# Leveraging Cohort analysis and LTV report in Google analytics.

## 1. What is Cohort Analysis?

A Cohort is a group/segment of users who share common characteristics that occur within a defined period of time and it is done to understand user behaviors. A cohort is simply just another way of segmenting users but it is based on date.

Examples of Cohorts – All users who are acquired during the Thanksgiving and Christmas holiday shopping season. Users who visited the website during 1 Dec – 31 Dec via organic search.

## 2. Settings and Features of Cohort Report –

The new cohort analysis report in Google Analytics has 3 main sections –

Section 1 – Menus to create the Cohort Report.

Section 2 – The Line Graph.

Section 3 – The Tabular Data.

Section 1 – Menus to create the Cohort Report –

A. Cohort Type – At this moment, cohort report in google analytics lets you create cohort only based on Date only. Acquisition Date is simply the date when your users first visited your website or App or when you acquired the users.

B. Cohort Size –

This determines the size of each cohort. It helps you to specify how do you want to group each Cohort? Do you want them to group by Day, Week, or Month?

C. Metric –

The metric that you want to evaluate.

All the metrics in the Cohort analysis report are categorized into three categories.

1. Per User – Like Goal completion per user, revenue or transactions per user, etc.

2. Retention – User Retention

3. Total – Goal completion, Revenue, Transactions, etc.

By Default, the user retention is selected in the cohort report.

What is User Retention?

The number of users in the cohort who returned in the Nth time period ( Day, week, month) divided by the total number of users in the Cohort.

D. Date Range –

The time frame that determines what data will appear in the report. The values of the date range depend on the “Cohort Size” selected.

As you can see that I have selected the Cohort Size by week so my options are Last week, last 3 weeks, last 6 weeks, etc.

and If I change the cohort size by day then my options will be last 7 days, last 14, 21, 30 days.

Suppose if I choose a date range of the last 7 days as shown in the above pic and today is 5 Jan. Google analytics will start to count 7 days from yesterday and pulled out the data from the past 7 days.

## 3. How to do Cohort analysis in Google Analytics? –

Now we know all the features, settings, and the way data is represented in the cohort report. let’s understand how to use these reports to find insights.

To make our analysis more effective and find better insights, we need to take certain steps.

What  – First, we need to decide what are we actually trying to understand from this report. Are we interested in understanding retention, revenue, engagement, etc?

Which Metric – Depending on our end goal, we need to select the most relevant metric, as we see there are lots of metrics available to us.

Which Segment – The last step is applying the segment that is meaningful to your business. Maybe you want to understand the difference in behavior between email and RSS readers or Paid vs Organic traffic etc.

To get started –  First Go to the Audiences > Cohort Analysis – to access the report in the Left Navigation.

As in my case, Recently I published an Article on Remarketing – The Ultimate guide to remarketing with Google analytics – Get started Now. And I have seen the highest number of traffic to this blog after publishing this article.

But the question is ” So What?

I get lots of visits but did I attract readers who stayed with me for a long time and become a loyal reader of this blog? What percentage of these users visited the website again every week or month? Cohort analysis can help us to answer these kinds of questions.

Depending upon the nature of the business, you set the cohort size, metric, and date range.

In the above pic, you can see that I have selected cohort size by week and user retention metric and last 6 weeks in the Date range. Here, I am interested to know what percentage of users came back to my website after they first interacted with it and how long they keep coming back again and again to read my articles.

If you look at the table data, you can see that Dec 10 – Dec 16 cohort has the maximum number of users (859 users) as I published the article on Dec 10.

And in the heatmap of Dec 10 – Dec 16 and Dec 17 – Dec 23 cohort, you can see that only 3.73% and 4.72% of the readers respectively come back after 1 week of acquisition. Then the numbers again reduced after the 2 weeks. And the Nov 26- Dec 2 cohort has the highest retention rate relative to all the data in the table hence very darker in color.

And in the line graph above, it’s clear that two of my high user cohort’s retention faded away after a week but the Nov 26- Dec 2 stayed longer than those other two cohorts.

Overall if you look at the table data above, you can see that my website ain’t able to retain users after the 3rd or 4th week.

Now, I know from the above data that I have to keep writing at least 2-3 articles every month ( In Dec I wrote only one) to keep these users coming back again and again to read my articles. Now, I know beyond what point, I am going to lose all these readers that I acquired with so much efforts.

I can also create a segment of any cohort that I am interested and apply to other reports in Google analytics to understand more about them.

Until Now, we only look at the users at an aggregate level but to go one step further by apply segments to our cohort report. Some of the websites that are sending high traffic to my blog are GrowthHackers community, direct traffic, and social media. Segmenting the cohort report with the traffic sources will help me to understand, which traffic sources are sending me more relevant traffic and which are not. Without segmentation, It will be very hard to understand the difference between the user behavior from different sources.

How to create the Traffic sources segment.

1. First Click on +Add segment at the top > New Segment.

2. Then select the source for which you want to create the segment. In my case it’s GrowthHackers. And choose filter users at the top.

Why User-scoped filter?

Because the cohort analysis report is user-based, so if you apply a segment based on sessions, you can get unexpected results that do not include 100% of users on day 0 as you would expect. As you can see in the above pic.

Now, let’s apply the two segments and try to understand the difference in user behaviors between these two.

If you look at the user retention for all social media visits between Nov 26 – Dec 2, the data looks promising but if you look at the number of users that came during this period, it is only 3. You can’t make any decision based on 3 users, so keep this in mind when analyzing you data.

Overall the user retention for Growth Hackers is better than the social media.

Now, we can take our analysis to the next level by asking again ” So what?

Ok, some % of users come back to my website again and again for some period of time but I want to know what was the outcome of all these? Are we able to convert these users or not? And if so then which cohort is better at it?

As this is a content website, I can use the Goal completion or session duration metrics to find it out and if you are in an E-commerce business then you may want to use Revenue per user or revenue. But you can also use Goal completion if you want to. As I said before depending on your end goal ( What are you trying to understand) pick the metric that gives you the direct insights.

Now, this is much better. Not only we able to retain more users from Growth Hackers community but the number of goal completion is also much higher than the social media.

So, it’s obvious that allocating more resources to Growth Hackers and then Social Media is the right thing to do.

And if you have an E-commerce website, select the Revenue or Revenue per user metrics as we discussed earlier.

Again, you can apply different segments to understand and compare users behavior.

Here, I Just applied two default segments in Google analytics- organic and paid. Nothing very fancy or complicated. And you can see that most of the revenue is generated on the day the customers were acquired and after that, it’s nearly come down to $0 for both the traffic sources. Although, the organic traffic is performing much better than the paid traffic. ## 4. What is Customer Lifetime Value? The customer lifetime value helps you to understand how valuable different customers are to your business based on Lifetime performance. As customers are becoming less loyal to brands and more loyal to their overall experience. Focusing on Customer lifetime value enables you to find the customers that matter most and have a better relationship with them. It helps you to compare the users acquired through different marketing channels ( organic, paid, email, display, etc.) and find out which sources bring the high-value users for your company in the long term. ## 5. Settings and Features of Lifetime Value report – 1. LTV Metric – The primary lifetime value metric you want to analyze. Available metrics in the report – 1. Goal completion per user (LTV). 2. Pageview per user ( LTV). 3. Revenue per user (LTV). 4. Session duration per user (LTV) 5. Sessions per user (LTV) 6. Transactions per user (LTV) 7. Appviews per user (LTV) – if it’s an app You can also compare these metrics with one another with the help of compare metric option. Look at the above picture. 2. Acquisition Date Range – The Date range during which users were acquired. Use the acquisition date range to set the cohort that you want to examine. The graph shows the lifetime value per user for the metric over a period of 90 days( Maximum lifetime) in increments of day, week, and month. In the above picture – Day 0 – is showing the cumulative revenue per user on the day of acquisition. Day 70 – is showing the cumulative revenue per user on the 70th day after the acquisition. The table shows the number of users you acquired during the Acquisition date range, along with the two additional metrics related to the LTV metric you have selected at the top. In this case, it’s – Revenue per user(LTV) and Revenue(LTV). ## 6. How to analyze the Lifetime value report in Google analytics – For the sake of simplicity, let’s set the acquisition date range to be Dec 1 – Dec 31, 2017. In this example, we want to understand which channel is responsible for acquiring users with the highest Revenue(LTV) for the Google Merchandise store. From the above pic, it is clear that the number of users acquired from organic search is the highest among all but the referral traffic is responsible for the highest Revenue(LTV)$264,788, followed by $57,213.51 for the direct traffic compared to only$31,499 for the organic search traffic.

And if you look at the last row for the Affiliate traffic, you can see that the lifetime value delivered by it is \$0.0. WTH!

From this report, you know which channel is helping you to succeed in the long-term and which isn’t?

Now let’s change the dimension from channel to campaigns.

Just look at the red rectangle in the above pic. you know which campaigns needs to be killed and where you should invest more.

I hope you find it easier to understand the Cohort and LTV report in Google Analytics. Please let me know in the comment section below. Like, share and subscribe if you like this post.

Rating: 1 out of 5.