Donor churn – how is it affecting your fundraising goals?
Donor churn is one of my favourite metrics.
When I told my colleagues I was writing a post on donor churn I could see them switch off and their faces glaze over – I get it, it is not a sexy metric on the face of it.
However, it is the lifeblood of most organisations and fundraising teams. It affects every other key metric; donor lifetime, donor lifetime value, donor acquisition etc.
In this post I will compare how different donor churn rates affect donor numbers & fundraising revenue over 10 years. I will also share with you a donor churn calculator to help you predict the effects of churn on your organisation.
Churn is the % of your donors who choose not to donate again.
There are a number of ways to measure churn (monthly, yearly etc) – I’m going to use the formula below to measure churn in this post.
Donor Churn = # of lost donors in 12 months / # of total donors in 12 months
The 80/20 rule says that 80% of a fundraising team’s revenue is going to come from 20% of its donors – the major donors.
I’m sure we all agree that keeping the churn rate down for those major donors is of utmost importance. But, what about the 80% of donors that only bring in 20% of your revenue? Is churn as important a metric for them?
I’m going to look at 2 hypothetical organisations, each with a different annual donor churn rate.
Annual donor churn rate
Organisation 1Organisation 2
On the face of it there is not a huge difference between them in terms of churn rate, only 15%.
In order to measure the impact over time, I will analyse the Cumulative Revenue these organisations bring in over ten years in two different scenarios.
The first scenario will just look at an existing cohort of donors, whilst the second will look at a cohort that grows over time in terms of both number of donors and average gift size over time.
2 Scenarios: no new donors versus new yearly donors
Scenario 2Number of starting donors1,0001,000Average yearly gift£120£120Number of new donors each year0250Year on year average yearly gift size increase0%10%
Note: I’ve purposely kept the yearly gift low as I’m ignoring major donors.
Scenario 1: In this scenario, we are looking at what will happen to the donor numbers and cumulative revenue over time if there are no new donors each year and the gift size stays the same. We are looking at the difference between what will happen to Organisation 1 with a 10% donor churn versus Organisation 2, with 25% donor churn.
Scenario 2: In this scenario, we are looking at what will happen to the donor numbers and cumulative revenue over time if there are 250 new donors each year with an average 10% gift size increase year on year.
Below are the cumulative revenue graphs for each scenario, each showing both organisations.
Scenario 1 (no new donors)
Scenario 2 (new yearly donors)
Let’s look at the numbers a little more closely.
Scenario 1: Organisation 1 VS Organisation 2
Scenario 2: organisation 1 VS organisation 2
In scenario 2 – that 15% churn difference led to Organisation 1 having £1,288,078 more in revenue; that’s 81% more than Organisation 2.
Perhaps more importantly, Organisation 1 had 997 more donors after 10 years – 130% more. That’s a whole lot more small donors that could go on to be tomorrow’s major donors.
This is obviously a very simplistic model and doesn’t take into account a whole host of variables that apply to a fundraising office. However, it should illustrate the importance of churn as a metric to watch and take into account, not just for major donors but also for the smaller regular givers.
Acquisition tactics matter
Often overlooked as a key influencer on your churn rate is how you acquired your donors. Gearing your campaigns and channels towards bringing in the most cash and donors, at the expense of genuine engagement and long-term value-building may wind you up in Organisation 2’s position – continually funnelling cash into replacing churned donors.
As mentioned, the scenarios I have used here are by necessity highly artificial. Why not click here to play around with the model I used, putting in your own numbers to see how donor churn could affect your own long-term donor and revenue numbers.