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Office Space: Time for a Better Annual Fund Process
Office Space: Time for a Better Annual Fund Process

Want to build mailing lists faster and quickly move donors up the giving ladder? Let the prep work begin.

By Michael Pasqua

Paul Garland

Some people have an annual ritual like doing spring cleaning or taking a beach vacation. I have one, too, but it's a little offbeat: preparing for the upcoming annual fund campaign. As a technology enthusiast and longtime advancement services professional, I developed a routine to reduce the time required to produce annual fund mailing lists.

In years past, annual fund directors used to request a multi-segment mailing list every few weeks and send me a formula to determine how much to ask each person to give. As the directors concocted the right mix of segments and ask amounts to grow the annual fund, the list requests often sounded like a recipe from Macbeth's three witches: Eye of newt, and toe of frog, wool of bat, and ... computer science alumni living in Santa Monica, California.

Then came the kicker: "And can I have it by tomorrow?"

Given the complexity of the request, my typical answer was "Not a chance." A frustrating situation all around. We needed the ability to quickly generate segmented mailing lists with individualized ask amounts that would move people up the giving ladder.

Now is the winter to fix our discontent

At California's Mills College a couple of years ago, the annual fund director and I decided to solve this problem. We experimented with ask amounts in the next annual fund appeal and found that segments with aggressive asks produced smaller gifts and fewer donors than segments where the ask amounts were closer to what the individual gave the preceding year. We also studied several years' worth of data and noticed that people's gifts were clustered around a dozen specific values—$25 and $50 were popular at the lower end while $1,500 and $2,500 were common higher up. Armed with this information, we agreed on three basic principles regarding ask amounts:

  1. They would not change throughout the fiscal year.
  2. The amount a donor gave last year would determine this year's ask.
  3. The formula for calculating ask amounts should move a person up the giving ladder over time.

To accomplish this, we designed a giving ladder with 12 steps corresponding to the 12 peak amounts we observed in our analysis. For example, a person who gave $30 last year would fall between the $25 step and the $50 step, so that person would be asked to give $50 this year.

As soon as the fiscal year ends, I run a program that computes everyone's ask amount for the coming year and store the results in the advancement database. The reports that build the mailing lists include these values, which can be dropped into appeal letters and reply cards.

You're going to need a better list

You can creatively segment constituents in thousands of ways when you build a mailing list, but the price you pay for unlimited creativity is longer programming time. So the annual fund director and I agreed on two parameters to build mailing lists: relationship to the institution (alumni status, parent, friend, etc.) and giving history (lapsed donors or those who gave last year but not this year—aka LYBUNTs—or people who gave some year but not this year—aka SYBUNTs).

We also needed subcategories to send targeted messages to specific groups. Parents, for example, fall into at least two subcategories, current and past. Alumni can be placed in many subcategories, such as reunion versus non-reunion year or degree earners versus non-degree earners. Individual giving histories can be broken into subcategories based on ask amount and years of consecutive giving. These subcategories help determine things such as membership in a premier gift or donor loyalty society. We ended up with 17 relationship subcategories and 14 donor history subcategories.

After calculating people's ask amounts, I run a program that assigns relationship and giving history attributes to each person. Assigning these attributes to everyone reduces the programming time needed to generate mailing lists during the rest of the year.

Summertime and the asking is easy

The final part of my ritual is updating the predictive model, which calculates each person's probability score—the likelihood that an individual will make a gift. Integrating probability scores when building a mailing list helps segment the information based on science rather than intuition. Refreshing these scores with updated data at the end of each fiscal year can predict who will give in the next one.

Once all the gifts from the previous fiscal year have been recorded, I begin the modeling process by creating a file that contains personal attributes—age, major, reunion status, whether a person lives in a high-wealth zip code, and more—for everyone who was solicited. This file helps build a probability formula, which can determine, for instance, whether being a computer science graduate living in Santa Monica has any relationship to being a donor—and if it does, how much weight to assign to that relationship. Then I build a second file with updated values for the new fiscal year, accounting for changes in a person's age, zip code, and so on. Finally, I apply the formula to the records in the second file to calculate each person's new probability score.

Using predictive modeling adds a third parameter to building a mailing list, but targeting the portion of your audience that will produce 90 percent of your gifts can reduce mailing costs 30 to 40 percent.

Show me the payoff

Preparing the programs that calculate ask amounts, categorize the people in your database, and provide probability scores is a worthwhile investment. If I begin this work in January, everything can be ready to go by July. Once the work is done for that first year, running the programs takes only a day or two at the end of the next fiscal year. No more toil and trouble, because I can hand an annual fund director a segmented mailing list in a few minutes. Farewell, witches' brew. Hello, mint julep.

About the Author Michael Pasqua

Michael Pasqua is director of development services at the University of San Francsico.




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