We know we compete for our donors’ attention span. And every day, they receive more messages from friends, family, brands, and organizations via television, email, text, social media, etc.

The noise in the giving space is louder. The competition is fiercer. Purse strings are tighter. No question that those you call on have to have a high philanthropic priority to your institution. But who you call on as a fundraiser should be first dictated by the math behind your alumni base. Applying analytics first to your entire alumni base is essential for your fundraising team to identify the best people to outreach to for major and leadership gifts so you can grow capital for your institution and achieve its goals.

HOW TO CLEARLY NAVIGATE INDIVIDUAL GIVING

Can you find those individuals who have the willingness to give and liquid wealth to do so?

Think about it this way: When you travel somewhere by car, what do you do? You look up the address, lock it into your GPS, and go. It guides on which turns to take and how to get there.

Fundraising also has a GPS: data. By creating a data-driven donor strategy, you can pinpoint which donors and prospects you need to contact. 

INSTITUTIONS CAN IDENTIFY AN APPROXIMATE 30-35% INCREASE IN THEIR GIVING RATE AT THE INDIVIDUAL DONOR LEVEL BY ANALYZING AND STUDYING DATA, MAKING STRATEGIC DECISIONS AND APPLYING BEST-PRACTICES. 

Don’t believe me? Let’s look at the math.

First- break your alumni base into two segments:

• currently donating alumni

• non-donating alumni

THE ASSUMPTIONS:

1. The ratio of “Total Alumni Population” to “Total Donors Who Do Give” is roughly two-thirds to one-third or less.

2. The study analyzes life time giving over 10 years and predicts donation amounts for alumni that have never donated by comparing non-donors to the donating population using data modeling techniques to predict giving behavior.

3. Alumni who gave anytime over the 10- year period were considered donors. 

Simply, the math for donor analysis to realize 30-35% giving rate return is:

 Number of non-donors (life time giving = $0) who are predicted to give anything > $0

+

Number of Donors who’s predicted annual gift amount is greater than their most recent gift amount

-----Divided by-----

Total Universe of Alumni in the Study

AN EXAMPLE FROM OUR WORK WITH A MID-SIZED UNIVERSITY:

This university has 19,800 total alumni in this study with 3,300 alumni giving annually. Therefore, it meets the 2/3:1/3 threshold.

The analysis of their “never donated” population of 16,500, it predicted that 11,728 of those who had never donated to give something greater than zero. Moreover, out of the 3,300 of those who do give, it predicted 1,263 donors to give an annual gift in an amount greater than their most recent gift.

Therefore,

(11,728+ 1263)/19,800 or

12991/19800 = .656

1-.656= 34%

Cheri Sullivan, Director of Advancement Services at St. Edward’s University had this to say about applying this data analysis to her total alumni base:  

The Analysis provided great insight in to our alumni donors so that we could start building a data-informed strategy to increase donor retention. …(we) identified some major gift prospects we did not have on our radar before. We have only just begun to fully capitalize on the results we received.

By creating a blueprint for individual giving that identified those undergraduate alumni who could increase their giving rate over a third to 34% in this fiscal year, this head of development was able to provide her annual, leadership and major gift officers actionable data to use in their outreach efforts and to pinpoint those donors to spend time on. Time is our most precious asset in this race for fundraising dollars and knowing where to spend your time for the return is invaluable.