How to Steal a Competitor's SEO in 15 Minutes

and create an Effective content plan based on it.

One of the most laborious and time-consuming parts of SEO is keyword research, cleaning, and clustering keywords. This is a thorough job that is important to do well to get results. But it can be simplified by looking at those who have already done this work and done it successfully.

I mean top competitors with traffic and positions. The method I will describe below is based on the competitors' keywords.

Advantages of the method:

• Speed — It takes up to 30 minutes
• Effective clustering — the method groups keywords that are already ranked on the same URL
• Selecting high-potential phrases — The result will be a list of clusters with the frequency and keywords difficulty

Step 1 - export competitor data

Download the data on search queries of the competitor's website.

?I personally use Serpstat, but you can use any similar service such as Ahrefs or Semrush.

The data we need include:

• Key phrase
• URL in the search results
• URL position by keyword
• Frequency of the phrase
• Keyword difficulty

We are only interested in the most relevant keyword phrases, so add a filter by position from 1 to 15 and frequency from 10.

Step 2 - Enhance the table data

We need to add some items for convenience when creating a pivot table.

1. Extract the last folder from the URL and use it as the name for the future cluster name.

This can be done in Google Spreadsheets using the formula

=IFERROR(IFERROR(TRIM(REGEXEXTRACT(M2, "([^/]+)/$")), TRIM(REGEXEXTRACT(M2, "([^/]+)$"))), "")

*Where M2 is the cell with your URL.

2. Change the "Keyword difficulty" values from 0 and N/A to 0.1.

This ensures accurate calculations in the subsequent steps.

Step 3 - Create a pivot table

Build a pivot table to form the foundation of your content plan.

Set the following parameters:

Rows:

• Cluster (Order=descending, Sort by=Sum of Volume)
• Keywords.

Values:

• Keywords (COUNTA)
• Volume (SUM)
• Keyword difficulty(Median or Average)

For ease of use, you can choose to hide the data within the clusters.

Step 4 - analyze and filter

Now that we have the necessary data, we can analyze and select clusters for our content plan based on the following criteria:

• Clustered semantics derived from SERPs and competitor URLs
• Total cluster frequency based on already ranking keywords
• Number of keywords in each cluster based on current rankings
• Median difficulty level of keywords within the cluster (average for all keywords in the group)

In most cases, we are interested in clusters that will deliver meaningful results more easily. Therefore, we select them according to the criteria that are important to us.

For example:

• The median keyword difficulty of the cluster is less than 10
• The total frequency of the cluster is more than 200
• The number of key phrases in the cluster is more than 3

Result:

As a result, we get already clustered keywords based on the SERP that can be ranked on 1 URL and a total frequency that is worthy of attention.

Each cluster can be used as a basis for creating a content brief for creating a page and writing text. ?Each cluster represents one page or article within your content plan.

In my example, there are more than 300 clusters remaining on the list.

It`s not bad for a content plan created in just 15 minutes. Isn't it?

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