Is Your Community Losing Members? How to Perform a Churn Analysis

High churn rates can look alarming at first glance. But a well-rounded understanding of who’s leaving and why allows community managers to make data-informed adjustments rather than reacting to surface-level metrics.

One of the most common missteps when examining churn is taking it at face value. Many community managers ask, “Is a X% churn rate good or bad?” without delving into what the rate actually represents. A churn percentage without context misses details about why members leave or go inactive.

To get to the core of the issue, you want to consider the underlying factors—such as engagement levels, member behaviors, and any recent community changes. By focusing on these elements, you can zero in on specific areas that need attention rather than trying to solve a blanket churn problem.

Gross Churn vs. Net Churn: Masking Churn Problems

Another key aspect of analyzing churn is distinguishing between gross churn and net churn. Gross churn reflects the total number of community members who leave or go inactive within a given period, giving a direct look at attrition without accounting for new members. Net churn, on the other hand, factors in both departures and new members gained, offering a clearer view of community growth or shrinkage over time. While gross churn shows potential retention issues, net churn highlights the community’s overall health and momentum by balancing losses against new joins.

These are two different metrics, yet both tend to appear simply as “churn.” It’s important not to oversimplify churn by focusing only on net churn, as this can mask retention challenges. Both net and gross churn serve distinct purposes, and both are valuable metrics. Understanding which metric you’re using—and why—will give you a clearer view of your community’s overall health.

How to Perform a Community Churn Analysis

After understanding what your churn metrics are telling you, the next step is to conduct a targeted churn analysis. This analysis will help you pinpoint specific areas for improvement, identify patterns, and design strategies to improve retention. Here’s a guide to get started:

• Define what constitutes “churn” and “active” within your community. Decide what “churn” means for your community. For some, churn might mean inactive accounts; for others, it could indicate decreased interaction with key features (e.g., posts, Q&A, resource downloads). Focus on metrics that reflect your community’s core purpose. Also, consider both active participation and passive membership. A “churned” member in one community might just be a “passive” member in another.
• Collect data. Dive into data that reflects user profiles (demographics and role or tenure within the community), engagement (activity frequency, interaction types, login patterns), behavioral trends (actions leading up to churn), and health indicators (response rate, discussion quality, and sentiment). This data will serve as the foundation for your analysis.
• Segment members. Break down your audience into meaningful segments (e.g., new members, veteran members, frequent contributors, or infrequent lurkers) to see how churn manifests across each group. Track top contributors or influential members and monitor their engagement separately as their departure can disproportionately impact overall community health and engagement.
• Identify churn drivers: Churn can be symptomatic of different issues depending on who’s leaving. If mostly casual members are churning, it might suggest onboarding or content relevance issues—they may not find what they need, see enough activity, or feel guided. If core members are churning, however, it could point to burnout, changes in community that don’t align to their interests, or gaps in content progression, such as a need for more advanced resources or opportunities for recognition. Understanding these drivers helps you address specific needs.
• Analyze timing of churn: Look for patterns in when members go inactive. Are there drops in activity after certain community changes? Do new members tend to churn shortly after joining? By recognizing these patterns, you can address root causes more effectively.
• Survey inactive members: Send a re-engagement survey to understand why they stopped participating. Use questions like: “What would make you return?” or “What would improve your experience?”
• Track qualitative signals: Read through exit posts, comments, or even support tickets for signs of dissatisfaction. Understanding the “why” behind members’ reasons for leaving helps shape strategies for improving retention.

Here are some additional lenses to consider when analyzing churn:

• Compare churn with health metrics: A high churn rate among occasional members might not be a red flag. But if your core contributors are leaving, it’s a warning signal. Weigh churn rates against engagement health metrics, such as active discussion threads or participation rate, to avoid misinterpreting churn as a systematic issue.
• Factor in sentiment analysis. Use sentiment analysis to understand the tone of member interactions, especially for at-risk groups. Negative or frustrated sentiment could signal impending churn, even if engagement appears stable.
• Assess involvement in community milestones: Track whether members who participate in specific milestones (e.g., completing onboarding, attending a webinar, reaching a certain number of posts) have lower churn rates. This helps identify key activities that correlate with retention.
• Segment by interest clusters. Segment members based specific content/topics they frequently engage with and compare churn across these clusters. If members from a particular cluster are churning more than others, it may highlight a need to refresh or expand content in that area.
• Connect churn to business impact metrics. Integrate churn insights with metrics tied to company goals, such as customer lifetime value, product adoption, or customer support efficiency. This will clarify the business implications of community churn. For product or support communities, examine if engagement (or lack thereof) in the community correlates with broader customer churn.
• Consider community lifecycle stages. Recognize that churn may look different depending on where your community is in its lifecycle (e.g., early growth, maturation, or stabilization). Early communities may have high initial churn, which stabilizes as the community matures.
• Evaluate cross-platform engagement. If your community has integrations with other platforms (e.g., social media, customer support channels), analyze if and how members who engage on these other platforms differ in retention. Sometimes cross-platform activity can compensate for a lull in direct community engagement.

Each lens provides a unique angle to understand churn dynamics and help pinpoint areas for improving member retention.

Using Engagement Data as a Leading Indicator

Churn doesn’t have to be a purely retroactive metric. It can serve as a proactive indicator of future engagement if analyzed correctly. By regularly monitoring engagement data and member activity, community managers can identify potential risk factors before they lead to attrition. Ask yourself:

• What times of day or days of the week show the lowest engagement, and could adjusting posting times improve visibility and interaction?
• Are certain content types or topics seeing reduced engagement?
• Is there a correlation between types of member interactions (likes, comments, shares) and longer-term engagement?
• Are members disengaging after specific actions or interactions? (e.g., after posting a question that receives no responses)
• Which community events or activities have the highest and lowest attendance, and what might that indicate about members’ interests?
• Are there specific onboarding steps or community areas that see higher inactivity rates?
• Are there specific members whose engagement drops might influence the participation of others (like super users or frequent contributors)?
• Are there shifts in member interests or trending topics?
• Is there a correlation between time spent in the community (e.g., session length) and engagement levels?
• Do seasonal trends affect engagement, and how could you adapt community activities to align with these fluctuations?

When these questions are answered with data, they reveal areas where you can make strategic adjustments to improve retention.

Tips for Conducting a Churn Analysis for Your Community

Churn metrics don’t exist in a vacuum. Each community has a unique member base, engagement levels, and goals, which means there’s no one-size-fits-all formula for interpreting churn. To create a meaningful churn analysis, tailor your approach to reflect the unique characteristics of your community. Here are a few tips:

• Benchmark against historical data: Track your community’s performance over time rather than relying on industry standards alone. This historical perspective lets you recognize changes in member behavior specific to your community rather than applying a generic “good” or “bad” churn rate.
• Adapt over time: Community goals and user behaviors evolve, so revisit your churn analysis regularly to adjust benchmarks, engagement metrics, and member segments as needed.
• Analyze community ‘stickiness’ rather than just churn. “Stickiness” measures how often members return to engage over a specific period and can reveal how well the community fosters habitual engagement. A community can have low churn but also low stickiness if members visit infrequently, which indicates a lack of engagement depth. Use stickiness metrics to gauge which content types or activities (e.g., regular Q&As, weekly digest emails) keep members coming back and improve overall retention.
• Consider churn as a healthy component of community evolution. Accept that a certain level of churn is natural and, at times, even healthy. Communities may lose inactive or disengaged members as they grow and evolve, making space for highly engaged members. Benchmark churn with this in mind, assessing whether it’s due to positive “pruning” (e.g., removal of spam or inactive members) rather than negative losses, allowing you to focus efforts where they’ll be most impactful.