[MUSIC PLAYING]
KRISTA SEIDEN: Hey, everyone.
I'm Krista Seiden.
And I'm here today with Stefano, who is a Product
Manager on Google Analytics.
And he is going to show us an overview of using analysis
in Google Analytics 4 Properties.
Now this is super exciting, because analysis was available
in Universal Analytics but only for 360 customers.
But in Google Analytics 4, it's available for everybody.
So with that, Stefano, thank you so much for being
here, and over to you.
STEFANO MENTI: Thank you, Krista.
Hi, everyone.
So first of all, why should you care about analysis?
Analysis is one of the modules within Google Analytics
4 property where on one side, you
have all the prepared reports within the reporting
curriculum in GA4.
That allows you to answer the most common question that you
have about your GA data.
On the other side, if you are an expert to sqlninja,
you will have tools like pQuery, where you can export your data
and run all other queries that you want on your Google
Analytics data.
Right in between, you have analysis.
It's a module within Google Analytics that gives you
the power of a series of techniques with advanced data
modeling to be able to answer all
those questions within the UI of Google Analytics.
And here we are on the Google Analytics 4 user interface.
And where you can find Analysis here is on the left navigation.
If you scroll down here in the Explore section,
you will have Analysis.
Analysis, if you click there, will have the Analysis Hub
and Template Gallery.
The first Analysis Hub will include the list of techniques
that you have available in Analysis.
Each technique is a predefined data model
to better analyze your data.
And then down here, you will have
the list of all saved analysis that you've
created over time that you can reaccess at any point in time.
There are the link the template gallery will
allow you to see all the premade templates,
of course, that exist in analysis.
Each one of them will have its own template, and then
a series of use cases and industries
where we will have a specific set of prepared analysis
that are specific for those use cases.
As an example, if I click here on the acquisition use case,
it will open up an analysis with a few different techniques
that are focused on the acquisition use case.
So in this case, the first analysis
is an exploration analysis with a deep dive on your acquisition
sources.
Every analysis that you create will be automatically saved
and given a name, a default name, that you can always
come here and change.
So I can change that to a new name.
And once that's saved, you can go back to the Analysis Hub
and see the analysis we have just
saved as the last in chronological order.
Within the Analysis Hub on the three dots here on the right,
you can do delete, rename the analysis.
You can create a duplicate.
You can also share the analysis.
By default, each analysis you create
is going to be private to yourself.
No one can see or edit it.
But you can share it [INAUDIBLE] with the rest of your property.
Now, let's jump into the exploration technique,
which is probably going to be one of the first techniques you
look at in analysis.
All technique will have these two panels
that you see on the left.
It will have the variable panel and the tab setting panel.
The variable panel is common across techniques
and has all the element that you need
to add to your visualization-- the name, the date
range, the ability to select segments,
dimension, and metric.
And these are the most commonly used.
But you can also always click the plus sign
and access all the available dimension and metric
that you have in your property and just
click the one that you need to see data and apply them to make
them part of the variable panel to be able to then just
double click or dragging and dropping
the metric or the dimension to make
it part of the visualization.
The second panel, the tab setting panel,
is specific for each technique.
And the exploration technique is that it
allows you to select different visualization.
So we are looking now at a table report.
You can do donut chart, line charts, scatterplot, et cetera.
You can apply segments to the data
by dragging and dropping the segment name in the segment.
Select roll, select column, select the different metric,
and finally be able to filter the data on the filter section
here where you can use whatever dimension you have applied
or metric and use that to filter and only
look at a subset of data.
The last important part that is common across technique
is that you can interact with the data.
On each data point, you can right
click and do a few action.
You could view user, create a segment,
include and exclude these specific selection
from your selection of data.
In the example segment, if you create a segment,
it opens up the segment builder with the pre-created all
the condition that defines that specific data point.
So you don't have to do this manually.
But you can manually add and make these segmentation more
customized if you want to add, for instance, a condition
to these conditions here.
KRISTA SEIDEN: Awesome, there is so much great information
there about how to use analysis in Google Analytics 4
properties.
I hope you guys can see how useful this tool might
be and start to dive in.
Stefano, thanks again.
And everybody, go make use of analysis
in Google Analytics 4 Properties.