Companies collect user data all the time. The real challenge comes from grouping that data and turning it into actionable business insights. 

Simply put, how can I make this data work for my SaaS company in the most efficient way? 

Cohort analysis is a very important but also misunderstood term when it comes to analyzing SaaS businesses.

Cohort analysis can provide answers about marketing strategies that are essentialfor both SMEs and large corporations.

Let’s look at SaaS businesses and their key metrics to understand the importance of adopting and implementing cohort analysis to ultimately optimize conversions.

What is the Definition of Cohort?

A cohort refers to a group of individuals sharing statistical characteristics, for example, a group of people classified by age or, for example, a group of students in a classroom.

What is Cohort Analysis?

Cohort Analysis is a tool used in behavioral analytics to measure user retention and user life cycle management. It’s a basic user segmentation tool.

You can segment users together in different ways, be it geographical location, age groups, etc. Instead of grouping all users together as one unit, they are broken up into related groups called cohorts.

An example of a cohort could be the graduating class of 2021 for instance. All the students are cohorts as they have graduation in common.

Cohort analysis allows you to find the highest or lowest cohorts by comparing their behavior and metrics over a period of time. 

Once you have this data you can ask targeted questions regarding your product to make decisions that will reduce churn and optimize revenue generation.

Key Metrics to Follow by Cohort Analysis

What is a Churn Rate?

Simply put, the churn rate is the percentage of customers that are unsubscribing or not using an app or a product within a time period.

Churn rates are vital in SaaS companies where revenue is dependent on subscriptions. High churn rates negatively affect profit and hinder growth. 

What are KPIs?

A key performance indicator (KPI) measures the performance and success of a business. It measures how effectively a company achieves its key objectives. 

Organizations evaluate their success for reaching targets by using KPIs. Companies have different KPIs which depend entirely on the business.

The most important KPIs are generally acquisition or growth, engagement, and retention.


Acquisition measures how many people have acquired and signed up to use your product. A lot of time is spent on how many website hits you have or how many downloads your mobile application has, for example. Acquisition is a really useful statistic to monitor. 

It’s crucial that people who download an app actually try your product. Acquiring new users is the easiest part of the process. However, the measure of success for product managers is whether or not people actually get value out of the products.

It’s also critical to increase your user base because it will ultimately help grow your customer or revenue intake. Having an active customer base and adding new acquisitions will increase your total number of active users.

While  acquisition is key to understanding your growth metrics, a product manager’s time should be spent more on engagement and retention.


Customers that engage with your product on a continuous basis and who get value out of your product are the focal point of your business.

Engagement measures how people are getting value on a recurring basis from your product. Customer engagement analysis provides guidelines and benchmarks for more effective marketing strategies and analysis. However, engagement metrics often inform a business more accurately when viewed in tandem with retention metrics.


Your customer retention rate is a reflection of customer loyalty and satisfaction. It’s the company’s existing customers.

As we’ve mentioned, the measure of success for product managers is whether or not people actually get value out of a product. Having consumers continually using your product and finding value in it is the primary focus in SaaS.

Retention and cohort analysis go together. Retention is the goal and cohort analysis is the tool that helps us identify opportunities to improve retention.

Retention is important for start-ups and existing companies because it can guarantee sustainability.

Estimate User LTV (Lifetime Value)

User lifetime value or customer lifetime value is an estimation of the net profit contribution by a user for the duration of their relationship with the company. Establishing a customer’s LTV can help companies make better economic decisions and important forecasts.

Start-up companies need to forecast revenue growth, and therefore LTV, through an assessment of their user base growth. Various companies have different definitions of lifetime value, for example, 12 months, 36 months, 48 months, or even 5 years for well-established companies.The type of company you have will define your LTV.

You can estimate your revenue and show your progress through the Cohort analysis curve.

How is a Cohort Analysis Presented?

A cohort analysis is presented on a visual chart that tracts the progression of key metrics relating to a group of users over a specific time period. 

SaaS companies track retention rates month by month, grouping cohorts together by the date they signed up. It’s also possible to do a comparative study of different cohorts by aligning their starting dates for analysis. 

The time-based cohort is the most common grouping of cohorts in SaaS. It provides an insightful segmentation reflecting behavioral trends over a specific time period. 

Understanding User Retention Curves

A retention curve tells us how many people have left and how many people are getting value from the product or service, thus adding value to your company by identifying your persistent loyal users.

If your product is successful, you will not lose users. You will retain users and new consumers visiting your site will likely return. To measure who stays and who goes, a retention curve is used.

The user retention curve is a graph that shows the percentage of acquisitions you have retained and the percentage of active users you’ve had over a specific period. You cannot just group any data together, you have to do it by cohort, or your metrics will not yield accurate or beneficial patterns.

You don’t want to see too much degradation on your cohort graff. Cohort Analysis does not only show you what has happened, it’s also a tool with the power to show you what has changed and, potentially, why.

Defining Your Cohort

The first step in Cohort Analysis is to define your cohort. There are typically two ways you can define a cohort.

  1. Engagement-Based: Using mobile or gaming downloads as an example – if a user installs your mobile or gaming app in June 2020, your cohort will be June 2020. You’ll always use the date of engagement.
  2. Monetization-Based: This will reflect when users first purchased from you. While many users download your product via a free trial for example, not all of them pay the subscription fees and continue using your product when the trial expires.

You don’t want to see too much degradation on your cohort graff.

Beginning Your Cohort

The first time a user establishes a meaningful relationship with you through engagement, or becomes an “active user,” that’s when your cohort starts. They might engage by downloading or installing your product. In the case of financial or eCommerce businesses, meaningful relationships are considered formed at registration. Monetization based on first transactions are also seen as meaningful engagements.

Name the cohort based on when the relationship happens, for example, June 2020 or 03/06/2020.

What is a SaaS Company?

SaaS is an acronym for Software as a Service. Simply put, software is made available on a company’s server for users to access remotely online 

In essence, a SaaS company is a software vendor that hosts and maintains their servers, databases, and application codes. The Saas company then makes the specific licensed apps available to customers via subscription over the internet. 

As the host, the SaaS company does the necessary application updates for its users.

The Main Challenge Facing SaaS Companies

The measure of success in SaaS businesses is in being able to adapt to change or, better yet, to be proactive in your adaptations. SaaS companies have to provide their users with what they need and meet them where they are in a timely manner. 

SaaS businesses are continually losing users. The analogy most commonly used, is water dripping from a leaking bucket. The business has to work hard at gaining new acquisitions to replace the users that they have lost. 

The Leaky Bucket Theory.

The leaky bucket model is an illustration of how a company’s churn and acquisition rates need to work in tandem. Acquisition is represented by the liquid being poured into the bucket. 

However, the bucket has holes in it and the leaking liquid represents the churn, or the users leaving the business. The ultimate goal of this model is to have the company’s acquisition growth (the water being added) fill the bucket at a rate higher than it is leaking (the churn) as best as possible.

A practical example

A company has 1 million users in June and they acquire an additional 500,000 in July. At the end of July they want to see the month-over-month growth from June. 

But instead of having 1.5 million users, the company only has 800k users. This is called the Leaky Bucket Problem; the organization couldn’t retain the 1 million active users because, in July, they lost 700,000 users through inactivity. The company is thus left with 800,000 users in the month of July.

In order to fix the problem, the company must measure the retention rate. They must also analyze user data to determine how they will manage their churn issue.

  • June 1: million active users
  • July 31: 800,000 active users
  • July Acquisitions: 500,000
  • Inactive Users in July: 700,000
  • Active User Rate: 30%

A 30% active user rate, month over month is considered low, so the company – thanks to their acquisition and churn analysis – now knows what they need to focus their efforts on improving. 

The time period a retention rate is calculated over (day, month, or year) will depend on the industry of a company. Mobile and gaming industries look at daily activity, for example.

Cohort Analysis is able to help companies understand retention analysis, estimate the LTV of their customers, and, ultimately, slow down the leakage.

Why is  Cohort Analysis so Important to SaaS Companies?

Information derived from a Cohort Analysis graph is incredibly beneficial to companies. It helps them to analyze data and find the answers they need to customer-targeted questions.

  • Cohort Analyses can compare different cohorts at the same time period during their lifecycle. They are a reflection of change in retention over a product lifetime.
  • They allow for an understanding of long-term relationships with a given user group.
  • The data sheds light on how different marketing strategies affect the customer churn for better or for worse.
  • Cohort analysis provides a better understanding of user trends and behaviours of cohorts  that affect business metrics like acquisitions and retention.
  • A better understanding of user trends and behaviors allows you to take steps to encourage other users to follow the same behaviors you identified in other cohorts. 
  • Cohort Analyses ensure more effective customer engagement that leads to optimized conversion rates. Cross-selling opportunities arise when you understand customer interaction towards marketing strategies and towards certain aspects of your product or service.

In Conclusion

In viewing what Cohort Analysis is in relation to an organization’s KPIs, we can see that it’s an absolute necessity, especially for SaaS companies.

Rather than trying to determine your business’ success by lumping growth and churn rates together, Cohort Analysis provides a clearer and more pinpointed perspective on user data.

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