Prospect identification Archives - Page 4 of 4

September 12, 2013 By Helen Brown 3 Comments

Fundraising Analytics ABCs – Donor Modeling

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.

vector

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:

Capacity affinity

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.

September 5, 2013 By Helen Brown 4 Comments

Fundraising Analytics ABCs – Data Mining

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 all of this. In each, we will describe the method and give examples of how they can be used. To begin our series, we discuss data mining.

Let’s begin with a case study:

The fundraising team at a university is having a problem with donor retention. Every year the university must acquire a significant number of new donors to offset the nearly 50% of donors they lose from the previous year. They need to find an answer to the question “why are we losing so many donors, and what can we do to keep them from leaving?”

They decide to use a technique called data mining to find out.

What is data mining?

Sometimes we don’t know what we don’t know. In those situations, it may be best to explore a little to see if we can find answers (and perhaps even see the questions we need to ask). Think of it as discovering what’s in a new mall by walking the length of it: data mining is like shopping in the data mall. What will we find when we look in each store?

Data mining sifts data back and forth until it finds natural breaking points, puts together associated characteristics and then lays out what it finds. For example:

“The donors who give the highest gift amounts are married male alumni. They’re in their 50s. They live along the east or west coast. They have a job and children that we know about.”

Data mining delves deeper to find relationships between many characteristics

The good news is that data mining also names the characteristics for the second best segment, and the third best, and so on, so a university could use it to find out various solutions to their attrition problem. The characteristics they see might look like these:

“The donors who stop donating tend to leave between their 5^th and 6^th years of consistently donating to the annual fund” So we can work harder to retain them before year 5!

“The donors who stop donating tend to be married alumni males in their thirties” What special incentives can we offer to that group since we know that married men in their 50s tend to be our largest donors later on?

Data mining can also be used for:

Determining the best solicitation methods for donor acquisition, renewal, or upgrade
Measuring the characteristics of event attendees who later become donors
Understanding the clusters of members/grateful patients/families/alumni/docents who respond better to e-mail, direct mail, phone calls, or social media
Finding the best pattern for the cultivation/giving ladder
Adding or dropping solicitation methods, or venues
Assessing timing, including how long it takes to successfully solicit gifts at different levels

What else can data mining do?

Have you ever walked into a store that has section after section of fun things for purchase? A department each of clever t-shirts, gifts that your best friend would love, beautiful hand-crafts, and more – things that are so perfect that you’ve picked up an armful of things and you need to find a basket to dump them all in.

Data mining is like that. It can also be for:

clustering like-minded, or like-attributed prospects for a cultivation dinner
breaking long-held “truths” about your donor base, such as “our best athletics prospects are male football alumni.” What if that’s not actually true?
looking at what statistics calls “interactions” – the combination of characteristics that make good prospects, members, volunteers, trustees, etc. For example: Married prospects and/or prospects living in rural areas show a mild relationship to loyal giving. However, prospects who are married AND live in rural areas show a strong relationship to loyal giving.
determining which group responds best to email and which to social media.

What do you want to know?

Our series continues next Thursday, September 12 when we will discuss Donor Modeling.

Do you have questions about data mining or would you like to see how it can work for your organization? Email us for more information at info [at] helenbrowngroup [dot] com.

June 24, 2013 By Helen Brown 2 Comments

5 Great Ways to Find New Donors

You need new donors in major gifts, annual giving, planned giving, principal giving…okay, I understand: you need new donors in ALL areas of your fundraising operation. No worries. Here are just a few (of the many possible) remedies to help you identify and involve new donors.

Remedy #1: Have you taken care of donor attrition?

For many organizations, attrition numbers are scary-high right now. Do you know what percentage of your donors leave every year? It’s a lot easier (and cheaper) to keep a donor than it is to acquire a new one, so work at understanding how many are drifting away and why they leave. Then devise strategies to keep them.

Remedy #2: Do you know who your best prospects are?

It doesn’t matter if you work at an organization with less than 500 donors or one with a million. You need to get to know your donors better so you can find others like them. Data analytics – even basic queries – can provide characteristics of your best prospects to help you identify more people just like them. Slicing and dicing your data – even sparse data – will give you great answers. If you don’t have capacity to do it in-house, it’s very easy to find talented analytics experts to help you.

Remedy #3: Do you know what it is about your organization that donors love?

You may be surprised to learn that it’s not always a priority you’re pushing, but some other X factor that gets them jazzed. Ask them! Surveys are a great way to find out donor interests and opportunities you could capitalize on. (And don’t give me the old “but we’re not an alumni-based organization!” argument!) Alumni organization or not, don’t you have gorgeous t-shirts to give away as an incentive? Or what about a “Free ice cream cone in the splash park for donor survey responders appreciation day”? What do you have that prospects would value? Be creative and piggyback activities!

Remedy #4: Are current donors giving you what they’re giving other nonprofits?

An electronic screening can help you answer this question, and will help you elevate both annual fund and major gift numbers – probably significantly. Many of the vendors, in addition to providing asset information, also match the individuals in your database to donor honor roll lists of nonprofits across the US and United Kingdom. Someone who is regularly making gifts across town that are 10x what they give your organization needs to be asked for more.

Remedy #5: Maybe they don’t love you yet, but what about the ones who ‘Like’ you?

It’s a good bet that your nonprofit has some kind of social media presence at this point (and if not, it’s time to get a move-on). What have you done to convert those people who just Like you into future donors who love you? What can you offer them – of value – in exchange for their contact information? A study or white paper? Access to an invitation-only lecture? A free hour in the swimming pool? A ‘behind the scenes’ tour with the performers?

These are just a few of the many ways strategic prospect research can help you identify prospects. Thanks for reading – What ideas do you have for how you identify new donors?

March 26, 2013 By Helen Brown 6 Comments

Prospect Research for Fundraisers – the Book!

Book Look at what arrived by special delivery today!

It’s an advance copy, meaning that for all of you who pre-ordered (and thank you for that, by the way!), yours will be arriving very soon.

If you haven’t already ordered it, now’s the time to get your very own copy hot off the presses! Just click that little book cover over there on the right to buy it at a discount (!). It will be on your doorstep in no time. This book has got everything anyone working in fundraising needs to know about prospect research. You’re going to love it.

Thank you to everyone who was involved: those who agreed to be interviewed, who were the subjects of case studies, who provided quotes and who read (and re-read!) drafts and offered sage advice and suggestions. And the biggest thank you to my co-author, the awesome Jen Filla.

May 17, 2012 By Helen Brown 1 Comment

Ten tips for a successful wealth screening

You may remember a few months ago I talked about how Brown University got a 500% return on the proactive research they did for the Boldly Brown campaign. One part of that was successfully integrating the results of several wealth screenings that they did.

Because some of the vendors are offering database screenings at a deep discount this quarter, a number of our clients are taking advantage of the savings … which means that it’s screening analysis season here at HBG!

Andrea, Jennifer and Maureen have been collaborating closely as a unit and with our clients on these screenings, and I’ve been really interested as I listen to them share ideas over lunch or at our afternoon tea breaks.

There’s a lot of delight and excitement when a screening is returned, but also some regret when they find an opportunity that was missed.

What I hear from their conversations underscores that how you approach a screening really makes a difference in the end result.

So I thought I’d ask them to share their top tips for making the most of an electronic screening so that we can all boost our return on screenings to Brown proportions. If you have more tips to share with readers, we’d love for you to add them!

From Andrea:

I’ve become a big fan of wealth screenings lately. I’d say my top three tips are:

Include as much information as possible: middle initials and spouse names are particularly important in helping save time later.
Don’t trust the database’s judgment: verify everything! Screenings are a good jumping off point but the human element of analysis is important.

Once the data is returned, try several different sorts to see if there are any trends. I generally start to look for patterns sorting by confirmed assets, then by identified assets and filtering by state, zip, and past giving. It’s really interesting what you can find!

From Jennifer:

Pay particular attention to high net worth individuals in New York City – chances are if they own a co-op apartment that the entire co-op building is being counted in their assets.
Cleaning the data beforehand is well worth the time investment. Fix any typos and check to be sure addresses are consistently entered – bad data is the #1 way why matches aren’t made. Time spent on this in advance can save lots of time (which is money!!) confirming later.
Don’t include anyone that only has a PO Box address. Either leave them out or find their street address.

From Maureen:

Purchase an address update (NCOA) as part of the screening if you haven’t done one recently – a significant match point for assets is address.
If your budget is tight, don’t waste it on screening donors that you already know well.
Depending on the size of your screening, make sure to allocate at least one staff member to do the analysis when the results are returned. Screenings are expensive and you don’t want the results to just sit there gathering dust.
Don’t screen if you don’t have the front-line fundraising staff to follow up on the leads that are produced. Be strategic in the number of prospects that you screen and consider doing rolling screenings.

October 13, 2011 By Helen Brown 1 Comment

More, Ben Franklin and Prospect Research

The creative fundraising folks at More Partnership in the UK recently put together a small book called More stories, which is the “first in a series of little books about fundraising.” I hope they put out another little book soon because its 32 pages delighted and entertained me with inspiring and amusing stories on fundraising (just wait ‘til you read the one about the doctor, the lawyer and the development director at the Pearly Gates!).

One of the quotes in the book really hit home for me because it dovetailed nicely with a conversation I’d just had earlier this week…

The executive director of a nonprofit in New York City and I were meeting over coffee. She asked me how we go about finding board, volunteer and major giving prospects, and I outlined the concentric circles we study:

Starting with those closest to the organization (trustees, lead volunteers, etc.) we work our way outward through their branches of connection, so that the people, foundations and companies we identify already have a clear connection to the organization or to the cause they serve. We eliminate those who have been previously involved or were asked to serve but could not. We build a model of the ideal prospect, and see what obvious connections can be branched from there. And, of course, we do a few other trade-secret-y things.

Our process is hand-tailored and intense because we believe that one warm call that will be answered is much easier for a fundraiser to make than 15 cold calls. And if it can’t be a warm call, then we suggest one where the potential attraction is so obvious that it has the power to lean the prospect like a magnet toward the new cause.

Reading this quote from Ben Franklin, I was struck by the thought that, even 220 years later, the important things stay the same.

June 6, 2011 By Helen Brown 5 Comments

How to get a 500% increase in prospects

Here is a crazy-good story for you:

When Brown University began their “Boldly Brown” campaign in July 2003 they had 1,535 people identified as potential major donors. That may sound like a lot, but they had over $1 billion to raise to support scholarships, attract and retain faculty and to upgrade their facilities and research capability. The fundraisers, both paid and volunteer, had some serious work to do if they were going to reach that ambitious goal.

During the course of the seven years to follow, the Brown research team made sure that their alumni records were up-to-date and that the data was as free from error as possible. They used sophisticated screening tools to find people with the means and interest in supporting Brown. They segmented their data to identify new potential donors based on the characteristics of their current loyal supporters. And they researched and fine-tuned the information they had to be sure not to bother people who weren’t likely to be interested in supporting Brown at a higher level.

Because in addition to using these methods to identify future supporters, the other thing we researchers are trying to do is eliminate (to the degree possible) annoying people with unnecessary mail, phone calls and visits when they don’t want them. It’s good business to avoid irritating people, but it’s also a smart way to save money, trees, electricity, and peoples’ valuable time. To be good stewards of past donor dollars.

So what happened?

5,284 new major gift prospects were identified.

That’s more than a 500% increase in potential supporters!

Even more incredible, Brown University received $710 million in new gifts and pledges from those newly identified and upgraded prospects. If you’re thinking “Hmmm, that number looks eerily like it’s nearly three-quarters of the total campaign goal”- you’re catching on. That’s the impact of applied prospect research and analytics – it makes a huge difference.

What else?

Brown University reached their goal of $1.4 billion eighteen months early, and went on (during the worst recession of our lifetimes) to garner over $1.6 billion in total support by the time they stopped counting in December of 2010.

Can their success be yours?

Sure, Brown University is a huge organization. And yes, they have a crack research and analytics team headed by Elizabeth Crabtree, a brilliant leader in our field. But the techniques Brown used can be applied to your nonprofit and scaled to your needs. What are the building blocks?

A cause that provides measurable results and inspires loyal support;
A multi-faceted prospect identification program that is funded to scale;
Policies and metrics for prospect relationship management;
Highly skilled prospect researchers/analysts who are both strategists and tacticians;
Effective collaboration between the research team and frontline fundraisers;
Inspired and engaging fundraisers and leadership;
Inspired and engaged donors and volunteers;
Stewardship that surprises (pleasantly, of course).

All of this takes time and money as well as a serious commitment of your heart to achieve the kind of success they had. But the results are undeniable:

Increased participation…
Increased donations…
And a solid foundation for future support.

Even if you’re a small organization with a staff of one, you can do this. You’ll need help, obviously, but there’s no time like the present to get started.