Top 9 Cohort Analysis Tools
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How do you measure your long-term success? Undoubtedly, you can acquire billions of potential customers. But how does it matter if they don’t stick around? To ensure the long-term health of your business, you need to understand seasonality, customer lifecycle, and customer behavior. And it all begins with cohort analysis tools.
Read on to learn about cohort analysis tools’ features, benefits, popular options, and how to select one for your organization.
What Is Cohort Analysis?
Cohort analysis is an analytics technique where users are grouped based on shared characteristics or behaviors. Then, these groups (cohorts) are examined over a specified period. Analyzing their behavior over time allows you to identify patterns and trends, understand how users interact with your product, and determine the most effective retention strategies.
This type of analysis enables product people to understand user interactions with the product better. Besides, it allows you to make data-driven decisions to improve customer satisfaction and retention and boost revenue.
The steps typically involved in the cohort analysis process include:
- Extract Data: Raw data is pulled from your data warehouse. If required, it is exported into product analytics software. Here, user attributes can be joined and segmented further.
- Create Cohort Identifiers: Group user data into different buckets. They can be – date joined, date of first purchase, all mobile devices at a particular place and time, etc.
- Calculate Lifecycle Stages: The time between events attributed to each customer is measured to calculate lifecycle stages.
- Visualization: Tables, charts, and graphs visually represent user data comparisons. This helps calculate the aggregation of multiple dimensions of user data.
The power of cohort analysis tools lies in the fact that you need not do any of the above steps manually to analyze a cohort. Your cohort analysis software will easily aggregate, segment, and visualize granular patterns of different cohorts. Here are some cohort analysis tools examples. Learn what you can do with cohort analysis:
- Evaluate the effectiveness of your onboarding process.
- Assess how different cohorts adopt and use specific features
- Understand and improve retention rate.
- Identify factors or events that lead to increased churn.
- Assess the impact of product updates or changes on user behavior.
- Shift the marketing budget at the right time in the customer lifecycle.
- Recognize when to end a trial or an offer to maximize value.
- Discover trends and commonalities that can inform product development, marketing strategies, and user engagement initiatives.
- Gain ideas for A/B testing in pricing, upgrade path, etc.
Benefits of Cohort Analysis Tools
Cohort analysis aims to uncover patterns. You can easily compare the performance and behavior of different cohorts over time. This empowers you with insights into how to engage and retain your users.
1. Improve Customer Retention
Picture this: Your users tend to churn, and you need to identify behavior patterns that may be causing this churn. Through cohort analysis, you can compare the performance and behavior of different cohorts contributing to churn. Identifying specific areas for improvement, such as onboarding processes or product features, helps you improve retention and reduce churn.
2. Identify Trends and Patterns
Cohort analysis helps you gain the ability to identify trends and patterns in user behavior. This can include understanding how new improvements impact user engagement, purchase frequency, or other relevant metrics. You can make data-driven decisions and tailor your strategies by understanding the patterns among different cohorts.
3. Improve Stickiness and Customer Lifetime Value
Once users find value in your product, they’ll likely stick around for longer. Cohort analysis helps you understand when your users drop off and what they do or don’t with your product. You can identify cohorts consistently engaging or not engaging with specific features. This information helps tailor your strategies to enhance stickiness and increase the overall LTV of your user base.
4. Understand User Behavior
Cohorts can be divided based on various parameters like sign-up date, user type, or geographic location, etc., to uncover insights into user behavior. This helps you understand how user groups evolve and reveal patterns within cohorts. A nuanced understanding of user behavior in different cohorts enables strategic decision-making.
Key Features to Look for in Cohort Analysis Tools
When choosing cohort analysis tools, simplicity is key. Opt for user-friendly options with these features:
- User-friendly Interface: You don’t need flashy tools only data analysts can use. Invest in product analytics tools with a simple, user-friendly interface for easy navigation.
- Clear Information Visualization: Choose platforms that make data interpretation a breeze through clear and concise graphs. Always remember these tools should make insights easy for everyone (not just product teams) to comprehend.
- Consider your Budget: Don’t opt for tools that make you pay for costly ETL pipelines or opaque storage and compute costs. Warehouse-native tools like Houseware can be cost-effective. It connects directly to your data warehouse and gives you value from Day 1.
- Active Notifications: A good product analytics solution keeps you informed. Active notifications ensure you and your teams stay on top of your data.
- Compatibility and Integrations: The tool should integrate seamlessly with your existing data sources and destinations like Snowflake, BigQuery, and Redshift.
- Customization: Ensure the software allows you to tailor cohorts based on your needs. It should provide ample filters for user properties and event behavior to help you create cohorts.
List of Top 9 Cohort Analysis Tools
Many cohort analysis tools are available, each with its own strengths and weaknesses. Below, we’ve compiled a list of 9 cohort analysis tools with their ratings, pros, and cons.
Houseware
Houseware has cohort analysis as one of the built-in features. It automatically captures all event data in your product (clicks, swipes, views, form-fills, and more). From there, building useful visualizations on product usage and retention is extremely simple.
Product teams can easily see how customers most (and least) likely to churn behave. In addition, you can also analyze what features they use the most, how often they log in, and what their common workflows look like.
In Houseware, you can create cohorts by applying appropriate filters on top of user properties (city, region, plan type, device type, etc.), event behavior, or a combination of both.
Houseware also has an excellent built-in retention dashboard to help you visualize retention through a retention heatmap and a retention curve.
G2 Rating:
4.6 of 5 ⭐️
Pros:
- Growth-friendly and easy to scale.
- Cost-effective than its counterparts.
- Easier to use for product, marketing, and customer success teams.
- Beyond cohort analysis, Houseware offers broader product analytics features like Flows, Funnels, Trends, and more.
Cons:
- Relatively new in the market.
Google Analytics
Google Analytics is an analytics service offered by Google that is ideal for marketers and small businesses. It tracks and reports website and mobile app traffic and user engagement events. The cohort analysis feature of Google Analytics provides a graphical representation of user behavior and a table showing user retention for different cohorts.
Although Google Analytics can be tedious to set up, once you have the correct event tracking in GA, you can compare different cohorts to see which actions will likely drive more excellent retention.
G2 Rating:
4.5 of 5 ⭐️
Pros:
- It is free of cost.
- User-friendly interface.
Cons:
- The possibility to only define cohorts based on acquisition dates.
- Tracking returning sessions with several devices is not accurate.
- No in-depth insights.
Mixpanel
Mixpanel is a simple product analytics tool that allows PMs to track and analyze in-app product engagement. The cohort analysis feature from Mixpanel can be used to identify patterns and engage your users. You can create cohorts based on user properties such as sign-up date, first purchase date, referral source, geographic location, device type, or another custom event/property.
G2 Rating:
4.6 of 5 ⭐️
Pros:
- You can export cohort analysis data easily for further analysis
Cons:
- With the free Mixpanel plan, you can’t save cohorts for future use
- Enterprise-level pricing is expensive
- Time-consuming cohort creation process
Amplitude
Amplitude is another product analytics tool that enables you to select a combination of behaviors and profile properties to create cohorts. With Amplitude, you can see the specifics of your customers’ behaviors. This enables PMs to make data-driven decisions to enhance their customer’s experience with your product.
With Amplitude, you can select any combination of behaviors and profile properties. Also, you can build custom cohort definitions based on your particular parameters.
G2 Rating:
4.5 of 5 ⭐️
Pros:
- Highly customizable and flexible
- Quick and simple setup
Cons:
- Cohort analysis feature is available to users on Plus, Growth, and Enterprise plans only.
- Steep learning curve — requires significant training.
- Slow loading speed.
- High price point compared to other tools.
Kissmetrics
As a customer engagement automation platform, Kissmetrics offers powerful analytics features. It provides behavioral analytics, segmentation, and email campaign automation. Kissmetrics can run cohort analyses focused on website conversion events. It can creat cohorts based on demographics, user behavior, referral sources, events, and specific time frames.
G2 Rating:
4.1 of 5 ⭐️
Pros:
- Powerful data visualization options
- Highly customizable
Cons:
- Difficult to install.
- Not well-suited for small businesses.
- Limited integration with other tools.
SQL
Building your own cohort analysis is easy if you are a pro at using SQL. You can use it to smoothen customer onboarding and enhance product development.
Cohort Analysis through SQL is based on retention calculation. You need to count the users who come back regularly on a weekly (or monthly) basis. Then, group them according to the time they signed up. Using SQL, you can generate a new table, group data into different cohorts, calculate retention rate, and perform cohort analysis.
G2 Rating:
4.4 of 5 ⭐️
Pros:
- Seamless integration with data visualization tools.
- SQL databases can handle large datasets also.
Cons:
- Challenging for non-technical users.
- Database schema changes influence the analysis.
Heap
Heap, a web and mobile app analytics platform, offers cohort analysis as one of its features. The platform helps businesses understand user behavior on their websites or mobile applications. Cohort analysis in Heap allows users to group individuals who share a common characteristic or perform a specific action during a defined time frame.
Organizing user cohorts according to their activities on your product provides valuable insights into the diverse ways users engage with your platform. This enables you to customize your communications to suit their preferences and utilize external data sources to establish user segments that faithfully capture the entire customer journey.
Additionally, Heap provides features like conversion tracking and funnel analysis, empowering businesses to comprehend the influence of various marketing campaigns on user behavior.
G2 Rating:
4.4 of 5 ⭐️
Pros:
- Intuitive and user-friendly interface.
- Comprehensive event tracking allows for detailed analysis of user interactions.
Cons:
- Pricing may be a concern for some businesses.
- Steep learning curve, especially for leveraging advanced features.
Pendo
Pendo is a product experience platform that helps businesses understand and improve the user experience of their products. Its analytics dashboard can help you conduct cohort analysis by sorting retention data by segment, cohort size, or date range to filter results. It enables you to see what percentage of each cohort is retained monthly.
You can also switch between visitors vs. accounts, weekly vs. monthly views, and measure retention for specific segments.
G2 Rating:
4.4 of 5 ⭐️
Pros:
- Has an intuitive and user-friendly interface.
- Offers a wide range of tracking capabilities like user behavior, feature usage, and more.
Cons:
- It can be pricey, especially for smaller businesses or startups.
- Has a steep learning curve for non-technical users.
User Pilot
Userpilot is a product growth platform that helps you drive user engagement and retain customers.
The cohort retention analysis feature from User Pilot empowers you to measure retention easily. You can filter the retention data by the number of web sessions, price plans, etc. to analyze retention in detail. You can also segment the users based on sign-up date, in-app behavior, and other attributes. Hence, you can easily create acquisition and behavioral cohorts.
G2 Rating:
4.6 of 5 ⭐️
Pros:
- Intuitive user interface.
- Easy to install.
Cons:
- Steep learning curve. It can be a bit confusing sometimes.
- Doesn’t offer adequate integration possibilities.
The true strength of cohort analysis tools lies in their visualizations. The charts allow you to compare a metric across various data segments over time. This helps you to understand your users’ behavior and supports you in planning future strategies.
Conclusion
Cohort analysis is a robust technique that can help you determine what drives your growth, retention, engagement, and revenue. All in all, the above nine tools are great options for getting started with cohort analysis. Selecting the best one would depend upon your requirements. Keep in mind the tool you choose must be growth-friendly. It should empower your growth when you scale your operations without burning your pockets.
Ready to start running a cohort analysis? Get a personalized demo on how to run cohort analysis to drive business growth with Houseware.
FAQs
1. What is an example of cohort analysis data?
Here is an example of cohort analysis data. Let’s consider a scenario where you want to understand the retention and churn for a mobile game app. The first attribute for a cohort can be “install date.” Here, users who installed the game in January 2023 will form the January cohort. Different cohorts can be compared to understand which cohorts displayed high or lower retention rates and the possible reasons for the same.
2. What are the 3 types of cohort analysis?
Time-based cohorts: Group of users acquired during a specific time frame, event, or marketing channel. Analyzing these cohorts can help you determine the value of different acquisition methods.
Behavioral cohorts: Groups of users divided based on their behaviors and actions with your product. Various cohorts can be studied to determine how long they have actively engaged with the product.
Size-based cohorts: Groups of users divided based on a specific attribute, such as the size of their initial purchase, the number of items in their cart, or their subscription tier.
