Understanding User Explorer Reporting: Google Analytics Latest Feature

User Explorer Reporting In Google Analytics

google analytics

The Google release notes for April 11, 2016 bought a nice little surprise. Google has introduced a new feature named User Explorer Reporting. It is quite an awesome feature that shows very specific visitor interactions across the website.


What Is User Explorer?

According to Google’s latest release notesConfusedUser Explorer Reporting is 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.

Too much technical? Alright lets simplify things like we always do!


User Explorer Reporting GuideUSer Explorer

You can find this report by navigating to Audience menu > User Explorer in your Google Analytics view.

Landing Page Overview

After you click, you will see the following screen.

USer Explorer

As you can see, you now have access to information based on individual users (client ids).
Client Id is a unique ID that Analytics assigns to each device from which users engage your content. Of course you won’t be able to know who the actual user is, but you get a better idea as to what a particular user stats are.

You will also notice a box (like a chess) below the date range option on top left. This is an important feature that lets you control the sample size of the number of sessions used to calculate this report.

User Report

In Analytics, sampling can occur in your reports, during your data collection, or in both places. Sampling your traffic allows for accurate reporting without a decrease in processing speed.

All the other options like sessions, bounce rate are self explanatory. Lets dive deeper into the user reporting part.


Introduction to User ReportUser Report

The ‘user explorer’ report is made up of several individual ‘user reports’. Each client Id will give you an individual report. The report provides details about an individual user like attributes Acquisition date and Acquisition channel.

After selecting the 1st client id you will see the following screen.

User Group

Lets go through every thing in this page and understand what it means:

  1. It shows the date range for which you want to see the the report.
  2. It depicts the client id which you selected.
  3. This shows that the user was first acquired on 15th April, 2016.USer Group
  4. The user came directly to the website. (This can be social and organic)
  5. The device used to access the website was a Desktop (or Laptop).
  6. If you want to go back to the main user explorer page select this.
  7. This user has generated 106 sessions in total so far and has spent 31 hours 39 minutes and 40 seconds on the website. The user has not generated any revenue.
  8. You can combine two dates to form a segment to view common results.
  9. You can opt for how many filters you want to apply. It is better depicted in the image on right.
  10. You can select descending if you want to see report from finish to beginning or ascending if not.
  11. This shows the last time the user was active on your website and how many sessions took place. In this case the user last came on 20th May, 2016 and had 3 sessions.

Did you find any analysis that I have missed? Please write in the comments below.


How to use the ‘User Explorer’ reportquestion mark 1019820 960 720

Now once you know what a user report contains, the most important question still remains: What do I do with this? How to use the report?

With the report you can:

  1. Generate thousands of reports for each user.
  2. See which particular user is more active.
  3. See how many people are making a purchase completing a goal.
  4. Get a better understanding about the conversion path
  5. Sort the report by sessions, session duration, bounce rate, revenue, transactions and goal conversions
  6. Get report on Pageviews, Goals, E commerce and Events.

Hopefully you have a better understanding about this very useful feature. Please implement it yourself and if you face any challenge or have any questions, feel free to write to me.

Here is a short video by Measureschool explaining User Explorer. Enjoy!

What Is Cohort Analysis: A complete Guide

Cohort Analysis In Google Analytics

Google recently included a cohort analysis report in the Analytics’ audience section that takes the data from a given website or app. Rather than looking at all users as one unit, it breaks them into related groups (Cohort Type, Cohort Size and Metrics etc.) for efficient analysis.

You can access Cohort Analysis by going to the Audience tab in Google Analytics.

Cohort Analysis

The report, which is in beta release, may help marketers and analysts identify time-based trends like testing the effectiveness of forms, content, products, or ads.

While cohort analysis is sometimes associated with a cohort study, they are different and should not be viewed as one in the same. Cohort analysis has come to describe specifically the analysis of cohorts in regards to big data and business analytics, while a cohort study is a more general umbrella term that describes a type of study in which data is broken down into similar groups.


How Do You Do Cohort Analysis In Google Analytics?

It might seem complicated but you can easily do a cohort analysis in Google Analytics. GA provides four different ways to display the cohort data:Cohort analysis

  1. The Cohort Type: Where you mention the grouping of cohorts
  2. The Cohort Size: That is measuring the number of cohorts,
  3. Metric: The number of times a cohort visited the page,
  4. Data Range: The time period of measuring cohorts and data.

The Cohort Size:

The dimension that’s the basis of the cohorts. You can only select one dimCohort Analysisension at a time.

The Cohort Type corresponds to the table column that includes the total number of users in a cohort.

For example, if you select Acquisition Date, the cohorts are grouped based on when users joined your website or app. Acquisition Date is the only option that’s currently available.


The Cohort Size:

The time frame that determines the size of each cohort. This corresponds to the date and number of users in each cohort cell in the dimension column.Cohort Analysis

For example, if you select Day, the cells in the dimension column display a single date and the number of users organized into the cohort for that day.

If you change your selection to Week, a date range appears, and the number of users organized into the cohort for that week also appears.


Metric:Cohort Analysis

The metric that’s being measured for each cohort. You can only select one metric at a time.

The metric corresponds to all columns in the table, except the Cohort Type column, which displays the dimension.

For example, if you select Session Retention, each Day displays the percentage of users in each cohort that had a session that specific day.


Date Range:Cohort Analysis

The time boundary that determines what data appears in the report. This corresponds to the number of rows in the table.

For example, if you select the Last 7 Days, there will be a total of 8 rows in the table: one for each of the past 7 days, and one for sum of all cohorts.


What Do Charts Mean: Understanding Cohort Charts

Cohort Analysis

This is the most important part: understanding what these cohort charts mean! I don’t know about you, but this isn’t really immediately clear to me, so let me walk you through how to look at it.


Understanding Cohort Chart

The cohort chart is a line chart which shows the cumulative metric values for the selected cohorts. To start, in the example below, 27.03% users have been retained the next day and only 13.96% users the day after that.

Cohort Analysis

Through the menu you can select and compare up to four cohorts on the cohort chart.

Cohort Analysis

You can apply up to 4 advanced segments (both default and custom) to the Cohort analysis report and these advanced segments are reflected in the Cohort Chart:

Cohort Analysis


Understanding Cohort Table

Here is a screenshot of the cohort table. Each row represents a cohort. For example, May 18, 2016 is one cohort and May 19, 2016 is second cohort and so on.

Cohort Analysis

If you select date range as ‘7 days’, the data table would contain 8 rows.

The first row or the top row shows the total or average value of all the cohorts for each column. The remaining 7 rows show data for each cohort. Similarly if you select ‘Last 30 days’ as the date range then the data table would contain 31 rows.

Each column in the Cohort Data table represents cohort size: one day/week/month of data.The data table contains fix number of columns which is 13.

Each cell in the cohort data table contains the value of the metric you selected through ‘metric’ menu. For example, if you selected pageviews metric then each cell would contain total number of pageviews per cohort per time increment.

The color intensity in each cell visually indicates the magnitude of the metric value relative to other values in the cohort.

Cohort Analysis

So what does the above table mean? I’ll combine all the points and give proper analysis:

  1. The table depicts the user retention for the past 7 days. That is why instead of numbers, percentage is showing.
  2. If you see the 2nd row (May 18, 2016), 582 users came to the website out of which 30.76% users came back on 19th May and 20.96% users came on 21st May.
  3. If you look at the color of the Day 2 on 19th May, it is darker than the Day 2 on 18th May. This depicts that user retention was better on 19th May than on 18th May.

So there you have it! Hope you have a better understanding about cohort analysis now. If there are any questions about cohort analysis, Google analytics or digital marketing in general, please write to me. I will be glad to help you out.

Here is short video by PPCHeroBlog explaining Google Analytics. Enjoy!