New User Explorer report in Google Analytics – a first look

Posted on Posted in New GA Features

I noticed a new report appear in my GA view recently. Since then it’s featured in the latest set of Google’s release notes:

  • User Explorer Reporting: A new set of reports in Google Analytics lets you perform analysis of anonymized individual interactions with your websites and apps. User Explorer utilizes existing anonymous Google Analytics data to deliver incremental insights that marketers need to improve and optimize their sites and apps. The feature is now available in the Audience sections. Anonymous Client ID and User ID will be surfaced in this report as a part of the release.
    https://support.google.com/analytics/answer/6392777?hl=en

TL:DR
I’m still looking at ways of utilising the report fully, and there’s some issues around sampling (as always) once you start drilling into it and applying segments. I’m also wondering about how we can use the report outside of the analytics team as there’s no way of exporting the ‘journey’ view currently – just the table. There’s also no widget available for it at the moment to enable you to add it to a dashboard.

Overall though I think it’s a really powerful, visual way of looking at the behaviour of groups of individuals – without compromising privacy.

 

Note: this report is based on a service/account management site with no ecommerce.

 

You’ll find the new report under Audience:

The user explorer report sits under audience

Selecting it displays a familiar view with the standard options in terms of date range and segments, along with a data table.

data table
Data table

You may notice a ‘high cardinality’ warning appear in the top left.

highcardinality
High Cardinality Warning

This basically means that where there are a large volume of possible values for each dimension, your report may be affected by Google Analytics limits.

For a dimension such as ‘Device category’ you will only have 3 values – desktop, mobile or tablet – so the cardinality is 3. For something like ‘Browser’ or ‘Country’ you could have dozens or hundreds of possible values therefore their cardinality will be high.

Essentially, you may not see each individual value as GA will roll them up and put them into a category called ‘other’.

The other thing to be aware of is the sampling setting. Although it doesn’t explicitly state that the data is sampled,the sample slider does appear by default.

Sampling Slider
Sampling Slider

Depending on the volume of traffic to your site you can get very different figures.

For example, when it’s set to ‘Faster processing’ the highest number of sessions for any ‘Client ID’ was 3. When it was set to the other end of the scale (‘Higher precision’), the sessions figure was 117.

It appears (from looking at the date range) that we’ve only got data for this report from 9th March 2016, but that’s a good month’s worth at least. For the purposes of this exercise though I’m only going to look at one day.

Let’s look at the ‘Client ID’ at the top of the table.

Client ID Overview
Client ID Overview

The user report tells us quite a lot. We’ve got acquisition date, the channel they found us through and what type of device they used.

It also tells us that on this day alone the user had 10 sessions and spent nearly an hour and a half on the site. If we’d set monetary values for any of the activities they had completed it would also have told us how much their visit meant to us in Pounds/Pence/Dollars/Cents.

clientoverview2

The initial view is sorted by last visit first but I prefer it in ‘Ascending’.

View order
View order

The report shows us an overview of each session (split by a thin grey line), with the pages the user visited.

Session history
Session history

If you click on the page view it gives you additional detail including the page title and URL.

Page detail
Page detail

What’s also very cool is that you can apply a filter to view those sessions containing pageviews, goals, ecommerce transactions or events.

View filter
View filter
Goal view
Goal view

Applying a goal filter and clicking on an individual goal gives you this detail:

Goal detail
Goal detail

Probably the most interesting feature of the user report though is the ability to create segments within it. Simply check the box next to the pageview/goal/ecommerce/event and hit create segment.

Create a segment
Create a segment

Give the segment a name and set your conditions. You also have the option to apply the segment to any view and to apply it to the report you are working on straight away.

Segment detail
Segment detail

Selecting save with those options applied takes you back to the first screen and as you can see our segment has been applied.

Segmented view
Segmented view

The segment also appears in our segment library to be used in future.

Segment in our library
Segment in our library

One thing to note though is that you can’t compare multiple segments next to each other. You have to select one or the other.

When creating a segment you can of course apply multiple conditions which is really easy to do in this report. So for example if I wanted to see which visitors had visited a certain page in a session and completed a goal I just tick the appropriate boxes and create the segment in the same way as above:

Multiple conditions
Multiple conditions
Multiple conditions segment
Multiple conditions segment

 

And that’s about it. I’m still looking at ways of utilising the report fully, and there’s some issues around sampling (as always) once you start drilling into it and applying segments. I’m also wondering about how we can use the report outside of the analytics team as there’s no way of exporting the ‘journey’ view currently – just the table.

Overall though I think it’s a really powerful, visual way of looking at the behaviour of groups of individuals – without compromising privacy.

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