Donor churn can be extremely harmful for nonprofits. Constantly acquiring new donors quickly becomes costly in terms of both time and money. Plus, you’re missing out on growing your relationships (and donations) with lapsed donors.

Too many nonprofits treat churn as just another reality of fundraising—but it can and should be combatted. Reducing churn should always be a top priority, especially for organizations that are trying to increase donor lifetime values, make up lost revenue, are struggling with donor acquisition, or simply want to stay adaptable in a turbulent economy.

For many organizations, a regular giving program is an invaluable infrastructure for retaining more donors and stabilizing your revenue, but it must be actively supported and grown over time. If you’ve already put in the hard work to build and grow a regular giving program, don’t let it go to waste! Churn management is essential.

At Dataro, we specialize in AI for nonprofits, which is all about making accurate predictions about donor behavior rather than operating on vague assumptions. We’ve built tools specifically designed to help nonprofits combat churn, so we wanted to share a few tips.

1. Use machine learning to predict churn.

First, you’ll need to start proactively predicting donor churn instead of simply reacting to it. This allows you to identify the most ‘at risk’ donors before they cancel their regular gift. Unless you can get ahead of churn, you won’t be able to understand why donors halt their giving, let alone begin addressing the root causes. 

Artificial intelligence has become an accessible tool for nonprofits of all sizes to take the guesswork out of predicting donor behavior. Check out the Dataro guide to AI for nonprofits for a full breakdown, but here are the basics of how this works:

  1. Your AI software analyzes your complete database of historical donor interactions to find deep patterns and connections.
  2. The software then trains an algorithmic machine-learning model based on those patterns, which is used to predict specific donor behaviors in the future.
  3. The propensity model then shows you exactly who is most likely to take a target action (like churning out of your giving program) at that moment. 

With a straightforward view of who’s likely to churn, you can directly counter it with targeted, individualized outreach and new engagement opportunities. The bottom line is that machine learning can be an extremely effective way to combat churn through proactive prediction. 

Here’s an example—we ran a test with a nonprofit partner to see how well AI could predict their real attrition numbers. Using a limited view of their data, our AI software trained propensity models to measure donors’ likelihood to churn. 

When we compared our predictions to how things actually played out in the data generated after our limited window, we found that more than 75% of the donors we flagged as at-risk (roughly 800 out of 1000) did ultimately churn within the next six months. Critically, we’ve found organizations can reduce this by 15% or more with targeted engagement strategies. 

2. Determine your donor churn opportunity cost.

Start by understanding exactly how much support you’re missing out on due to churn. Find how many of your regular donors churn out of your program each month on average. Multiply this by the average monthly gift that you receive, then project it out over several months. For example:

100 (average number of lapsed monthly donors) 

x $25 (average monthly gift amount) 

x 9 (months projected in the future) 

= $22,500 (projected lost revenue over 9 months if your churn rate remains unchanged)

This is essentially the opportunity cost of not improving your churn rate. An alarming number, but it’s necessary to understand if you want to improve it. Looking at churn through this lens can help nonprofits approach it more strategically rather than simply accepting it as an unfortunate reality. You’re probably leaving a lot of money on the table!

To combat churn, you’ll likely want to make new investments (like in AI prediction tools and new engagement initiatives). Your board will likely need to understand these investments as important parts of a broader strategic plan, so having some hard numbers on your side will strengthen your case and make it easier to communicate with them.

3. Immediately guide your strategies based on AI insights.

With AI helping you proactively predict churn and a clear sense of what exactly it’s costing you, you can make some immediate improvements to your outreach and engagement strategies. 

Reach out to put your mission back on the minds of donors flagged as at-risk. Write awesome emails to thank them, explain exactly what you’ve been able to accomplish with their gifts, or even invite them to your next event. Call them to thank them for their support, answer any questions, and explain how their money is doing real good in the world. Just don’t ask for money—focus instead on gratitude, impact, and offering new engagement opportunities.

With your at-risk donors contacted, you can dig deeper into your data to learn more about exactly who’s churning. Try sorting your at-risk donors by acquisition channel, demographic characteristics, or their initial donation amount. Do donors acquired through events churn the most often? How does the amount of your initial ask impact their long-term retention? 

Based on everything you’ve learned from your data and your AI tools, you can make some big-picture strategic changes to combat churn. For instance, you may find that you need to:

  • Create a specific new engagement program targeted at at-risk regular givers, reducing your overall churn rate on an ongoing basis. 
  • Alter your communication cadences with regular donors to send more or different types of messages.
  • Diversify your acquisition efforts through new marketing initiatives or community partnerships.
  • Ask for less from new donors upfront and focus instead on strategically growing their gifts over time. (AI can predict donor likelihood to upgrade, too!)

These types of strategic improvements can be extremely valuable, but remember to not rely on segmentation and manual analysis alone to source them. AI-driven predictions should always be your first stop for an accurate picture of exactly who’s at-risk at any given moment. This gives you a solid, data-driven foundation on which to build new strategies. 

Donor churn is a major problem for most nonprofits, but many organizations unfortunately are unaware of what it’s costing them. If you want to start combatting churn so that you can focus more on relationship-building and less on costly acquisition, you’ll first need to proactively get ahead of it. Using your data and artificial intelligence is the answer.

Aly Sterling Philanthropy