[MUSIC PLAYING]
KRISTA SEIDEN: Hey, everyone.
I'm Kristin Seiden, and today I'm here with Anjali Raghavan.
And she's going to tell us all about the new attribution
reports in Google Analytics 4 Properties.
Anjali, over to you.
ANJALI RAGHAVAN: Thanks, Krista.
I'm so excited to be here and to speak to all of you
about attribution and Google Analytics 4 Properties.
Let's go ahead and jump in.
Attribution is the act of assigning
credit for conversions to different touchpoints
in a user's path to completing a conversion.
An attribution model can be a rule, a set of rules,
or a data-driven algorithm that determines
how credit for conversions is assigned to touch points
on conversion paths.
Google Analytics 4 offers two attribution reports today.
The conversion paths report gives you
a view of your customer's paths to conversion
and assigns credit to the touchpoints
in those journeys based on the attribution model you select.
And the model comparison report allows
you to compare campaign performance
using different attribution models
and assess how each model impacts the value
of your marketing channels.
Here you can see the models available in Google Analytics 4
Properties.
Our recommended model is cross-channel data-driven
attribution, or DDA.
DDA uses advanced machine learning
to more accurately understand all
of the relevant data about the marketing moments
that led up to a conversion and how each of those touchpoints
contributed to a conversion, all while respecting user privacy.
So let's dive a little bit deeper on DDA.
There are two main parts to the data-driven attribution
methodology.
The first part is analyzing the available path data
to develop conversion rate models for each
of your conversion types.
Data-driven attribution uses data
from both converting and nonconverting paths.
So for example, the paths that clicked on an ad,
viewed a product, and purchased versus the paths
that clicked on ads but did not ultimately purchase.
It uses this data to understand how
the presence and timing of particular marketing
touchpoints may impact your users'
probability of conversion.
The resulting models assess how likely
a user is to convert at any particular point
in the path given exposure to a particular click event.
The second part is using the conversion rate model
predictions as input to an algorithm
that attributes conversion credit to click events.
The data-driven attribution model
assigns credit based on how the addition of each click
event to the path changes the estimated conversion
probability.
In addition to looking at data from both converting
and nonconverting paths, the data-driven attribution
algorithm uses features, including
time between the click event and the conversion, format type,
and other query signals to calculate this credit.
And so with that, let's dive into the Google Analytics 4
UI and take a look at the attribution reports.
You can find both of these reports in the Advertising
Workspace.
For those of you familiar with Universal Analytics,
you'll notice that these two reports are enhanced and merged
versions of the multichannel funnel reporting.
First, let's look at the conversion paths report.
This report is a central place for you
to analyze top paths, time lag to conversion, and path length
to conversion.
It has two sections, the data visualization
and the data table.
Once you're in this report, like all of your other Google
Analytics 4 reports, you can customize the date range.
You can also select one or more conversion events
or add filters.
Both the chart and the data table
show your data broken out by the default channel grouping
dimension.
You can use this dropdown at the top of the chart or the data
table to view data by the source medium or campaign dimensions.
And then, of course, you can use the attribution model dropdown
to select the attribution model that you'd
like to use for the visualization and the data
table.
Now, let's talk about this data visualization here.
The data visualization depicts the customer journey,
showing conversion credit across early, mid,
and late touchpoints so you can see which channels initiate,
assist, and close conversions.
Early touchpoints are the first 25% of touchpoints in the path.
Mid touchpoints are the middle 50% of touchpoints in the path.
And late touchpoints are the last 25%
of touchpoints in the path.
You can hover over the data visualization elements
for more specific information.
Now, if we look at the data table
right underneath the visualization,
this is similar to what you've seen in Universal Analytics
attribution.
It shows you the paths users take
to complete conversions, as well as the following metrics--
conversions, purchase revenue, days to conversion,
and touchpoints to conversion.
And that's an overview of the conversion path report.
Next, let's take a look at the model comparison report.
When you go into this report, you
will see a data table that shows your data broken out
by the default channel grouping dimension.
For each channel, you will see two metrics as calculated
by the selected attribution models, conversions
and revenue.
In this example, we are comparing
the cross-channel last click model
to the cross-channel data-driven model.
You'll be able to understand the percentage by which conversions
and revenue increase or decrease under different attribution
models.
And that's an overview of how you can use the attribution
reports with data-driven attribution in Google Analytics
4.
KRISTA SEIDEN: Thank you so much for sharing the new attribution
reports in Google Analytics 4 Properties with us.
I know I am super excited that data-driven attribution is now
available to everybody in Google Analytics 4.
In Universal Analytics, it was only available
to 360 customers, so this is a huge value add to GA4.
Thank you again.