Introduction
As an SaaS business owner, you always aim to improve profitability. To do so, you need to improve the lifetime value of customers while reducing the acquisition expenses. The best thing you can do regarding this is to focus on improving the retention rate. It’s a crucial metric not only for boosting profitability but also for developing strong and lasting customer relationships.
Retaining customers costs less than acquiring new ones. To improve retention, understanding customer behavior over time is essential. This is where cohort retention analysis can help you. In this post, we will tell you how to use cohort analysis to retain customers.
What is cohort analysis?
Cohort analysis is a method of segmenting your customers based on shared characteristics in a specific time frame. For instance, you can make a cohort of customers acquired in the same month. These cohorts can be tracked over time to analyze trends in behavior.
Cohort analysis groups them based on shared experiences, such as the date of their first purchase, sign-up date, or product usage. By analyzing how different segments behave over time, you can get valuable insights into user behavior. It will help you identify what influences retention.
A Stepwise Guide to Using Cohort Analysis to Improve Retention
You may have been thinking about how cohort analysis works and how you can use it to retain more customers. Let’s figure this out by exploring a detailed guide on it.
Step 1: Define the Cohort Groups
The first step you need to follow is defining shared characteristics on which basis you can group your users. The following are some of the most common segments.
Acquisition Cohorts: In this group, you will place customers based on their acquisition. You can make subgroups of customers who signed from the same channel or on the same day. Similarly, you can also make a cohort of customers based on the date they made their first purchase.
Behavioral Cohorts: It involves grouping customers based on their specific actions or behaviors. For instance, you can make a segment of users who have engaged with a similar feature.
Demographic Cohorts: It’s one of the most basic types of cohorts. You have to group customers based on their location and age.
Acquisition cohorts are most commonly used for retention purposes For example, you can analyze users who signed up in January and compare them to those who signed up in February to see how their retention rates vary over time.
Step 2: Choose the Key Metrics to Track
Once you define cohorts, the next step is to choose and track metrics that matter most for your business. The core metric you need to focus on is retention rate. However, it never means you can ignore the rest. You should also track:
Churn Rate: The percentage of users who stop using your product after a certain period.
Customer Lifetime Value: The total revenue you expect to earn from customers over their entire lifecycle.
Engagement Rate: The percentage of users who perform key actions or interact with a specific feature.
Repeat Purchase Rate: The percentage of customers who return for a second purchase.
These metrics will give you a clear understanding of how users behave after acquisition.
Step 3: Set a time frame for Analysis
Only making cohorts and tracking metrics isn’t enough to develop retention strategies. You need to analyze them in a specific time frame. It will help you gain meaningful insights and make informed decisions. The time frame you choose should depend on your product type and customer journey.
If you have high-frequency products like mobile apps or social media platforms, you can opt for a daily or weekly timeframe. It is useful for tracking rapid changes in behavior. Meanwhile, if you’re running a subscription-based business model, monthly cohorts can be ideal for analysis. It will offer a broader view of user retention over time.
Step 4: Visualize Data
Analyzing cohorts in a specific time frame enables you to collect useful data. Now, it’s time to visualize it. You can present it in a cohort table or a heat map for visualization. The cohort table lists cohorts in rows and time intervals in columns. Each cell shows the percentage of users retained during each interval. For example, if you’re analyzing monthly retention, the table will show what percentage of users are still active after each month.
A heat map, on the other hand, highlights retention patterns using color scales. The darker the color, the higher the retention. Heat maps are particularly useful for spotting retention trends quickly. This data visualization helps you spot cohorts with the highest retention rates and significant drop-offs.
Step 5: Analyze the Results
After data visualization, you have to analyze it to find trends. Key things you need to focus on are listed below.
- Identify cohorts with the highest retention rate and analyze what differentiates them. You should know whether a product update or new marketing campaign is improving retention rate.
- Investigate the factors that may have led to low retention, such as poor onboarding, technical issues, or a mismatch in customer expectations.
- Identify patterns like whether users tend to drop off after a specific period or seasonal factors influence retention.
Step 6: Take Action on Insights
It’s the final and most crucial step. It involves turning your cohort analysis insights into actionable strategies. You can use these insights to:
Improve Onboarding: If you see high drop-off rates within the first month, it indicates an issue with your onboarding process. You can focus on improving it to get desired outcomes. Retention.
Tailor User Engagement: If you notice certain cohorts engaging with specific features, you can use this information to personalize communication. You can also use it for product recommendations to improve customer engagement.
Adjust Pricing: Sometimes, customers churn right after they move from a free trial to a paid plan. It hints that you need to reconsider your pricing model or offer more affordable options to retain customers.
Now, you are all set to leverage cohort retention analysis to improve retention rate. You can use Baremetrics to make cohorts, analyze metrics, and find patterns. Its user-friendly interface makes it easy for you to conduct this analysis.
