Explicit Keyword Research Using Google Search Console
Posted: Wed Dec 18, 2024 3:34 am
I've covered this process before in my section On-Page Strategies for Local SEO: Ranking in Multiple Cities , but we'll go over it again using our new topic.
To make this process as seamless as possible, we’ll be using Search Analytics for Sheets to pull data from Google Search Console.
Install the add-on in the same Google denmark whatsapp number Account that you use to sign in to the Search Console you want to export data from.
From the spreadsheet where you uploaded the Semrush export, create a new spreadsheet.
From the menu, click on Add-ons and you will see "Search Analytics for Sheets".
Hover over it and click "Open Sidebar".
We will configure it to only insert queries that match our argument.
As a Date Range, I prefer to extract 12 months of data.
Search type: Leave it as is
Group by: query, page
Filter by: tankless (we want the widest selection possible)
The rest of the fields should remain unchanged.
Results Sheet: Make sure you select your new sheet to enter data here.
Request data.
Once the data has been compiled, we now have the fun task of sorting it and starting to dive a little deeper into the topic.
I removed CTR and Position and sorted the export by impressions. I also added a new column and called it "Avg MSV" (average monthly search volume) with a formula that divides by 12:
img-semblog
An important note about our "Avg MSV" from Google Search Console: this number is the impressions this property has received over the previous 12 months. This is not a unique representation of the true average monthly search volume for these queries.
My export had a total of 512 queries. Which could be grouped into just a couple of categories. I added a column to the spreadsheet and called it "Categories". I then started adding categories to the first 30 queries in the sheet and sorted the categories.
img-semblog
Categories will potentially be unique pages that relate to our main topic, condensing boilers.
Going through 500+ queries to capture all the possible keywords is very time consuming. You can analyze all the queries, but at some point you will notice that they are very similar to others you have already classified (tankless boiler vs tank; tank vs tankless boiler).
We are quite satisfied with the work done on our topic, but we still have some steps to complete before defining a content plan.
To make this process as seamless as possible, we’ll be using Search Analytics for Sheets to pull data from Google Search Console.
Install the add-on in the same Google denmark whatsapp number Account that you use to sign in to the Search Console you want to export data from.
From the spreadsheet where you uploaded the Semrush export, create a new spreadsheet.
From the menu, click on Add-ons and you will see "Search Analytics for Sheets".
Hover over it and click "Open Sidebar".
We will configure it to only insert queries that match our argument.
As a Date Range, I prefer to extract 12 months of data.
Search type: Leave it as is
Group by: query, page
Filter by: tankless (we want the widest selection possible)
The rest of the fields should remain unchanged.
Results Sheet: Make sure you select your new sheet to enter data here.
Request data.
Once the data has been compiled, we now have the fun task of sorting it and starting to dive a little deeper into the topic.
I removed CTR and Position and sorted the export by impressions. I also added a new column and called it "Avg MSV" (average monthly search volume) with a formula that divides by 12:
img-semblog
An important note about our "Avg MSV" from Google Search Console: this number is the impressions this property has received over the previous 12 months. This is not a unique representation of the true average monthly search volume for these queries.
My export had a total of 512 queries. Which could be grouped into just a couple of categories. I added a column to the spreadsheet and called it "Categories". I then started adding categories to the first 30 queries in the sheet and sorted the categories.
img-semblog
Categories will potentially be unique pages that relate to our main topic, condensing boilers.
Going through 500+ queries to capture all the possible keywords is very time consuming. You can analyze all the queries, but at some point you will notice that they are very similar to others you have already classified (tankless boiler vs tank; tank vs tankless boiler).
We are quite satisfied with the work done on our topic, but we still have some steps to complete before defining a content plan.