Cluster Search Console queries in Google Data Studio

Google Data Studio visualization Query Clustering

Cluster Search Console queries in Google Data Studio

In the previous post, we saw how to split and track the evolution of brand and non brand queries in Google Data Studio.

Today I’d like to follow that path a little more, showing you another slicing technique I like to use in Data Studio: clustering queries.

Clusering Google Search Console queries it’s useful for tracking how searches evolved in time, and what results you reached with your SEO activity.

How to set up the dashboard

As previously seen, let’s start by importing a Site Impression Table, and the Web Property Parameter of the Site we’re working on.

Then, let’s create a custom dimension and some code to start our clustering process, like:

CASE
  WHEN REGEXP_MATCH(Query,".*(term_1|term_2|term_3).*") THEN "Cluster 1"
  WHEN REGEXP_MATCH(Query,".*(term_1|term_2|term_3).*") THEN "Cluster 2"
  WHEN REGEXP_MATCH(Query,".*(term_1|term_2|term_3).*") THEN "Cluster 3"
  WHEN REGEXP_MATCH(Query,".*(term_1|term_2|term_3).*") THEN "Cluster 4"
  ELSE "Else"
END

An important note here: you are limited to a maximum of 40 cluster here.

Set up the visualization in Google Data Studio

So we finally get at the moment of the visualization.

I like to set up a time series chart (2) here, to show how a particular cluster evolved; and two different tables. Pay attention to set correctly Dimension and Breakdown Dimension here: Dimension is Date, instead Breakdown Dimension is your custom dimension, in my case Cluster Queries (1).

A smaller one (3) where you have all the clusters and the “Else” field, so you can see how much every single cluster impact on the whole traffic, and how much every cluster impact in your clusterization.

BTW, pay attention here, because Google Search Console samples data, so numbers with and without filters won’t never match.

Finally, a larger table (4) group both Query and your custom dimension to show what key is falling into what bucket, and it’s evolution in time if you set a comparison timeframe. I haven’t set in in the report in the screenshot, but I definitely encorage you to do so.