The document discusses the metrics system developed for alumni relations at Lewis University, focusing on measuring engagement among alumni to enhance decision-making and program effectiveness. Key metrics include event attendance, giving frequency, and volunteerism, which help identify trends and opportunities for improving alumni engagement and fundraising efforts. The system has resulted in significant cost savings and increased donor participation by utilizing data-driven insights to target the right alumni prospects.

1. Presented by: Reggie Bustinza
Director of Alumni Relations
Lewis University
Metrics system by Reggie Bustinza and Joe Volin

2.  Romeoville, IL
 Private Catholic institution
 6,700 students (4,700 undergrad, 2,000
grad)
 40,000 alumni – primarily in Chicago area
 Alumni Relations staff of 3
 Database: Raiser’s Edge (“R/E”)

3.  Why try to measure engagement?
 The Lewis System
◦ Process
 The Value in Metrics
 Results

4.  Metrics can guide decision making
◦ Spot trends
◦ Identify opportunities
◦ Abandon dead ends
◦ Quantify program success
 More efficiency & efficacy
 Justify our existence

5.  Established in 2012
 Created in-house
 Created by Alumni Staff (Joe Volin and Reggie
Bustinza)

6.  Requirements
◦ Work with existing data
◦ Comprehensive
◦ Searchable (integer data)
◦ Valid as aggregate and/or individual data
◦ Easy to understand
 Not required, but nice to have…
◦ Inexpensive to implement
◦ Ability to run ourselves, as frequently as we want
OR dynamic
◦ Option to exclude data to look for correlations
◦ Simplicity

7.  Process
1. Make sure database can handle it
2. Identify what relevant data we track – “What
information do we have that shows some kind of
engagement?”
3. Assign relative values
4. Test
5. Repeat until values are no longer questioned

8.  Step 1: Can Database Handle It?
 Step 2: What do we Track?

9.  Is it indicative of engagement?
 Is the data consistent and accurate?
 Will we keep tracking it?
• Event Attendance
• Giving – how much
and how often
• Valid email
• Open emails
• Social media
• Valid address
• Valid business info
• Board member
• Award winner
• Legacy parent
• Campus visits
• Interested volunteer
• Active volunteer

10.  Can we categorize?
Events
Event Attendance
Giving
Giving – how much and how
often
Communications
Valid email
Open emails
Social media
Valid address
Valid business info
Volunteerism
Active volunteer
Board member
Interested volunteer
Other
Award winner
Legacy parent
Campus visits
Employee
Affinity Partners

11.  Challenges
◦ Not all board members are equally engaged.
◦ How stratified should we make giving levels?
◦ Free events vs. Paid events
◦ How long is an activity valuable?

12.  6 scores are actually produced
◦ 1 for each category
◦ Overall Engagement Score (sum of each category)

13.  Share values with colleagues for feedback
 Run the numbers, see what results are
 Spot check results
 Pull top 10, top 20, top 50, top 100 alumni
◦ Does it add up?
◦ If not, why?

14.  Tweak values, repeat test

15.  Run Quarterly (past 12 months)
 Exported each category to Excel where values
are assigned and coded
 SPSS is used to merge data
 Import integers back into Raiser’s Edge

16. Strengths Weaknesses
 Can run in house
 Values recent activity
over old activity
 Results are easy to
understand
 Some data can be
suspect (eg: acquired
mailing lists)
 Have to export, use
two programs, then
import for scores
 As data points are
added, historical
scores are distorted

17.  Metrics are half of the battle. The real question is: How will you
use this tool?
◦ Whittle mailing lists
 We have re-allocated more than $15,000 in printing costs in the 3 years
since we have had metrics.
◦ Identify prospects that were under-the-radar
 Identified 550 top engaged alumni with high wealth scores that had not been
previously assigned through traditional prospect research
 Resulting in 170 portfolio assignments; and 45 initial visits during Fiscal Year
2015
◦ More efficient Annual Fund calling lists
 118 new donors in the categories that utilized engagement metrics for
further segmentation (FY14 vs FY15)
◦ Identify potential affinity groups
◦ Evaluate programming

18.  Advancement programming can create higher
levels of engagement.
 Higher levels of engagement lead to higher
giving participation.

19. Category Giving Events Comm. Vol. Other TOTAL
All Alumni 1.36 0.19 9.52 0.06 0.22 11.08
Young Alumni 0.99 0.24 10.56 0.07 0.09 11.95
Athletes 3.68 .64 10.24 .10 .35 14.4
Volunteers 9.42 4.83 16.31 4.82 1.15 36.54
Aviation 0.84 0.1 8.72 0.07 0.19 9.92
Law & Justice .90 .12 8.82 .04 .25 10.13

20. Top X % Point Cutoff
1% 48
5% 26
10% 19
25% 13
50% 8
75% 6

21. Top X % Point Cutoff
1% 26
5% 19
10% 17
25% 11
50% 8
75% 6

22. Top X % Point Cutoff
Giving
Participation
Giving
Participation
1% 48+ 402 / 402 100%
5% 26-47 1530 / 1621 94.4%
10% 19-25 1218 / 2540 48.0%
25% 13-18 735 / 5242 14.0%
50% 8-12 395 / 17701 2.2%
75% 6-7 17 / 6334 0.3%
100% 0-5 3 / 4736 0.06%

23. Top X % Point Cutoff
Giving
Participation
Giving
Participation
1% 26 301 / 353 85.27%
5% 19-25 508 / 1113 45.64%
10% 17-18 652 / 2703 24.12%
25% 11-16 964 / 5944 16.22%
50% 8-10 623 / 6116 10.19%
75% 6-7 474 / 8202 5.78%
100% 0-5 284 / 11245 2.53%

24. 2013 2015 Change
Engagement 9.81 11.08 +1.27
Giving-
Independent
Engagement
8.425 9.72 +1.295
Giving
Participation
6.7% 7.0% +0.3%
Total Population: 35536

25. 2013 2015 Change
Engagement 8.92 10.13 +1.21
Giving-
Independent
Engagement
8.05 9.23 +1.18
Giving
Participation
4.1% 4.7% +0.6%
General
Population
6.7% 7.0% +0.3%
Total Population: 3965

26. 2013 2015 Change
Engagement 12.83 14.56 +1.73
Giving-
Independent
Engagement
10.04 11.33 +1.29
Giving
Participation
14.4% 16.4% +2.0%
General
Population
6.7% 7.0% +0.3%
Total Population: 2809

27. 2013 2015 Change
Engagement 8.56 9.92 +1.36
Giving-
Independent
Engagement
7.72 9.08 +1.36
Giving
Participation
3.9% 4.3% +0.4%
General
Population
6.7% 7.0% +0.3%
Total Population: 3909

28. 2013 2015 Change
Engagement 29.1 36.54 +7.44
Giving-
Independent
Engagement
21.33 27.11 +5.78
Giving
Participation
36.7% 44.0% +7.3%
General
Population
6.7% 7.0% +0.3%
Total Population: 400

29.  There IS a correlation between Engagement and Giving
 Its too early to tell if a general engagement push can lead
to increased giving
 Volunteerism is the individual engagement component
that can lead most directly to increased giving
 The surest way to get more gifts is to ask for them… but
metrics can show you who to ask
 TBD: Strength of correlations within engagement
(volunteerism vs. communications vs. events)
 TBD: Different engagement techniques within variable
groups

31. Contact:
Reggie Bustinza
Director of Alumni Relations
(815) 588-7542
bustinre@lewisu.edu
Joe Volin
Assistant Director of Alumni Relations
(815) 836-5472
volinjo@lewisu.edu