Transcript Gifts of Real Estate

Discovering, opening and
developing PG relationships
with donor surveys
Doug Puffer, Director , Planned Giving
Simon Fraser University
November 9, 2012
Warm the Brain
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Overview
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Planning to Market
Prospect Profiling
Data Analysis
Finding the Big Ones
Get Visible
Numbers:
• 0
• 18000 X 2, 50+
• 3.5 years = 7 touches
• 0.5 % = 630
• 302 info, 52 leads, 31 discoveries
Get Visible
Words:
• Plan ahead
• Develop demographic
• Get the message out
• Benchmark standards (CPL, CPC)
• Results justify further investment
Bequests and Leads
Profiling and Data Mining
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Best prospects for a gift by will
Profile first
Parameters second
Data mining third
Prioritize lists
Targeted markets
In the beginning, keep it simple!
[(A>50)+MI55+(R+F+M)]=PGP
In the beginning, keep it simple!
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Instant results matter
Age = 50+
Title = Miss
Loyal Donors = R
Monthly Donors = F
Generous Donors = M
Include: who gives, who will, who
didn’t, who did, who won’t
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Planned Giving Propensity
Who said “YES”
Who said “NO”
Who did but you didn’t know
Giving records, degrees, job info, addresses, phones, email,
sports, campus clubs, reunions, ...everything!
The SFU Algorithm
Refined Profile
•Alumni volunteer
•Regular donor (3/7 years)
•Job title
•Number of actions
•Highest degree
Finding the Big Ones
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Donors love you
They know you
Right age
Good records
Invisible to “Normal” prospect research
Limited budget
Bequests and Leads
Finding the Big Ones
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Donors love you
They know you
Right age
Good records
Invisible to “Normal” prospect research
Limited budget
Results
Calling Pool
Completion Rate
New Leads
Potential
Discoveries
Expected Value
Actual Cost
SFU
UBC
QU 2008
4554
831
4957
48%
428
369
35
$3.15M
$15.7K
66%
110
208
17
$2.04M
60%
117
730
60
$6.60M
Brain Science
Prof. Russell James, Texas Tech
• Bequest giving and current giving stimulate different parts of the
brain.
• Different motivators and de-motivators are at work.
• Charitable bequest decision making engages parts of the brain
associated with, what researchers call, “management of death
salience.”
• Charitable bequest decision making involves reminders of one’s
mortality.
• A charitable bequest decision involves the internal visualization
system for recalling autobiographical events in relation to the
charity.
References:
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Does Data Mining Really Work for Higher Education Fundraising?
A Study of the Results of Predictive Models Built for 5 Higher Education Institutions
By Peter B. Wylie and John Sammis
http://www.case.org/Documents/Books/29502/Does_Data_Mining_Really_Work.pdf
Data Mining and Alumni Association Membership By Peter B. Wylie and John
Sammis.
http://www.case.org/Documents/Publications_and_Products/Reports/DataMiningandAlum
niAssociationMembership.pdf
A pauper’s guide to electronic screening. Guest post by Peter B. Wylie
http://cooldata.wordpress.com/2010/09/21/a-paupers-guide-to-electronic-screening/
Data Mining for Fund Raisers Peter B. Wylie
C.A.S.E. (2004).ISBN-10: 0899643809 or ISBN-13: 978-0899643809
Fundraising Analytics: Using Data to Guide Strategy Joshua M. Birkholz (April 4,
2008)AFP/ John Wiley pub. ISBN-10: 047016557X or ISBN-13: 978-0470165577
Charitable Estate Planning as Visualized Autobiography: An fMRI Study of its
Neural Correlates (February 6, 2012). James, Russell N. and O'Boyle, Michael W. ,
Available at SSRN: http://ssrn.com/abstract=2000345 or
http://dx.doi.org/10.2139/ssrn.2000345
Thanks for listening!