Presented by: Reggie Bustinza
Director of Alumni RelationsLewis University
Metrics system by Reggie Bustinza and Joe Volin
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”)
Why try to measure engagement?
The Lewis System◦ Process
The Value in Metrics
Results
Metrics can guide decision making◦ Spot trends
◦ Identify opportunities
◦ Abandon dead ends
◦ Quantify program success
More efficiency & efficacy
Justify our existence
Established in 2012
Created in-house
Created by Alumni Staff (Joe Volin and Reggie Bustinza)
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
Process1. 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
Step 1: Can Database Handle It?
Step 2: What do we Track?
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
Can we categorize?
EventsEvent Attendance
GivingGiving – how much and how often
CommunicationsValid emailOpen emailsSocial mediaValid addressValid business info
VolunteerismActive volunteerBoard memberInterested volunteer
OtherAward winnerLegacy parentCampus visitsEmployeeAffinity Partners
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?
6 scores are actually produced◦ 1 for each category
◦ Overall Engagement Score (sum of each category)
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?
Tweak values, repeat test
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
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
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
Advancement programming can create higher levels of engagement.
Higher levels of engagement lead to higher giving participation.
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
Top X % Point Cutoff
1% 48
5% 26
10% 19
25% 13
50% 8
75% 6
Top X % Point Cutoff
1% 26
5% 19
10% 17
25% 11
50% 8
75% 6
Top X % Point CutoffGiving
ParticipationGiving
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%
Top X % Point CutoffGiving
ParticipationGiving
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%
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
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%
GeneralPopulation
6.7% 7.0% +0.3%
Total Population: 3965
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%
GeneralPopulation
6.7% 7.0% +0.3%
Total Population: 2809
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%
GeneralPopulation
6.7% 7.0% +0.3%
Total Population: 3909
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%
GeneralPopulation
6.7% 7.0% +0.3%
Total Population: 400
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
Contact:
Reggie BustinzaDirector of Alumni Relations(815) [email protected]
Joe VolinAssistant Director of Alumni Relations(815) [email protected]
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