How to connect Google search console to Google analytics 4
Log in to GA4, hover over the left column, and click on Admin.
Then after the user account and properties appear, select the property that you want to link to GSC.
Scroll down and under the Product link and click on Search Console Links.
Click Link in the new dashboard panel.
The link setup consists of 3 steps:
Step 1 is to click Choose accounts and select the GSC account you want to link to GA4. Click Confirm and then Next.
Step 2 is to select the Web stream to which the GSC will be connected. Click Select and select the desired data stream, then click Choose. Once selected, click Next.
Step 3 is to click on Submit and that’s it.
No matter when you connect them, all GSC data will be displayed in GA4.
Accessing the GSC data in GA4
- To access the data, you need to hover over the left column and click on Reports – Acquisition – Acquisition Overview.
- Look for the Google organic search traffic tab and at the bottom click on View Google organic traffic acquisition.
Organic performance data will be displayed in the form of 3 widgets:
- a line chart (left column),
- Scatter plot (right column),
- and a table (at the bottom)
The landing page will be displayed as the main dimension, but you can also choose between the country and the type of device. Depending on what you click on the table, the data in the other two widgets will also be updated.
How to use and read the data?
Let’s say we want to compare the site’s performance over the last two weeks with the previous period.
In the upper right corner, we can click on the date range.
The advice is for the end date to be the one that has the final data (not fresh data that can be changed later), and that will usually be one or two days back. The GSC needs some time to process the data, so it is best to follow this procedure.
After selecting the date range, click Compare and then Apply.
Line chart
A line chart will update accordingly and then you can get a quick glimpse of the organic performance and compare the current period with the previous one.
In this particular case, we see that when it comes to organic clicks the first 5 days differ from the 5 days of the previous period. The other days are almost the same. We can continue researching what happened in the first two days that traffic dropped. But that’s a topic for another post.
What is important to remember is that you need to spot irregularities that can be further investigated.
Scatter plot
The Scatter plot shows the correlation between impressions (Y) and clicks (X). It’s important to take a look at the graph as a whole as well as pay attention to the dots that stand out.
It provides quick and excellent insight into valuable information.
We see that this scatter plot has a very loose and kind of scattered growth, which is to be expected due to the very nature of impressions and clicks. What is important to note is that the scatter plot serves to quickly obtain some practically represented general information that needs to be studied in detail afterward.
In the case below, we will explain what we can conclude from the position of points A, B, and C.
Point A
The higher the point on the graph, the more untapped potential there is. The data itself says that it has close to 60k impressions, but only 4k clicks, which gives it an approximately 15% clickthrough rate.
When we know the clickthrough rate, it is easy to conclude that the average position for all search queries on Google is approximately between 3rd and 5th place. We can also check the table below for actual data. With that in mind, we could further adjust the strategy in a variety of ways to have even more clicks.
Point B
This is an example of an almost ideal position of a point on the scatter plot of impressions and clicks. Unlike point A, point B has much fewer impressions but more clicks.
About 18k impressions and 5.5k clicks mean that the clickthrough rate is about 30%. This tells us that the average position of this site for all search queries varies from 1st to 3rd place.
Given the above information, we could take a closer look at the table below or at the positions of the page for certain search queries in the GSC itself so that we could make it perform even better.
However, taking into account the overall graph, we should primarily focus on points A and C instead.
Point C
Point C is in a very unusual position. It has a lot of impressions and very few clicks, which means that her average position for all search queries is most likely between 5 and 10.
Conclusion
We should address point C first, then point A, and finally, point B. This would be a logical order given the untapped opportunities and potential.
A table
The table consists of several different columns. The main dimension is the landing page, but, as we have already said, the country or device category can also be selected. Unlike the line chart and scatter plot, here we see concrete figures.
In the Totals row, we can see the change expressed in percentages and colored in red or green.
Furthermore, we can see the statistics for each individual page. We have insight into some other metrics besides impressions and clicks: CTR, average position, users, engaged sessions, engagement rate, etc.
Taking everything into account
A conclusion based on the analysis of the line chart and row totals is that the current situation is fine and under control, regardless of the fact that the table shows that:
- Impressions decreased by 8.73%,
- Users decreased by 3.9%
- Clicks decreased by 0.9%.
If you remember – in the line chart we came to the information that the first 5 days were somewhat different. In this case, Labor Day or Workers’ Day (1st of May) has influenced the statistics, in many different ways.
Always keep in mind seasonal changes and dates as they can affect the statistics.
What we learned more is, in fact, great information:
- Organic CTR increased by 8.58%,
- Avg position increased by 3.8%
- Avg engagement time increased by 18.51%
The reason for this is that a few days before the first period, we published a redesigned version of the web in order to further customize it for users.
The increase in avg engagement time of 18.51% is an excellent result. Although we have not measured exactly from the date when the web was redesigned, so the new web data is partly included in the previous period.
Conclusion
Statistics is a very interesting thing and can sometimes feel overwhelming. You can easily get lost in it if you don’t look for the right things and lay the right foundations. It is always important to know what information you are looking for, and then use statistics as a tool.
I hope you found this real-life example interesting and that you learned something from it.
