Getting Started With Google Analytics 360
Unsampled Reports and Custom Tables - Part 1
Analytics 360 empowers enterprise level organizations
to work with large quantities of data by providing
higher sampling thresholds than the standard Google Analytics offering.
In any instance where you exceed those higher thresholds,
Analytics 360 offers even further reporting capabilities
with Unsampled Reports and Custom Tables.
We’re going to cover this in two parts.
In this video, we’ll discuss two main factors
- sampling thresholds and row limits -
in order to understand the benefits of Unsampled Reports and Custom Tables.
In the next video, we’ll discuss how you can benefit
from Unsampled Reports and Custom Tables.
Let’s start by discussing how sampling works in Google Analytics.
Built-in reports are not sampled in the Analytics user interface.
There are tables of data behind-the-scenes
that have been processed to support the right dimensions
and metrics for your built-in Analytics reports.
We refer to these tables as “aggregate tables.”
When you add a secondary dimension or segment,
or create a custom report, you may be requesting
a combination of dimensions and metrics
that are not available in the existing aggregate tables.
This means that Google Analytics has to assemble
the data for that report at the moment you
modify the report or open your custom report.
This report request is now considered an ad-hoc query.
Ad-hoc queries are subject to sampling
if the number of sessions for the date range selected
exceeds the threshold for your property type.
The goal of sampling is to serve ad-hoc reporting quickly within the interface.
Without sampling, a user could be waiting a long time to receive a report,
making analysis less user-friendly.
Here’s an example of a report where a secondary dimension, “Browser,”
was added to the primary dimension, “Source / Medium.”
Because the report was above the sampling threshold limit for ad-hoc queries,
adding this secondary dimension caused the report to be sampled.
You can see if a report is sampled by checking the indicator icon
next to the title of the report.
When the indicator is green, the report has not been sampled.
When sampling or row limits are imposed, the indicator will be yellow.
Hovering over the icon provides more detail.
When you require a complete and unsampled dataset
for customized reporting that exceeds the sampling threshold,
you can benefit from Unsampled Reports and Custom Tables.
The second factor to keep in mind with Analytics reporting is row limits.
Row limits are separate from sampling thresholds
in that the limit applies to the maximum number of unique rows in a report
and not the number of sessions or conversions.
It’s possible for a report to be impacted by sampling thresholds
and not row limits and vice versa.
In Analytics reports, each row is a dimension value.
Some Analytics reports contain dimensions that have
a large array of different values.
The number of different values a dimension can have is called cardinality.
Dimensions with many different values
are referred to as high-cardinality dimensions.
The “Page” dimension is a common example of a high-cardinality dimension.
Imagine an Ecommerce site that sells a huge number of products,
each with its unique product page and therefore unique URL.
In contrast, a dimension such as “Device Category” is a low-cardinality dimension
since there are only three possible values.
In this case: desktop, mobile, and tablet.
When a report is impacted by row limits
you’ll see a row containing data marked as “(other)”,
or a warning that mentions a high-cardinality dimension.
As with sampling, row limits are imposed in order to maintain a faster experience
in navigating and using reports.
In cases where you see rows grouped as “(other)”
or a warning about a high-cardinality dimension,
Unsampled Reports and Custom Tables can help
because of their expanded row limits.
In the next video, we’ll discuss how to use these features.