If you’re looking to better understand your customer retention efforts, download our Ultimate Customer Retention Cohort Analysis Template for SaaS.
- What is a Cohort Analysis?
- Why Cohorts are Effective for Analyzing Data
- The 2 Types of Cohort Analysis
- How to Build a Cohort Analysis in 4 Steps
- Applications of Customer Cohort Analysis
- How to Build a Cohort Analysis for Customer Success
- What are the benefits of customer cohort analysis?
- Our Customer Retention Cohort Analysis Google Sheet Template
What is a Cohort Analysis?
A cohort analysis is a study of activities for a certain segment of customers or users. In this template, we are looking at the customer cohorts for the quarter or month they were acquired, and what % of those customers were retained for subsequent quarters/months.
As summarized in Lean Analytics (via Wikipedia), “Cohort analysis is a kind of behavioral analytics that breaks the data in a data set into related groups before analysis. These groups, or cohorts, usually share common characteristics or experiences within a defined time span. Cohort analysis allows a company to “see patterns clearly across the life-cycle of a customer (or user), rather than slicing across all customers blindly without accounting for the natural cycle that a customer undergoes.”
Why Cohorts are Effective for Analyzing Data
With cohort analysis, you can start to correlate initiatives in your own business to see how they may affect the customer lifecycle. As your company scales, iterates, innovates and creates processes, you would hope to not only acquire customers at a faster pace but also retain them longer, correct? One would assume as product/market fit is found, domain experts are hired and new campaigns are launched that customer retention gets better… but how do you know?
New Product Features
In order to best understand how new product features are impacting customer retention and other metrics you will want to look at a certain cohort of customers/users. Perhaps cohort retention improved as you started to introduce features in your product to engage customers through a daily digest. By understanding how customers interacted with the new daily digest you’ll be able to use data to determine where development time and resources should be placed in the future.
New Marketing Campaigns
Startups are constantly testing new marketing channels and go-to-market efforts. Without the proper data behind a new campaign, it can be difficult to determine what cohorts and campaigns are performing best. For example, maybe you introduce paid search as a marketing strategy, then realize retention drops because customers acquired through paid were not the ideal customer type. This should be a clear indicator that you either need to (1) improve different aspects of your paid funnel or (2) focus the time and energy on paid channels on different channels.
New Customer Onboarding
For SaaS companies and service providers, onboarding new customers is vital to their retention and growth with the product and your organization. Onboarding flows are constantly being tested and tweaked to convert your customers as best as possible. For example, let’s say you add 3 questions during the signup process to better tailor a new user/customers onboarding experience and it is shown in the data that this cohort is 2x as likely to take a key action in your application, you will want to implement and improve this even further.
The 2 Types of Cohort Analysis
Cohort analysis can be a powerful tool to interpret and understand your user data. While you can slice and dice your cohort data in a wide variety of ways, it ultimately comes down to 2 main types of cohort analysis:
Related Resource: Startup Metrics You Need to Monitor
One of the main types of cohort analysis is by acquisition type. As we mentioned in the previous section, cohorts can be valuable when analyzing marketing campaigns and efforts. By breaking down cohorts by acquisition channels, you’ll be able to better understand the specific channels that are performing best or campaigns that need to be tweaked.
The other main type of cohort analysis is by behavior. This can generally be used in regard to steps taken in a product. For example, you can create a cohort of users that have taken a specific action in your product. This can be used to inform and dictate product development and strategy.
How to Build a Cohort Analysis in 4 Steps
Building a cohort analysis can be time-consuming and tricky. That is why we created a template with just a few steps to help get you started (more on using our template later). At the end of the day, if you are creating a cohort analysis from scratch or plan on using our template there are a few steps you’ll need to take before you can get started
1) Start with a Goal and Questions
When building a cohort analysis you first need to figure out what the goal of the analysis is. At the end of the day the goal of a cohort analysis is to better inform your team to make decisions around product, marketing, customer experience, etc. If you’re not setting expectations and questions you want to answer, you can miss the point and impact of a cohort analysis.
2) Define the Metrics & Data Needed
Once you’ve determined the goal and questions you’d like to answer you need to understand what data and metrics you will need to measure and compile to execute your analysis. If you are measuring customer retention, you will want to start with clean data around your customer base. For example, you will want to have a grasp on contract size, sign up dates, churn dates, etc.
Depending on what you are tracking, it may require a deeper layer of data. For example, if you are looking at a specific marketing channel, you will likely want to include this data as well. Having cleaning and correct data is essential to making sure your analysis is effective as possible.
3) Perform the Analysis
There are countless tools and resources available to help performt the actual analysis. For example, Google Analytics has a builtin tool to perform cohort analysis but that requires your Google Analytics data to be 100% clean. To help we’ve created a tool to help automatically perform the analysis in a few quick steps.
4) Study the Data
The most important part of a cohort analysis is finding actionable insights to help better inform your business and product decisions. When studying your data, it is important to keep in mind the original goal and questions you set out with. See how different cohorts can help answer these questions and make better business and product decisions in the future. Check out more about specific things you should analyze and look for in the next section:
Applications of Customer Cohort Analysis
Cohort analysis can be applied to all business models. Depending on your model, acquisition strategy, and product or service will determine how to apply a cohort analysis.
Customer Cohort Analysis in Ecommerce
In order to best understand your eCommerce efforts, you need to understand how customers are engaging with your brand, website, and product. For example, you can use a cohort analysis to see if customers from certain marketing campaigns are making repeat purchases.
Related Resource: Key Metrics to Track and Measure In the eCommerce World
Customer Cohort Analysis in Mobile App Development
In order to best develop mobile apps, you need to understand what marketing strategy and product are impacting your key usage metrics. For example, you can use a cohort analysis to see how customers going through a certain onboarding flow are engaging with your mobile app.
Customer Cohort Analysis in Digital Marketing
In order to best build a digital marketing business, you need to understand what campaigns are performing best. For example, you can use a cohort analysis to see how customers are engaging through different marketing channels and campaigns.
Customer Cohort Analysis in Online Gaming
In order to best build an online gaming business, you need to understand what strategies are getting gamers to engage with your product the most. For example, you can use a cohort analysis to see how customers who play in specific tournaments engage with your game at later dates.
Related Resource: 10 Gaming and Esports Investors You Should Know
Customer Cohort Analysis in Cybersecurity
In order to best build a cybersecurity business, you need to understand what strategies are working best to retain customers. For example, you can use a cohort analysis to see how likely it is for customers to renew and expand their contracts that come from certain campaigns.
Related Resource: 10 Cybersecurity VCs You Should Know About
How to Build a Cohort Analysis for Customer Success
As we mentioned above a cohort analysis can be extremely useful for making better business and product decisions. One of the key aspects of this is how it can impact customer success and your retention efforts. Our template has a deep focus on customer retention and allows you to look back at different cohorts to see how you can improve retention efforts.
In our SaaS Metrics Guide we discuss the importance of retention. As we put it, “Poor customer retention isn’t just bad for finances; it’s an indicator that there could be a core issue with the solution itself. Customer retention rates are always a major feature of revenue development.”
At its core, a cohort analysis is best for measuring customer and revenue retention. While it could be an array of factors, understanding what cohorts are most likely to stay customers and have the highest lifetime value is essential. This may start with a top of funnel problem or may it is a product problem.
By taking aim at improving your net and gross revenue retention, a cohort analysis can be a valuable tool.
Customer Lifetime Value
As defined in our Customer Acquisition Costs Guide, “Customer lifetime value quantifies the value of what the customer acquisition actually brought into the business. Without customer lifetime value, you know how much every customer cost to bring in, but you don’t know how much those customers were worth.”
This idea goes hand-in-hand with gross and net revenue retention. If a cohort of customers has a higher customer lifetime value, why is that? Was there a particular onboarding process or channel that was prevalent that led to a higher LTV? If a cohort of customers has a lower lifetime value, why is that? Was a certain channel performing poorly? Did you remove a step from onboarding that may have reduced activation and in turn forced customers to churn sooner?
Measuring customer lifetime value is an incredibly valuable aspect of a cohort analysis. By finding the customers that are more likely to stick around, you can focus on what is working and apply it across your customer base and product moving forward.
Onboarding and Engagement
When analyzing different cohorts of customers you can look at things like onboarding and engagement campaigns during their lifecycle. Whether a software company or service provider, customer onboarding is constantly always changing. It could be a new questionnaire during onboarding or more touch points from a customer success representative. Oftentimes onboarding can be an integral part of how quickly a customer finds value and sets the tone moving forward. If there is a radical change to onboarding and customer engagement, it has the opportunity to impact their lifetime value and likelihood of churn.
New Products and Services
Startups are constantly testing different product and service offerings. Use a customer cohort analysis to determine how they impacted your revenue retention months later. If customers that activated a new feature or product are more likely to stay onboard, see how you can fit this into your customer success messaging and onboarding.
Discounts and Promotions
What good is offering a discount if you cannot see how it ultimately affects your revenue. If you offer customers a discount at the end of a quarter or month, see how likely they are to stay onboard once the promotion or discount expires. If you find customers that activated a promotion or discount ultimately churn sooner, it may be worth putting that time and energy into cohorts of customers who you know have a higher lifetime value.
What are the Benefits of Customer Cohort Analysis?
As we’ve alluded to throughout this post, there are countless benefits to building and analyzing different customer cohorts. Learn more about a few key benefits below:
Inform Product Development
Cohort analysis can be used to break down segments of customers based on their product usage. Because of this, you can understand what product features lead to your best customers. This can be used to inform product development and strategy down the road.
Related Resource: How SaaS Companies Can Best Leverage a Product-led Growth Strategy
Focus on Acquisition Channels
Another major benefit of analyzing different customer cohorts is by breaking down different acquisition channels and strategies. By evaluating cohorts based on their source channel, you’ll be able to better understand what strategies and channels you should be investing in further.
Improve Customer Success & Onboarding
Looking at the bottom of your funnel, you can analyze your customers by the customer success and onboarding strategies used. For example, if you are testing a dedicated customer success representative for a certain set of customers you’ll be able to determine if it is worth rolling out this strategy across all of your customers.
Our Customer Retention Cohort Analysis Google Sheet Template
Building a customer retention cohort analysis can be a time suck which is why we are open sourcing our template with you today. Our template provides entry of customer data in two different ways, in addition to supporting tracking over quarters and months.
Everything you need can be found in the instructions tab of the template. This template will allow you to get data from the previous eight quarters and is completely automated. A quick explainer:
Decide if you want to enter row level data of your customers, simply head to the “Customer Data” tab, remove all of the fake data we’ve entered, and enter in your own data. This will automatically fuel the other tabs and be the start of your cohort analysis.
If you’d prefer to enter simple counts of your customers at the start and end of different time periods, head to the “Customers Retained Count” tab. From here, you can enter the total customers acquired and churned during a period.
Get The Ultimate Customer Retention Cohort Analysis Template for SaaS
Use our template to correlate key business decisions to your customer acquisition and retention efforts. As your company scales, iterates, innovates and creates processes, you would hope to not only acquire customers at a faster pace, but also retain them longer, correct? One would assume as product/market fit is found, domain experts are hired and new campaigns are launched that customer retention gets better… but how do you know?
With our free template you’ll be able to:
- Easily enter customer lifetime information in a pre-formatted section.
- Generate a monthly and quarterly cohort analysis of your customer retention efforts.
- Compare your cohort analysis against company milestones to understand what is generating the highest-quality customers for your business.
Download our template, by clicking the image below: