Note that we are looking at the average ranking

[israt9623525]

Below is the completed scatterplot with my example: 768x505.png Each bubble is a keyword (I removed the keyword label). On the X-axis you can see its organic position in Google from 1 to 100.


On the Y-axis you can see the number of annual impressions. I pulled in some cards from Visualizations. We ended up finding 896 keywords represented across all datasets representing 3 million annual impressions and 106,000 clicks. This is already interesting, but here's where things get interesting.


Now drag Revenue from the GA 12m self employed phone number list dataset into the Size field (select the minimum). Boom! Now we can see which search queries have given us the most revenue in Google Ads over the last 12 months.


However, please over the last 12 months. The average ranking could be very different from the current one. Therefore, we need to combine the two datasets with the latest GSC ranking dataset to get the current ranking.


Go to Relationship Manager and create the connection between the two GSC datasets. When finished, insert the GSC ranking position as the X-axis. Now you have the most important search queries Now you are ready to do a deep dive and find the most interesting keywords to work on.