As a membership-based organization, your livelihood depends on members valuing your programming and choosing to renew each year. Without members to attend your events, join your online community, and leverage your career resources, where would your association be?
Although many associations are currently confident in their future renewals, with 86% expecting no change or an increase in renewals between 2024 and 2025, it can be difficult to predict exactly which members will and won’t renew without a strong, data-backed strategy.
This guide will provide tips for incorporating analytics into your membership renewal process. That way, you can more precisely forecast member trends and run campaigns that boost renewals.
1. Consider multiple types of member data.
The more data you have, the more well-rounded and accurate your renewal predictions will be. While you may have historically relied on metrics like dues payment history alone, that information is typically not enough to forecast renewals, especially if you offer auto-pay and automatic renewals.
To get a more comprehensive sense of which members are likely to return, leverage data points like:
- Event participation. Members who consistently attend your conferences, webinars, and committee meetings are more likely to renew. On the other hand, members who barely attend events or have stopped attending events they used to champion may be at risk of lapsing.
- Financial data. Paying dues outright isn’t the only satisfaction marker to track. Look into whether members pay on time and in full to get a better picture of their current standing. Members who make full, prompt payments are likely more committed to your association.
- Program engagement. Whether members consistently open your emails, log in to your member portal, participate in online member discussions, and interact with your social media content can give you insight into their chances of renewal.
- Member history. Longstanding members who have been loyal to your association for years have clearly seen the value of membership over time and may be more likely to renew. Scour your association management system (AMS) to pinpoint which of your members have been active the longest.
- Demographics. Early career members may have more to gain from membership than those looking to retire soon. Additionally, those closer to your association’s headquarters may be more inclined to stay since it’s more convenient for them to attend in-person events.
If you want to learn even more about your members beyond the data you already have, consider using data enrichment to expand your understanding of your member base. For example, you may append education information to see if there is any correlation between education level and membership renewal likelihood.
2. Segment your members.
Members have unique characteristics that shape their engagement with your association. Splitting members into groups based on these traits can make your analytics more meaningful and help you create personalized campaigns. For instance, you may segment your members based on engagement:
- Low engagement. Members at the lowest engagement levels are likely at the highest risk of lapsing. Analyze low-engagement member data across other potential renewal indicators to focus your outreach on those most likely to renew. For example, you may find a subset of low-engagement members who live close to your association’s headquarters and invite them to a small in-person gathering to help them build deeper connections with other members.
- Moderate engagement. Think of members in the middle as a chance to find your newest high-engagement members. Identify those with factors that could indicate a willingness to engage more, like event participation or longstanding member history, and send them surveys to learn about their preferences so you can deliver more targeted communications.
- High engagement. While high-engagement members likely don’t need much convincing to renew, they may be wondering, “What more will this association provide me this year that they haven’t in previous years?” Leverage analytics to determine which initiatives have been most successful in the past, and create new ones with this knowledge in mind. For example, if your career development services are popular, consider introducing a new mentorship program and promote this offering to keep highly engaged members satisfied.
Segmenting your members into relevant groups can also help you send more relevant communications throughout the year. Store these segments in your constituent relationship management platform (CRM) for future reference.
3. Build predictive models.
While AI tools can help you build advanced models, you can often make informed predictions on your own using the member data you’ve collected. Consider the following methods for projecting member renewal trends:
- Scoring model. Assign points to different activities that members complete. The more significant the action, the greater the point value should be. For example, attending an event may earn 15 points, while commenting on your association’s social media post may earn five. Determine a certain point threshold that indicates members are likely to renew.
- Cohort analysis. Track renewal rates based on when members joined or their career stage. You may find that first-year members often have the lowest renewal rates and implement a plan to engage them more deeply.
- Engagement trend analysis. Look at member engagement data from this year and last year. Pinpoint which members have significantly decreased their involvement, and launch campaigns that target them for renewal.
If you’re looking for more advanced capabilities, a machine learning model may be right for your organization, but if you want to forecast trends using the technology and data already available to you, this approach can help.
4. Track renewal KPIs.
Actual renewal numbers aren’t the only valuable insights you can gain into your renewal process. By identifying and tracking other renewal key performance indicators (KPIs) related to your goals, you can further refine your renewal strategy. These metrics may include:
- Renewal rate by member type or segment. Go beyond a cohort analysis to determine your average renewal rates for different member groups. For example, you may closely track mid-career professionals’ renewal rates and implement campaigns that aim to increase these numbers over time.
- Average time to renew. Determine how long it typically takes for members to renew after receiving their initial renewal notices. Cross-reference this data with engagement metrics to determine if there’s a correlation between shorter renewal times and higher engagement rates.
- Auto-renewal enrollment rate. Identify the percentage of your members who have opted into automatic renewals and how that number has changed over time. If that number has decreased, it may indicate waning trust in your association or simply members wanting more control over the renewal process.
Use dashboards to visualize this data so you can more easily spot and present trends. Sharing this data with leadership, board members, and accounting staff can help justify an increased budget for new renewal efforts.
You likely already have most (if not all) of the data you need to predict member renewal trends, but it’s how you implement that information that matters. By accurately forecasting membership renewal trends, you can better understand your members’ motivations, create content and programming that resonates with them, and keep running a strong, thriving community of like-minded individuals.
