Get the most out of Google Data Studio in 7 steps

Data Studio is one more example of how, from the Mountain View company, they tend to overtake the rest of the world. And for better or worse, they have democratized the possibility to visualize and analyze data to make more decisions in the company.

Google Data Studio was launched in the early 2016, Within The Google Analytics Suite 360, and is a free tool that allows you to create quite complete graphics from multiple data sources.

Like many other Google tools, it has some limitations (lack of personalization, sometimes performance, no official support...), but it is a very valid alternative for the aforementioned tasks.

To analyze the data we will need to link or create one or more data sources and for this the data Studio offers Connectors for AdWords, Google Analytics, Google Sheets, BigQuery, Search Console, among others. But there are also community connectors that allow you to use data from other vendors as input.

 Data Studio Connectors

There is also a Data Studio User Community, where you can look for unresolved doubts or propose new topics to get help.

Google Data Studio Reports Example

Here are 2 sample reports from templates available when creating a new dashboard.

First, for PPC campaigns of an ecommerce:

PPC Data Studio Example

And second, for specific AdWords campaigns:

Example AdWords Data Studio

Get the most out of Google Data Studio in 7 steps

1. Creating Data Studio Pages

I Have seen many reports in which all the information is shown on a single page. This may be enough for reports where there is little data. But for cases where we have a larger number of graphics, it is more efficient to work at the page level, showing in each a different country, a different product line or any other separation that we can think of.

Creating Data Studio Pages

2. Date Selector

Once we have the pages created, we should add a date selector to our report so we can choose the time period that we want to analyze in a more agile way.

Data Studio Date Selector

3. Control Filters

By Means of the control filters we will be able to choose dimensions to act as a filter in our reports. For example, if we are analyzing AdWords campaigns, we could add a filter for the device dimension and thus have a drop-down to show data of mobile, desktop and/or tablet, as we are interested.

Data Studio Control Filters

4. Report Level

If we are working with reports from more than one page, another very useful option is to right-click on the date selector and mark it at report level. Thus, we will have this widget in common for all the pages, without having to add it manually in each one of the pages. This also applies to graphics and other widgets.

Data Studio Report Level

5. Filters in Google Data Studio

Another possibility, one of the most profitable Of Google Data Studio, is the option to filter with which we will include or exclude dimensions or metrics fulfilling one or several conditions. For example, for a specific graphic we can choose to show us only data of the Campaigns that contain "bicycles".

Data Studio Filters 2 Data Studio Filters

6. Custom Metrics in Data Studio

When choosing a certain metric for a chart we also have the possibility to create a new one.

Personal Data Studio Metric

Within an analysis of AdWords campaigns, we could create, for example, a new metric Called necessary clicks, result of Splitting clicks between conversions. And so we would have a new metric with the average value of clicks needed to get a conversion.

2 Data Studio Custom Metric

7. Custom Dimensions in Google Data Studio

With behavior analogous to custom metrics, we can use custom dimensions to create new variables, this time with aggregation functions. Here is a list of the Functions recognized by Google.

For example, we could create a custom dimension to display differentiated metrics depending on weekdays or weekends:

Data Studio Custom Dimension

And you, do you use Google Data Studio? What use do you give? Do you Know any tricks to better analyze the campaigns?

Written by

Joan Buigues

ANALYTICS · 20/02/2018

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