West Texas Rehabilitation Center Foundation, San Angelo, Texas
Productivity Profile |
Blackbaud Analytics |
In the heat of the West Texas summer, unannounced
visits to donors in their homes can hardly
be called “cold calls.” Rather, Roger Ellison calls these
visits his “screen door ministry.” It’s the primary
way Ellison meets planned giving prospects for West Texas Rehabilitation
Center Foundation, where he is vice president for planned giving.
“Lots of hard work produced good results,” said Ellison,
who drives approximately 40,000 miles a year
across two-thirds of Texas to call on donors. Direct mail, newsletters
and referrals from Board members, staff and other donors supplement
the screen door ministry. But he believed
the mailings in particular weren’t as effective as they could
have been. “We felt like we were sending costly quarterly newsletters
and direct mail pieces in much too blind a fashion. We needed something
to help us aim in the right direction.”
In the past, Ellison had used various methods to target planned giving prospects: age and giving history, a generosity/passion grid he developed, and an informed mental comparison of how a donor’s information compared to what he knew about their existing planned givers.
Ellison realized that as his pool of prospective donors and other responsibilities grew, he would need to find ways to target donors more efficiently. “I felt a need to synergize hard work with smart work — to systemize what I had been trying to do by intuition.”
After extensive research and investigation, he decided that Blackbaud Analytics’ planned giving data modeling service offered the right approach for the Foundation. “As I delved into the modeling process, I became convinced that Blackbaud Analytics would produce results that were closer to real world circumstances than any other tools.”
Ellison was not concerned with knowing who among his prospects had the most money. Rather, he focused on who was likely to consider various types of planned gifts. “I already know that Bill Gates and Warren Buffett are the two wealthiest persons in America, but that is irrelevant to me,” he said. “I want to know who is likely to be interested in a planned gift for our work at West Texas Rehabilitation Center. If the propensity to make a planned gift can be estimated, the wealth issue will take care of itself.”
The Foundation put 59,000 of its individual donor records through the
modeling process. Upon
receiving the results, Ellison immediately checked the Blackbaud Analytics’
rankings for people
who had already made a planned gift. He was thrilled to see that 100
percent of their Charitable
Gift Annuity (CGA) donors were in the top half of the Blackbaud Analytics
rankings and 91
percent in the top quartile. “That alone was impressive and gave
us confidence,” said Ellison.
The Foundation’s staff uses the modeling results to determine
who receives the planned giving
newsletters, which are theme-driven. Ellison explained: “When
the theme is CGAs, we weight
the mailing list heavily toward those donors with high Blackbaud Analytics
annuity scores. The
same for issues with a bequest, appreciated assets or a general planned
giving theme — we use
the respective Blackbaud Analytics scores to drive the mailing list.”
The Foundation is also in the planning stages of an endowment campaign.
“We’re trying to find
the planned givers among 59,000 donors,” Ellison said. We know
they are out there, and we feel
comfortable that Blackbaud Analytics will help us find them.”
What results has Ellison seen so far? “We’re already at
the gravy stage. Within just a few months,
the Blackbaud Analytics scores have already helped us find the gifts
that have paid for the
modeling and the costs of our direct mail,” he said.
Ellison is able to make better use of his time as well by prioritizing
his “screen door” visits based
on donors’ annuity scores. “What I am finding is that these
people have all the characteristics I
associate with gift annuity donors. This increases my confidence in
Blackbaud Analytics’ planned
giving propensity scores.”
