Cohort Analysis in Google Analytics: When Should I Use Each of The Metrics?

The cohort analysis is one of the most useful features in Google Analytics, because it helps you isolate the impact of your different marketing activities on a specific group of recipients, instead of noise in the data.

But there is still a lot of confusion in practice, such as which cohort size should I choose? Or when should I use each of the metrics?

If you have the same confusion, you are not alone, in our last article we mainly introduced which cohort size should I choose.

This week, we will pay attention to introducing the other question, when should I use each of them? 

Let’s begin by looking at the metrics that are available in Google Analytics. 

Google Analytics offers you 14 metrics to use for your cohort analysis and defaults to percentage retention, which describes the percentage of users that come back at each of the later cohorts.

While 14 metrics might seem daunting, they are really just different ways to measure three key user experience questions. 

Let’s look at each in detail.

Are Users Coming Back?

In Google Analytics, you can answer this question in three levels:

Users and User Retentions — How many users, as individuals, are coming back to our website? 

User retention is probably the most important metric for ecommerce stores or freemium apps. 

Early retention metrics such as Day 3 retention can serve as proxies to assess traffic quality for ROI-positive user acquisition campaigns. 

Needless to say, retention is also a strong indication of the general quality of the app and its user experience.

Sessions — A session is the period of time a particular user is actively engaged with your website. 

How many sessions are visited by users after the initial cohort time?

Pageviews — Pageviews is the total number of pages viewed.

How many pages are visited by users after the initial cohort time?

Increasing pageviews are a reflection of increasing traffic, hence a good thing. But the low pageviews indicate that you need to optimize your website design or user experience.

Out of all three, User Retention is probably the “purest” answer to the question, but sessions and pageviews can also give you a slight idea of how engaged those users are in the future — pick whichever one you like.

Are Users Engaged Over Time?

The question can be answered in two ways: how frequent do users visit during each of the future time periods, and how engaged are users during each of their visits.

Sessions Per User —This metric is the average number of sessions per user in a special period in each certain group.

It is the direct answer to the first question. It shows you how frequently your users come back in one specific future period.

The higher the number, the better. For example, if your website uses more than 1.6 sessions per user, it means that a large portion of your visitors return to another session, which means your online content is very attractive.

If it is lower than 1.2, the performance of the website is not high and needs to be optimized.

Pageviews Per User — This metric is the average number of pages a person views in a given session. And it is the direct answer to the second question.

For example, if your website has an average page per session of 3, this means the average user visits three pages before leaving your website.    

This metric can be helpful for measuring how sticky and engaging your website is. In general, any content site that relies on Adsense, advertising, or affiliate revenue wants to increase the number of pages that each user sees. 

More eyeballs and time spent browsing pages on your site means more revenue. 

Session Duration and Session Duration Per User — Both of these metrics serve as an answer to both questions. 

Session duration is a metric that measures the average length of sessions on your website. 

This metric helps measure the stickiness of your website. In general a good website design and high-quality content will increase the user’s stay time.

The “per user” option is considered better as it is less impacted by the amount of users visiting in total.

Overall, session duration per user is recommended as the metric to measure user engagement within each future period as it kills two birds with one stone.

However, feel free to use a combination of pageview per user and session per user as those metrics are perhaps more familiar to your intended audiences.

Are Users Converting Over Time?

Now onto the ultimate question that is relevant to everyone running a business out there. There are so many perspectives to look at when trying to answer this question, and my honest suggestion is just to pick one that works for you and your company.

Transactions and Transactions Per User — Just as it is stated, the “per user” option is recommended to remove the effect of user fluctuations in each of the future periods.

This metric is used to measure marketing effectiveness. If this number is high, that's good.

Revenues and Revenues Per User — Just as it is stated. The “per user” option is recommended to remove the effect of user fluctuations in each of the future periods.

Average revenue per user is the (average) revenue generated by each active user using your application in a certain period of time in each group.

Average revenue per user is helpful for determining the ROI of your marketing efforts and calculating the lifetime value of your customers. This metric is also beneficial for evaluating pricing structure (should you charge more?) and understanding how ARPU is changing over time.

Goal Completions and Goal Completions Per User — Notice that this is the completion of ALL of your goals, which is very sad for me since it is a vanity metric. 

I do NOT recommend using this metric as your goal could vary from the ultimate conversion, to engagement conversion, to other usages. I certainly hope they enable tracking of completion of separate goals soon.

Overall, Cohort analysis is a long-term process that continuously analyzes and observes changes in data, and optimizes your ads based on feedback to increase website traffic. 

Optimize the website and continue to output high-quality content to increase the stickiness and interaction of the website, and ultimately increase transactions and revenue.

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Cohort analysis in Google Analytics : Which cohort size should I choose?