RiF Scotland 2016 Final

WEALTHENGINE.COM | [email protected] |+44 207 717 8483WEALTHENGINE.COM | [email protected] |+ 44 207 717 8483

ProfilesWho, why & when?

Marcelle Jansen, Wealth Engine

David Scott, University of Stirling

WEALTHENGINE.COM | [email protected] |+44 207 717 8483

Our presentation inspiration:

“They want me to be able to produce at a rate of 7 bios on

individuals per day and 1 foundation profile per day. That

works out to 35 individual bios per week and 5 foundation

profiles per week.

“That's a total of 160 bios in total per month.”

1,920 annually!


Guess the quotation:

“When they got back to the cabin they made a midnight snack

and heated up the coffee. Mikael took a look at the almost 500

pages that Dragan Armansky’s favourite researcher had

produced for him.

“You’ve done a fantastic job of digging up these facts in such a

short time,” he said.

“Thanks. And thanks also for being nice enough to come up here

and report on it…”


500 pages!



Three questions immediately raised:

• Who do you target?

• Why should you target them?

• When do you provide line management with the profile?

Additionally, what is reasonable in terms of proactive

research against reactive research?


Find me a wealthy prospect!


Who to Profile?The Intersection!3 NOVEMBER 2016 MARCELLE JANSEN, DIRECTOR, WEALTHENGINE UK


Agenda

CPA

Segmenting Based on Capacity

P2G Scoring

Measuring Engagement

Segmentation Results

Solicitation Pools

Creating Affinity Scores

Major Gift Model Predictors

Taking Action!


Major Gift Prospects Have CPA

Capacity: The financial abilityto make a major gift at aspecified threshold

Propensity: The inclination tomake charitable gifts to anycause or charity

Affinity: The linkage betweena donor and the charityand/or mission

Capacity

AffinityPropensity



0 200 400 600 800 1,000 1,200 1,400

£1-£1,249

£1,250-£2,499

£2,500-£4,999

£5,000-£7,499

£7,500-£12,499

£12,500-£24,999

£25,000-£49,999

£50,000-£124,999

£125,000-£249,999

£250,000-£499,999

£500,000-£2,499,999

£2,500,000+

Distribution of data match results



0 200 400 600 800 1,000 1,200 1,400

£1-£1,249

£1,250-£2,499

£2,500-£4,999

£5,000-£7,499

£7,500-£12,499

£12,500-£24,999

£25,000-£49,999

£50,000-£124,999

£125,000-£249,999

£250,000-£499,999

£500,000-£2,499,999

£2,500,000+

Distribution of data match results


P2G 1’s and 2’s make up 42% of the file (2,845 records) and should be considered among the priority for major gifts.

38%

4%

31%

15%12%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

1 2 3 4 5

P2G Scores


Measuring Engagement

Take all positive supporter actions…

1. Giving (measured by recency, frequency and value)

2. Response ration (number of responses divided by number of solicitations)

3. Number of areas ‘present’ in )cash giving, DD, legacy, volunteering, etc.)

4. Tenure (with evidence of continuous giving)

5. Email actions (open, click through, response)

6. Membership and specialist communications/publications sign ups

7. Has a valid address, email and telephone

8. Opt-outs (downgrade their score)

Then build an aggregate score for every supporter to gauge how into you your supporters are

This has direct application to your communications planning, supporter development program, pricing strategy and targeting AND can also be used as a variable in itself within your data models

14


Creating Affinity Scores

Based on internal data, you can develop a simple scoring model for affinity, for example:

Criteria Points

Event Attendance 1-3Facebook Friend 1 Member of LinkedIn Group 1Volunteer Status 1-2Tenure 1-3Giving History 1-3

Scores:

0-4 Low Affinity5-9 Moderate Affinity10-15 High Affinity

Affinity


Giving as a Proxy for Affinity

Each of your donors are scored in terms of:

Recency

Frequency

Money

The resulting total is your proxy affinity score


Combining CPA: Donor Segments

Donors are screened by the RFM scores and Estimated Giving Capacity

They are then rank ordered and placed into 7 segments

17

£25K+ £5k+ <£5K

VHAngels True Believers Loyalist

H

M High TouchFoundational

Givers Pyramid Base

L Wish List

Estimated Giving Capacity

RFM

Sco

res

Tota

l


Donor Segments by P2G Score

Donor Segment P2G 1 P2G 2 P2G 3 P2G 4 Totals

Angels 265 13 43 10 331

True Believers 93 26 125 69 313

High Touch 80 7 14 1 102

Loyalists 10 3 57 11 81

Wish List 2 0 0 0 2

Foundational Givers 60 12 65 33 170

Pyramid Base 4 1 24 6 35

Totals 2,528 291 1642 899 5,360

Angels, True Believers and High Touch donors with P2G scores of 1 and 2 should be considered top priority for potential major gifts


Segmentation Results: Prospects

Forerunners

- These are your future angels! These prospects have the highest capacity to make donations to your organization.

- Estimated Giving Capacity > £25,000

1,328 in your file

1,040 are P2G1

15 rated at £500,000-£2,499,999

- This segment is the pipeline for leadership gifts.

- Estimated Giving Capacity between £5,000 and£24,999

2,782 in your file

- This segment with lower capacity are the pipeline of future regular donors.

- Estimated Giving Capacity < £5,000

216 in your file

Forerunners

Future Leaders

Building Blocks

Future Leaders Building Blocks


Goal:

Identify your top 200 major donor prospects

20


Segmenting Prospects into Solicitation Pools

21

Most promising

Major Donor

prospects

Vendor screen output

Internal data

21

Filter Criteria:

3) Company Director

Filter Criteria:

4) Investment Portfolio

Filter Criteria:

2) Property Value

Filter Criteria:

1) Age > 40

Filter Criteria:

4) Recent Gifts

Filter Criteria:

5) Event Attendance

Filter Criteria:

6) Tenure


Major Gift Model

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

£50 £100 £200 £300 £500 £1,000 £1,500

% o

f M

ajo

r G

ift

Do

no

rs

Largest Gift Amount

Dependent Variable Largest Gift Amount >= £500

Used logistic regression to build model

Selected larger gift of £500 or more

303 donors met this threshold in the sample of 48,546 records

Modelling identifies individuals in the file with attributes similar to the 303 donors

Identified predictive attributes by analyzingacross giving, wealth, and demographic variable


Major Gift Model Predictors

Major Gift Model

Predictors Description SourceRank by

Contribution to Score

Attended Events Number of alumni events attended (+) Client 1

Total Number Gifts Total number of gifts (+) Client 2

Total Real Estate Total real estate value (+) WealthEngine 3

Company Value Company values (+) WealthEngine 4

Perfect Match to Matrix Indication that a constituent matched perfectly to Matrix investor database1

WealthEngine 5

MOSAIC Code Lifestyle/demographic coding is ‘A4 Serious Money’ (+) Client 6

Age Age (+) WealthEngine 7

Perfect Match to ZoomIndication that a constituent matched perfectly to ZoomInfo database2

WealthEngine 8

1 Matrix Investor data identifies private investors and provides an estimated private investment portfolio to highlight an individual’s investment interests and affinities.2 ZoomInfo reports include such information as names, titles, addresses, phone numbers, schools of attendance, past and current employment and board memberships.


Newly identified major gift prospects require action

Attribute Averages Top New Prospects Others

Count203 47,788

Capacity£144,733 £13,749

Total Giving£1,249 £41

Event Attendance2.0 1.6

Number of Gifts7 1

Company Value£189,996,726 £1,830,503

Real Estate Owned£1,393,225 £257,018

Age67 60

101 of the top 304 prospects were already identified /qualified or under management

203 are completely new major gift prospects ready for verification and qualification


Take Action with Major Gift Prospects

203 Prospects

Average Capacity £144,733

Average Total Giving £1,429

Verify Data – Is this a major gift prospect?

Qualify with contact – is there propensity and affinity?

Assign for cultivation

Major Donor Prospects


Case Study: University of Stirling – 5th Jan 2016 to date

• 5,300 records reviewed (addition of Potential to Give, contact

details, etc. – vast majority individuals);

• 2,504 Major Gift giving potential (£10k+ over 5 years);

• Potential to Give Scoring established;

• Affinity Scoring established;

• Likelihood Scoring Established in principal;

• 658 Short Profiles;

• 53 Full Profiles.



Steps and stages


Steps and stages



In conclusion, please consider:

• Capacity;

• Propensity;

• Affinity;

• Profile Prioritisation (Provisional/Short v Full);

• Strategy Creation;

• Ongoing Review.


Questions3 NOVEMBER 2016 MARCELLE JANSEN, DIRECTOR, WEALTHENGINE UK

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RiF Scotland 2016 Final

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