Fixing Empty Static Cohorts In PostHog With Variables

by Kenji Nakamura 54 views

Introduction

Hey guys! Are you experiencing issues while creating static cohorts from insights that utilize variables in PostHog? You're not alone! This article dives deep into a specific bug that causes static cohort creation to fail when variables are involved in your SQL queries. We'll explore the problem, understand how to reproduce it, and discuss the implications. So, if you're scratching your head over empty cohorts, this guide is for you! In this comprehensive guide, we'll walk you through the intricacies of creating static cohorts from insights with variables in PostHog, address common issues, and provide practical solutions. Understanding the nuances of cohort creation is crucial for leveraging the full power of PostHog in your analytics endeavors. So, let's dive in and get those cohorts working!

Understanding the Bug: Static Cohort Creation with Variables

The core issue lies in how PostHog handles variables within SQL queries when creating static cohorts. When a query uses variables, such as {variables.days}, the system sometimes fails to correctly interpret these variables during the cohort creation process. This leads to an empty cohort, which can be frustrating and time-consuming. The problem specifically arises when you try to create a static cohort from an insight that uses variables. For instance, consider a scenario where you want to create a cohort of users who viewed a specific page within the last few days. You might use a query similar to the one below:

SELECT
 person_id
FROM events
WHERE
 event = 'pageview'
 AND timestamp >= now() - INTERVAL {variables.days} DAY
GROUP BY person_id
LIMIT 100

In this query, {variables.days} represents a variable that defines the number of days to look back. The problem is that PostHog may not correctly substitute this variable when creating a static cohort, resulting in an empty cohort. This bug can impact your ability to create targeted cohorts based on dynamic timeframes or other variable conditions. It's essential to understand the root cause and find workarounds to ensure accurate cohort creation.

Detailed Bug Description

To provide a more detailed understanding, let's break down the bug further. The primary symptom is that when a user attempts to create a static cohort from an insight, and that insight's query includes variables, the creation process fails, and the resulting cohort is empty. The variable substitution mechanism appears to be the point of failure. Instead of correctly interpreting and replacing the variable with its actual value, the system either ignores it or misinterprets it, leading to an incorrect or incomplete query execution. For example, in the provided SQL query:

SELECT
 person_id
FROM events
WHERE
 event = 'pageview'
 AND timestamp >= now() - INTERVAL {variables.days} DAY
GROUP BY person_id
LIMIT 100

The {variables.days} part is intended to dynamically adjust the time frame based on a defined variable. However, when creating a static cohort, this variable is not being resolved correctly. If you were to replace {variables.days} with a static value, such as 7, the query would work as expected. This highlights that the issue is specifically related to the variable handling during static cohort creation. Understanding this specific behavior is key to finding effective solutions and workarounds.

Steps to Reproduce the Issue

To help you better understand and potentially troubleshoot this issue, let's outline the exact steps to reproduce the bug. By following these steps, you can confirm if you're encountering the same problem and gather more information for debugging.

  1. Create a SQL Insight with a Variable:
    • Start by creating a new insight in PostHog.
    • Select the SQL insight type to write a custom query.
    • Write a SQL query that includes a variable. For example, use the query provided earlier:
SELECT
 person_id
FROM events
WHERE
 event = 'pageview'
 AND timestamp >= now() - INTERVAL {variables.days} DAY
GROUP BY person_id
LIMIT 100

  1. Try to Create a Static Cohort from the Insight:

    • Once you have saved your insight, navigate to the options menu (usually represented by three dots) for that insight.
    • Select the option to "Create Static Cohort".

  2. Observe the Empty Cohort:

    • After initiating the cohort creation, navigate to the cohorts section in PostHog.
    • You will find that the cohort you just created is empty, meaning it contains no members.

By following these steps, you can reliably reproduce the bug. This consistent reproduction is crucial for developers and users to understand the scope of the issue and work towards a resolution.

Real-World Implications and Additional Context

The inability to create static cohorts from insights with variables has several real-world implications. For example, if you're trying to segment users based on their activity over a dynamic timeframe (e.g., the last 30 days), this bug will prevent you from creating an accurate static cohort. This can impact your ability to target specific user groups for campaigns, analyze user behavior over time, and perform other crucial analytics tasks. The discovery of this bug in a support ticket (https://posthoghelp.zendesk.com/agent/tickets/34771) underscores its practical impact on PostHog users. Understanding these implications helps prioritize the issue and drives the need for a timely solution. Moreover, having a clear understanding of the context in which the bug was discovered can provide additional insights into its potential causes and solutions.

Debugging and Troubleshooting the Issue

When you encounter this bug, there are several steps you can take to debug and troubleshoot the issue. These steps can help you gather more information, identify potential workarounds, and assist the PostHog team in resolving the bug.

  1. Verify the Variable:

    • Ensure that the variable you are using is correctly defined and accessible in your PostHog project settings.
    • Check the spelling and syntax of the variable name in your SQL query.

  2. Test with Static Values:

    • Replace the variable in your query with a static value (e.g., replace {variables.days} with 7).
    • Try creating the static cohort again. If it works, this confirms that the issue is specifically related to the variable handling.

  3. Examine the PostHog Logs:

    • Check the PostHog server logs for any error messages or warnings related to cohort creation or variable substitution.
    • Logs can provide valuable insights into what might be going wrong during the process.

  4. Check Debug Information:

  5. Simplify the Query:

    • Try simplifying your SQL query to isolate the issue.
    • Remove any unnecessary conditions or clauses and see if the cohort creation works with a basic query.

  6. Consult the PostHog Community:

    • Reach out to the PostHog community or support channels for assistance.
    • Sharing your specific scenario and debugging steps can help others identify potential solutions or workarounds.

By systematically following these debugging steps, you can gather valuable information that will aid in resolving the issue. Effective debugging not only helps you find immediate solutions but also contributes to the overall stability and reliability of your PostHog setup.

Potential Workarounds and Solutions

While the PostHog team works on a permanent fix, there are several potential workarounds you can use to mitigate the issue. These workarounds may not be ideal in all situations, but they can help you create the cohorts you need in the meantime.

  1. Use Dynamic Cohorts:

    • Instead of creating a static cohort, consider using a dynamic cohort. Dynamic cohorts are continuously updated based on the defined criteria, so they can adapt to changes in your data.
    • While dynamic cohorts may not be suitable for all use cases, they can be a viable alternative if you need a cohort that reflects the most current data.

  2. Create Multiple Static Cohorts:

    • If you need a static cohort for a specific timeframe, you can create multiple static cohorts with different date ranges.
    • This approach can be more time-consuming, but it allows you to achieve the desired segmentation.

  3. Pre-calculate Cohort Members:

    • You can run the SQL query with the variable replaced by a static value and manually create a list of person IDs.
    • Then, you can use this list to create a static cohort using PostHog's API or UI.

  4. Refactor the Query (If Possible):

    • In some cases, you may be able to refactor your SQL query to avoid using variables altogether.
    • For example, you could use a fixed date range instead of a variable-based timeframe.

  5. Wait for the Bug Fix:

    • The PostHog team is aware of the issue and is working on a fix. Keep an eye on the PostHog release notes for updates.
    • In the meantime, you can use one of the workarounds mentioned above.

While these workarounds can help you create cohorts in the short term, it's crucial to remember that they are temporary solutions. The ideal solution is for PostHog to correctly handle variables during static cohort creation. Therefore, staying informed about bug fixes and updates is essential.

Best Practices for Cohort Creation in PostHog

To ensure you're making the most of cohorts in PostHog, let's review some best practices for cohort creation. Following these guidelines can help you avoid common pitfalls and create effective segments for your analysis.

  1. Clearly Define Your Cohort Criteria:

    • Before creating a cohort, clearly define the criteria you want to use to segment your users.
    • What specific behaviors, events, or properties should be included in the cohort?

  2. Use Descriptive Names:

    • Give your cohorts descriptive names that clearly indicate their purpose.
    • This makes it easier to identify and manage your cohorts over time.

  3. Document Your Cohorts:

    • Add a description to your cohorts to explain their purpose and criteria.
    • This is especially helpful if you're working in a team or if you need to revisit the cohort later.

  4. Regularly Review Your Cohorts:

    • Cohorts can become outdated as your data changes.
    • Regularly review your cohorts to ensure they are still relevant and accurate.

  5. Use Dynamic Cohorts When Appropriate:

    • Dynamic cohorts are a great option for segments that need to be continuously updated.
    • Consider using dynamic cohorts for use cases such as active users, churn risk, or new sign-ups.

  6. Test Your Cohorts:

    • After creating a cohort, test it to ensure it contains the expected members.
    • You can use PostHog's query builder to verify the cohort membership.

By following these best practices, you can create cohorts that are accurate, effective, and easy to manage. Adhering to these guidelines will help you unlock the full potential of cohorts in your analytics workflow.

Conclusion

In conclusion, the bug affecting static cohort creation with variables in PostHog can be a significant hurdle, but understanding the issue and utilizing the outlined workarounds and debugging steps can help you navigate this challenge. Remember, staying informed and proactive is key to ensuring your analytics workflows remain smooth and effective. By adopting best practices for cohort creation and staying engaged with the PostHog community, you can continue to leverage the power of cohorts for your analytics needs. The PostHog team is actively working on resolving this issue, so keep an eye on future updates and releases. Happy cohorting, guys!