That's where a tool like SEMrush comes in.
Before continuing, it should be noted that, to make this dashboard, it is necessary to have access to the Business plan of this tool, which is what allows us to use the API and, what we are going to do here, take advantage of its integration with Google Data Studio.
To follow the entire process, we have prepared a short educational video that I encourage you to watch below, explained in detail by Miguel Carreira, Senior SEO at Elabs Consulting.
Youtube video thumbnail
In our case, what we will do is use the “position tracking” connector to link Google Data Studio with our keyword tracking project.
In this way, we will connect with the project we have created in SEMrush and we will be able to import from there the list of keywords that we are interested in monitoring, along with their corresponding labels (an opportunity to build our “categories”, although we can do it again later with GDS) and the data that SEMrush gives us for each keyword:
CPC.
Landing page.
Position.
SERP features.
Tags.
Volume.
We will then include a second data source: Google Search Console.
When you do this keep in mind that we can connect two different GSC code phone number philippines tables: web and URL.
Specifically, we will focus on the “ Web” table because at this stage, what we are interested in is knowing the overall positioning of the page and not so much going into the detail of each of the URLs.
Next, we'll use what is perhaps one of the most underused (and most powerful) features of Google Data Studio: data blending.
In our case, we are going to use the information from Google Search Console to link it to the SEMrush position report.
We will link the two tables using the “Query” field (which appears as “Keyword” in the tool report). This will be the term we will use to link the two tables.
As we show in the video, in this example, you will notice that we are using a very simple case, because what interests us is only to describe the mechanics and steps to follow to achieve this table linking.
For other scenarios, if the goal is to be accurate when handling estimates, we will need to consider components such as “country” and “device” when comparing metrics.
This way we can get a fairly accurate estimate of the volume of searches generated around our website, what part of that volume we are reaching, and how much we still have to grow.
By doing this, you will never again have to cross-reference a Keyword Research with a click graph.
No more usual processes like: exporting Excel spreadsheets from different sources, cross-checking them, remembering that we have not changed the date period, cross-checking them again, and all this to finally be able to work with the results.