Cohort Analytics 101
What is a Cohort Analysis?
A cohort analysis groups object by certain characteristics within a defined time span. These groups, also known as cohorts, are key to identifying trends for object behaviors and performance.
Why is It Important to B2B Software Companies:
Analyzing performance by cohort offers several distinct advantages over analyzing data using a generic aggregate analysis. Namely, a cohort analysis provides deeper insights into trends and behaviors that might not be immediately apparent otherwise. Furthermore, a cohort analysis helps companies:
- Identify Patterns: Companies use cohort analysis to identify patterns and trends that might not be visible in aggregate data. By comparing groups with common characteristics over time, companies can spot changes in behavior, preferences, or performance that could inform strategic decisions. For example, you could uncover whether user engagement drops off after a certain period or if new customers have different buying patterns compared to long-term customers.
- Reveal Impact: Cohort analysis helps isolate the impact of specific events, changes, or strategies on behavioral patterns. For instance, you could analyze how a new feature release affects user behavior and engagement. Does it increase the number of monthly active users or introduce new user segments to your product? By understanding this information, companies can gain insights into the feature’s success or areas for improvement.
- Drive Effective Decision-Making: By understanding how different cohorts perform, companies can make more targeted and informed decisions. Being able to identify high-performing cohorts based on defined characteristic, helps companies efficiently allocate resources accordingly. For instance, if you realize existing customers in the Oil and Gas sector have the highest lifetime value, you’ll want to invest more in sales and marketing efforts that target Oil and Gas. Doing so optimizes budget and effort.
Challenges With Analyzing Cohorts
The benefits of running a cohort analysis are clear; but most companies are still not running a cohort analysis regularly. So, if a cohort analysis is so impactful, you might be wondering why. Well, to start, it’s not easy to run cohort analyses in an automated fashion.
Running an automated cohort analysis can be challenging due to several complexities inherent in handling and interpreting the data. Firstly, a cohort analysis depends on accurate and consistent data. Inconsistent or incomplete data can lead to inaccurate insights. Ensuring data quality often involves data cleansing, validation, and integration from various sources.
Additionally, a cohort analysis requires detailed data on individual user actions or customer behaviors. Gathering this granular data can be resource-intensive and might involve tracking mechanisms, event logging, and integration with multiple systems.
Additional Considerations When Pursuing a Cohort Data Strategy
There are several considerations that should also be taken into account for those looking to run a new cohort analysis.
- Time-Dependent Factors: A cohort analysis spans an extended period of time. This means external factors like seasonality, market changes, or economic trends can impact the results. Isolating the effects of these factors from cohort insights can be complex. Nevertheless, it is worth considering when looking at the results of your analysis.
- Cohort Selection: Choosing appropriate cohort time periods is crucial. If your cohort is too small, the data might not be representative. If they’re too large, subtle differences between user groups might be masked. Selecting the right cohort size and duration requires specific knowledge of your domain.
- Long-Term Analysis: Running a cohort study requires tracking cohort data over extended periods of time. As such, companies need historical data to observe trends accurately. If this data is not available, it’s important to be patient! Continue tracking the right information while you wait for the cohorted insights to become available.
About Discern
Discern is a data analytics company designed to help B2B companies scale effectively. With deep business analytics across Finance, Sales, Marketing and Customer success, Discern provides a holistic view into company performance against targets. Our data visualization helps identify trends that:
- Reduce customer churn rates
- Increase customer lifecycle lengths
- Shorten the sales and marketing life cycle
- Increase customer acquisition.
Click here to book a demo of our cohort analysis capabilities or click here to read our five star reviews on G2.
