The nuclear fundraiser: 3 figures every data analyst should know
Next week I’ll be attending one day of the Fundraising Institute of Australia’s conference. After some recent interactions with fellow fundraisers, I’m walking into this conference trying to prepare myself for anything. I wouldn’t be surprised if the next fundraiser I met was a nuclear physicist in a former role, a funeral parlour director or a pole dancer.
It seems John Jeffries, the CEO of CBM is right. To paraphrase what I heard him say once: no one leaves school and says ‘I want to be a fundraiser.’ I certainly didn’t! (This is, of course, presuming that as a database manager / data analyst, I am a fundraiser. But that’s a whole different debate).
Given people don’t seem to ‘decide’ to become a fundraiser, people certainly don’t go to ‘fundraising college.’ When I think back to when I first started working with fundraising data, I could have benefitted from a few ideas of where to start. In that vain, I’m offering up the 3 figures every data analyst should know.
Figure 1: How many active donors do you have?
I know, this seems so basic but you’d be surprised how many people have trouble answering this question. The trouble comes not from inadequate databases (although this can be a factor and certainly a good excuse!). It usually comes from a lack of clarity about what an active donor is. Whether you decide an active donor is anyone who has donated in the last 6 months, 12 months or 24 is not nearly as important as picking a definition and sticking to it. Once a charity does this, it can know over time whether it’s going up, down or to planet Jupiter. The latter could be interesting but I’m sure your board of directors would prefer you were going ‘up.’
Figure 2: What ‘types’ of donors do you have?
When I say donor type, I’m not referring to whether they are companies or individuals. I’m also not referring to whether your donors are the ‘glass half full’ or ‘glass half empty’ types. Quite simply: it is what methods do your donors respond to or support? (There’s probably a far better word than ‘type’ for this; however it eludes me at this time. Perhaps I should have substituted that word for any random word… like ketchup maybe?)
Typical ‘ketchups’ include: Regular Givers/Pledgers, Community Fundraising Sponsors (e.g. city to surf; host a morning tea; the office staff come dressed as an antelope day… that kind of stuff…), Eventers (dinners, lunches, balls, high tea… you know the kind), Direct Mail/Marketing responsive donors), Bequests etc.
Why do you care about ‘ketchups’?
It can make an enormous difference to your results. At the very least, I think every analyst should know how many donors they have who have DM responsive, regular givers and then, if you like, the rest. If they can tell you more than that, woohoo! Chain them to a desk and don’t let them leave – they’re a keeper. (For the record, I’ve only managed to get clear in my head DM, RG and the rest, so I’m certainly not chained to any desk… yet).
Figure 3: How ‘matured’ are your donors?
I hear the word matured and I think of a fine cheese, or a red wine. With the utmost respect, I’d like to say that donors are similar. Let’s presume that we have two charities. For the first, I’ll use my fictitious charity – the flamingo protection foundation; the second, I’ll call the Quidditch Mission.
Each has 5,000 active DM responsive donors (defined as anyone who donated in the last 12 months to a DM campaign). For the sake of argument, let’s presume each charity deploys the same fundraising strategy and activities for 12 months. Let’s even presume that the donors give exactly the same average donation over the next 12 months and I’ll make that an even $100.
At the end of the 12 months, the Flamingo Protection Foundation has raised $350,000 from the donors who were active at the start of the year and the Quidditch Mission has raised $200,000.
They started with the same number of donors, did the same thing and got the same average donation (in my hypothetical world). So why are they so different? Quite simple: the Flamingo Protection Foundation donors were more ‘matured’ than those from the Quidditch Mission. Translated into numbers, those who save Flamingoes from the evil clutches of the red queen for croquet enslavement ‘renew’ at a rate of 75%. These are donors who were not ‘new donors’ in the previous year. In fact, it’s unlikely they were even ‘new’ the year before that. These people have been around for some time just like Alice herself. The Quidditch Mission donors on the otherhand are relatively ‘fresh’; a more recent invention. These guys only renew at a rate of 40% in the first 12 months and therein lies the difference. (To be more realistic, the flamingo supporters would probably also give a higher value of donation than the broomstick soccer nuts but let’s just glance over that).
So, that’s figure 3. Go quiz your data analyst and see whether they can tell you (in raw numbers or in percentages of active donors) how ‘mature’ your donors are. If they don’t know; ask for the retention rate. That alone may give you an indication. If they can’t give you either of those numbers, then I think we’ve located someone who was a scuba diving trainer in their former career and has yet to adjust to fundraising data analytics.
Posted on February 25, 2012, in Data, Direct Mail, Fundraising, Not for Profit and tagged Data Analysis, data analytics, Donation, FIA2012, fundraiser, fundraising, fundraising analytics, John Jeffries, Nonprofit organization, Philanthropy. Bookmark the permalink. 2 Comments.