The data that re-defines ‘good’ fundraising
Do you know who your best new donors are? Do you know who your best fundraisers are?
My guess is, if you’re honest with yourself, your answer to the first question is no, but to the second it’s yes (am I right?)
This new data changes everything!
For the first time ever it’s possible to quickly identify who is going to leave before they do!
It is no exaggeration to say this data redefines what a quality fundraising experience looks like – and how you should define and measure a quality fundraiser.
The data you’re about to see is from feedback taken immediately after a donor has signed up with a street fundraiser (but don’t get hung up on channel; similar results are born out across all channels).
The first table shows first month cancellation listed using patented Commitment (also known as ‘relationship’) segments. This unique methodology allows you to accurately categorize donors as being High Commitment, Potential High Commitment, Vulnerable or Transactional.
As you can see there is a perfect correlation with all the cancellations coming from the “Transactional” category.
This indicator is causal, not coincidental. It gives you a clear picture of what you can, and should do, either to save donors sooner or stop wasting money trying to get them back (also known as endlessly and expensively harassing people who were never that interested and are increasingly less so).
The related, and perhaps even bigger, opportunity to redefine, and refine, face to face (and of course all channels), is highlighted by the 2nd bar chart.
This time each column represents individual fundraisers. This is filtered to only show the ‘good’ fundraisers by traditional, transactional metrics; number of sign ups per day. All these fundraisers are ‘good’ by that definition.
But this chart breaks out, by fundraiser, the patented Commitment level of the people they are recruiting. One-hundred percent of Fundraiser #8’s recruits are Low Commitment; half are Transactional, half Vulnerable. Compare this with Fundraiser #113 (the 5th column from left to right) who recruits 0% Low Commitment donors.
There’s another piece of information, not shown on this chart, which would be funny if it wasn’t tragic. Fundraiser #8 has the most sign-ups per day making him the best if we view him by traditional, but clearly very faulty metrics!
Of course there is a lot more nuance, value and process involved in all this. This wasn’t found using the kind of simplistic satisfaction survey our sectors slowly starting to look into long after the commercial world’s ditched them as ineffective.
Nor is it the result of some patronizing creative effort to ‘inspire’ or ‘engage’ people about whom we know nothing other than the amount they gave and the demographic bucket we’ve dumped them in. By this frankly dumb process the people who leave look identical to the people who stay. The only defining difference being one’s still here and one isn’t – leaving us no clue as to why in either case.
There is a science to knowing what, where and when to ask for feedback and what to do about it.
One glance at these groundbreaking numbers shows how much we don’t know about the people who sign up and the people signing them up. Using this data, we can re-define good fundraising and really do some good.
3 Comments
James · February 22, 2016 at 17:40
Hi Charlie,
Thanks for this interesting piece. I’d be really grateful if you could clarify how the ‘commitment’ scoring was compiled – I’m assuming that you captured some attitudinal information immediately after sign up?
If that’s the case I’m interested in whether your captured information was based on personality traits (i.e. generic across sectors) or whether the commitment questions were specific to that charity.
Look forward to your thoughts as ever
Kind regards
James
Kevin Schulman · February 23, 2016 at 13:33
James,
Allow me to reply to your question. Yes, we measure Commitment as an attitudinal construct using a short, survey – I’d actually call it a feedback script but that is semantic I suppose.
The measures were identified as part of a multi-year product development (i.e. scale and model development) effort, starting with the standard lit review on what is already known, theorized as the component parts of a “relationship” and items to measure those.
The end result is a standardized set of items that do a very good job of measuring latent, component “parts” of a relationship (e.g. consistency, reliability, reciprocity, satisfaction, trust) that are also very predictive, as the post indicates, of future behavior.
The standardization however includes customizing ever so slightly to ask about the specific charity in question so it is not a global measure of Commitment to the charitable sector or some sub-sector (e.g. environment, international relief), it is a measure of loyalty (if one prefers that term) to the specific charity.
The real bespoke part of the model is not just measurement of loyalty but determining the specific touchpoints of a specific charity (e.g. their specific enews or magazine or core message or donor service interaction) that actually cause Commitment and by extension, those that do not.
But, that is beyond the scope/purpose of this particular post.
James Long · February 23, 2016 at 15:55
Thanks Kevin, that’s really helpful – sounds like a great piece of work and a step forward in the sectors approach.
Best wishes
James