you an understanding of what would not otherwise be. In this example, you see the words milk and almonds, but you find that this is actually part of the phrase almond milk.

To collect this information, use the Phrase Frequency Counter from WriteWords and repeat the process for phrases that have two, three, four and more terms in them. Paste all of this data into your spreadsheet too.

A two-word phrase that is more common than a one-word phrase indicates its importance. To calculate this, I use the COUNTA function in Google Sheets to show the number of words in a phrase:

=COUNTA(SPLIT(B2,” “))

Now we can look at the data of our keyword from another dimension: not only the number of words or phrases, but also the number of words in this phrase.

Finally, in order to give more weight to phrases that are repeated less often, but contain more words, I put the exponent of the number of words using the basic formula:

=(C4^2)*A4

In other words, take the number of words and raise it to a power, and then multiply by the frequency of its occurrence. All this gives more weight to the fact that a two-word phrase, which is less common, is still more important than a one-word phrase, which can be more common.

Since I don’t know how to properly raise it, I conduct several tests and continue to sort through the sheet to find the most important words and phrases on the sheet.

When you see this now, you can already begin to see the patterns, and you are already able to better understand your researchers.

In this sample dataset, we go through a list of 10,000+ keywords to understand what people are actually asking. For example, the phrases “what is the best” and “where can i buy” are phrases that we can fully understand.

I mark important words or phrases. I try to keep this number below 50 and to a maximum of around 75 otherwise, grouping will get risky in Part 5.