A customer cohort analysis helps you better understand how your customers interact with your product. It can help you identify common patterns among groups of customers and inform your marketing and product development strategies. We’ll cover details about exactly what it is and why it’s such a crucial component of your overall strategy to fight churn.
What is customer cohort analysis?
A cohort is a group of people who share common characteristics or experiences within a defined period of time. A customer cohort is a group of customers who share a common characteristic or experience within the context of your product or service. Customer cohort analysis is the process of tracking and analyzing how a group of customers interact with your product or service over time. Businesses use a customer cohort analysis to understand customer behavior and trends. A customer cohort analysis is performed by grouping people based on their common characteristics. Customer interactions and behavior are then analyzed in the context of this common characteristic.
Types of cohort analysis
We’ll dive into the two most common types of customer cohort analysis: acquisition cohorts and behavioral cohorts.
Acquisition cohorts are groups of customers who share a common characteristic such as signing up for a service during the same period of time, or purchasing a product within the same price range. These could also be based on demographic characteristics such as geographic location or your customer’s occupation.
Behavioral cohorts are groups of customers who share a common behavior such as using a product or service in the same way, using certain product features more frequently, or consistently engaging with your company through social media. These characteristics are based on your customers actions rather than facts about them.
Example of a customer cohort analysis
Let’s say you own an online store that sells home goods. You decide to group your customers into three different cohorts, based on when they made their purchases:
- Cohort 1: customers who made a purchase within the last 30 days
- Cohort 2: customers who made a purchase between 31-60 days ago
- Cohort 3: customers who made a purchase more than 60 days ago
For each of those cohorts, you can then track metrics that you feel will be important to the development of your business strategies. Some of those metrics may include:
- Number of total purchases
- Average order value
- Other buyer behavior (how often they visit your site, how long they stay, etc.)
Once you’ve collected this data, you can start looking for patterns. You might notice, for example, that cohort 1 has a much higher number of purchases than cohort 3. This could be due to a number of factors such as the time of year (does your time window include the holiday season?) or the types of products they purchased. Perhaps your customers buy items in very small time windows and go a long time between purchases.
By understanding these patterns, you can make changes to your business strategy that can help improve customer experience and increase sales. For example, if you notice fewer sales in cohort 3, you can offer them personalized discounts to encourage further purchases, or you can create a marketing campaign specifically targeted to them.
Why use customer cohort analysis?
Customer cohort analysis can help businesses improve customer acquisition, capitalize on customer behavior, and boost customer retention. This type of analysis can also help businesses identify possible areas of improvement and make changes to increase customer satisfaction, overall building a more successful and profitable product.
Steps to perform a cohort analysis
1: Determine the right queries to ask
Before starting your customer cohort analysis, determine the right set of questions to ask and what you’re looking to get out of your analysis. This will help you focus the process and ensure that you’re gathering productive data.
2: Define the metrics
Next, define the metrics you will use to track and analyze customer behavior. These could include things like customer acquisition rate, customer churn rate, or customer lifetime value.
3: Define your cohorts
Once you have your metrics, focus on defining the specific cohorts you’ll be analyzing. Decide which characteristics you think will help you yield the most relevant data, and break your customers into cohorts from there.
4: Perform the cohort analysis
This step will involve collecting data, analyzing that data, and then interpreting the results.
5: Evaluate test results
Once you’ve actually collected your data, interpreting and evaluating your results will help you determine what’s going on with your customers’ behavior. This is where you might start to see patterns and determine what you should change, if anything, to continue to improve. If you feel that your chosen cohorts haven’t provided useful data, go back and choose new cohort characteristics to run a new analysis.
Understand your customers, reduce churn
Customer cohort analysis is a critical analysis tool that can provide insights into how your customers are interacting with your product and where your service might be falling short. Giving some attention to your customer cohorts can ultimately help you improve customer satisfaction and fight churn.
If you’re looking for more foundational Customer Success information, read through the rest of our Churnopedia, an extensive glossary that can help boost your strategies by offering a deeper understanding of SaaS business.