Over the weekend I realized that I had just launched right into this series on ratings assuming that they are a given in every fundraising office. That everyone is already clear on the types of ratings that are out there and how they are used in a relationship management system for fundraising.
In my early days as a prospect researcher, I used to be a “Just the facts, ma’am” kind of researcher and report writer. A “here’s what I can see. I have no idea what the rest looks like so I can’t even guess for you” kind of gal. I was so afraid to be wrong.
Except I already was wrong.
“Yes, we did a wealth screening a couple of years ago. We didn’t really find it very helpful.” <pause>
“Well, to be honest, we didn’t really do anything with the information when it came back. It just kind of sat there.”
If I had a twenty for every time someone said that to me I’d be making major gifts already.
It absolutely kills me, too, because wealth screenings
a) are not cheap, and
b) can be worth every single penny.
There’s a critical piece of information missing from most capital campaign feasibility studies:
The amount of money an organization’s constituency can actually give.
We need the answer to that before we can set the goal, right?
And yet… most of the time nonprofit organizations launch their campaigns without knowing the full answer to that question. They wait until after they’ve launched to finally get all the pieces in place. Which seems kind of crazy to me.
Imagine with me that it’s Saturday afternoon. You are flat out busy today, and tonight you have exactly two hours to prep and cook dinner for guests. One of the guests is a good friend, but the other two you don’t really know all that well. They are friends-of-friends in town for the weekend.
Is this the night that you’re going to pull out the 25-ingredient recipe for a gourmet French dinner? Julia’s cassoulet, perhaps?
This week I’m in England talking with our colleagues at The Factary in Bristol. Their offices are open-plan and I’m impressed at how collaborative they are, with each other and with their clients. I met with nearly everyone on the team to learn more about the kinds of projects they’re working on, what they each do to meet their clients’ needs and how they work together as a team. It’s really interesting to see the ways we’re the same and the ways we do things differently.
Back before I started my career in prospect research in 1987 at The University of North Carolina at Chapel Hill, I was the assistant to the director of finance for the development office at the university. My responsibility was to help my boss Jean track all of the money the university received; she had to make sure it went into the right bucket and was distributed correctly.
As a fundraiser constantly on the go, sometimes it might seem like it takes a long time to get a research profile back from an in-house prospect researcher or consultant. When you’ve got a meeting coming up or you need to prioritize your prospect pool in a hurry, I know that you really haven’t got a lot of extra time to wait. Here are four secrets to getting information back faster from your research partner:
1. Take care of your gold. Chances are that your nonprofit received a larger-than-normal number of gifts last month, and many of them came from new donors. The money that came in will help you do your important work, but the gold I’m talking about is the information that came with each gift. You’ve just started a relationship with someone new that you hope will last a lifetime, right? Here are a few things that your organization should pay attention to:
Chances are good if you are in the fundraising field that you have heard the term “fundraising analytics.” You’ve probably also heard the terms “data mining,” “donor modeling,” “reporting” and “prospect identification,” too. Do these terms mean the same thing? What are the differences among them?
I asked Marianne Pelletier, who leads the HBG Analytics team, to help me put together a series of short articles designed to make sense of these terms. In each, she will describe the method and give examples of how they can be used. To continue our series, we describe the questions that Donor Modeling can answer.
Let’s begin with a case study:
A museum is in the planning stage to launch a major fundraising campaign. Their last campaign was over 5 years ago, and while they had a number of significant gifts, the coming campaign will require many more major gifts in order to be successful. After developing a table of gifts for the campaign, it quickly becomes apparent that there are huge gaps that need to be filled with prospects at every level. Significant prospect identification needs to happen.
To score the museum’s database and identify the top prospects, the museum decides to use a technique called predictive modeling, also referred to commonly as donor modeling.
What is donor modeling?
Donor modeling uses statistics tools to score a group of records using a variety of methods, including regression analysis, clustering, decision trees, neural networks and support vector machines (SVMs) amongst lots of others. Let’s take a look at just one of them, regression analysis.
Regression analysis uses calculus to find the slope of a line, which helps us visualize trends in the data. For example, we could see (based on a number of factors) which groups of people in the museum’s database have the most capacity to give as well as affinity, or connection to, the museum.
Here’s a standard matrix that is often built for major gifts programs. After downloading records and using regression analysis to score the group studied, prospects would be shown along the slope of the red line based on their relative affinity with the museum and their capacity to make a major gift.
Affinity, or “how much they love the museum” might be measured by the number of times someone attended events, or donated in consecutive years, or bought tickets to special exhibits, amongst other things. Capacity, or “how much they can give” might be found through primary or secondary research, such as a visit, prospect research or an electronic screening.
A graphic describing the relative level of a group of prospects’ affinity using a number of hearts (ranked on a scale of 1 to 3) and the relative level of their gift capacity (ranked 1 to 3) by dollar signs might look something like this:
In this example, the top-right box represents those with greatest capacity and affinity for the organization, and the bottom-left box shows those with the least.
If you were the chief development officer at the museum, whom would you want to approach first? Your answer is likely to be those in the top right group. Unfortunately most of the time that group is also the smallest population among the scored groups, and are usually the donors you know fairly well.
Whom to select next, then? Often, two of the largest groups, represented by the larger boxes, are the $$$ ♥♥ and the $$♥♥♥ groups. And of those, it might be hard to decide which to choose.
So, your next donor modeling study might be to look at the museum’s past track record with each of these two groups. What is your level of success in cultivating each group? What motivates them to become major gift donors?
Donor modeling helps answer those questions. The characteristics of top level donors are compared to various segments of the pool, and their scores help bubble up the best future prospects.
What else can you use donor modeling for?
Although it’s most often used to identify major gifts prospects, donor modeling can also rank groups like these:
- Annual giving prospects who are most likely to renew
- People who are likely to be good board/volunteer candidates
- Planned giving prospects
- People who would be great prospects for a specific project or campaign (like a library fund, or for endowment)
- People who would be most likely to accept a request for a visit
- Top level annual giving prospects
- Prospects best suited for a particular gift officer or volunteer
Donor modeling can even help determine the best ways to acquire new members for a member recruitment campaign. It’s a powerful tool to help your organization identify new donors, whether you’re in a campaign, thinking about a campaign, or just looking for new donor prospects.
What do you need to know?
Our series on the ABCs of fundraising analytics continues next Thursday, September 19 with a look at data visualization.
Do you have questions about donor modeling or would you like to see it at work at your organization? Contact us at info [at] helenbrowngroup [dot] com for more information.