Transcript PART1 MARCELLE

Data Analytics:
A powerful insight into your donors’
giving potential
Insight SIG
19th February, 2013
Definitions
 Data Mining: “the extraction of meaningful
patterns of information from databases”
 Analytics: “how an entity arrives at an optimal or
realistic decision based on existing data”
 Predictive Modeling: “the process by which a
model is created or chosen to try to best predict
the probability of an outcome”
2
The Goal: Fundraising Intelligence
“Fundraising Intelligence can be described as the process of gathering
data, turning it into actionable information through analysis, and
making it accessible to the right people, at the right time, to support
fact-based decision making.”
3
Data Mining
What data is
important?
What type of
data should we
collect?
Where are the
sources for data?
4
The Devil’s in the Data….
Types of Data
5
Sources of Data
 Financial
 Internal
 Biographical
 Volunteer Information
 Philanthropic
 Research Information
 Behavioral
 Electronic Screening
Data, Data and More Data
Biographical

Age

Marital Status
Giving History
Contact

Last Staff Contact

Event Attendance

Last Solicitation

Amount of Last
Solicitation

First Gift Date / First Gift
Amount

Last Gift Date / Last Gift
Amount

Total Giving / Total # of gifts

Largest Gift Amount /
Largest Gift Date

Gender

Business Title

Email address

# of Contacts Overall

Business/home phone



Others?
# of Contacts in last 3
years, 5 years
Average gift (annual vs.
major)

Others?

Other factors?
6
Electronic Screening of Data
Q: How do I select the right type of screening for my organization?
A: Determine your organizations
needs….
 Do you need to screen your entire
database or does it make more
sense to screen a targeted
sample?
 Do you want hard asset data?
 Or demographic data?
7
Electronic Screening Data: Results
 Capacity Ratings
 Propensity to Give
Ratings/Indicators
 Financial Information
 Income
 Real Estate
 Stock Holdings
 Gifts to Others
 Age/Children
 Household Interests
8
Data Analysis vs. Statistical Modeling
Data Analysis
Statistical Modeling
Definition
• Analysis of specific business
questions and the development
of foundational insights
• Building statistical models to
predict desired behaviors
Techniques
• Hypothesis Based Approach
• Univariate & Bivariate Analysis
• Multivariate Analysis
• Linear/Logistic Regression,
Cluster Analysis, etc
Tools
• MS Excel most commonly used
• SAS, SPSS are most popular
9
Segmenting Your Data
Distribution of data match results
£2,500,000+
£500,000-£2,499,999
£250,000-£499,999
£125,000-£249,999
£50,000-£124,999
£25,000-£49,999
£12,500-£24,999
£7,500-£12,499
£5,000-£7,499
£2,500-£4,999
£1,250-£2,499
£1-£1,249
0
200
400
600
800
Number of matches
1,000
1,200
1,400
More than just the Millionaires……
Distribution of data match results
£2,500,000+
£500,000-£2,499,999
£250,000-£499,999
£125,000-£249,999
£50,000-£124,999
£25,000-£49,999
£12,500-£24,999
£7,500-£12,499
£5,000-£7,499
£2,500-£4,999
£1,250-£2,499
£1-£1,249
0
200
400
600
800
Number of matches
1,000
1,200
1,400
Segmenting Prospects into Solicitation Pools
Vendor screen output
Internal data
Filter Criteria:
1) Age > 60
Filter Criteria:
4) Recent Gifts
Filter Criteria:
2) Property Value
Filter Criteria:
3) Company Director
Filter Criteria:
5) Event Attendance
Most promising
legacy prospects
Integrate Wealth Intelligence
Integrating wealth data into your DMS/CRM helps you:
Individual’s
record in DMS
 Prepare for a meeting
 Refine ask amounts
 Make informed decisions
Bring Ratings &
Key Datapoints
into the DMS
New Data from
Screening
 Automate marketing and
donor outreach activities
 Save time and streamline
workflows
Calculate
Ratings &
Scores
Classify by
Donor Pool
Summary
 Consider the predictive value of your
internal data
 Use screening to add external data that
increases your knowledge about your
prospects
 Combine internal and external data to
segment your database
 Create data-driven donor pools for every
fundraising campaign
Analytics = Powerful Insight into your Data = Actionable Results
Contact Details
Marcelle Jansen
Garrick House
26 – 27 Southampton St.
London, WC2E 7RS
+44 20 3318 4835
+44 20 7717 8483
[email protected]
www.wealthengine.com