Target Analytics 1 © 2014 Blackbaud PROSPECT RESEARCH: BUILDING A BRIDGE TO FUNDRAISING SUCCESS

Target Analytics 1© 2014 Blackbaud

PROSPECT RESEARCH: BUILDING A BRIDGE TO FUNDRAISING SUCCESS


PRESENTER:

• Founder of Blackbaud Analytics, which became Target Analytics• 34 years as development officer and consultant• Author and Frequent Presenter on Planned Giving, Major Gifts,

Prospect Research and Industry Topics • Law degree, University of Wisconsin-Madison• Lives in Lafayette, California

Lawrence Henze, J.D., Principal Consultant


AGENDA

• Prospect research philosophy• Entire database Research

• Metrics• Descriptive analytics• Predictive analytics

• Individual research• Worth knowing?• Discoverable?• Where is the information found?

• Putting it together – Cohesive Development• Summary and Questions

• How much information do I need to know?


IDENTIFYING PROSPECTS: BEST PRACTICES

Past Behavior

Analytics and

Predictive

Modeling

Wealth Screenin

g

Research

Field Qualifica

tion


P ROS P E CT RE S E ARCH P HIL OS OP HY






START WITH TRUE UNDERSTANDING OF YOUR FUNDRAISING ‘STATUS QUO’

Traditional Pyramid ‘unlikely’


A MORE LIKELY SCENARIO


PROSPECT IDENTIFICATION SUCCESS…

• Is most likely when:- You possess accurate information on and awareness of your current

status- The process is fluid, ongoing, and not reactionary- The results are integrated into engagement, cultivation and

solicitation strategies- Those strategies are supported by a relationship management

system- You have a commitment to evaluate and monitor your progress, and

revise strategies, programs to fit the data- There is accountability


WHAT ARE YOUR PROSPECT IDENTIFICATION NEEDS?

?

?

?

?


WHAT ARE YOUR PROSPECT IDENTIFICATION NEEDS? CREATE A GIFT CHART TO REVEAL ANSWERS


WHAT ARE YOUR PROSPECT IDENTIFICATION NEEDS? CREATE A GIFT CHART TO REVEAL ANSWERS


BOTTOM-UP OR TOP-DOWN?

Major

Annual


PROSPECT IDENTIFICATION THROUGH ANALYTICS

• What analytics has taught us:- Analytics may validate tradition, and also…- Indicate change- Certain fundraising axioms are not supported by data- Predictive analytics more accurately identifies giving prospects at all

levels- Planned giving:

• Loyalty and fiscal conservatism more important than age

- Major giving:• Most major giving prospects are discoverable through annual giving

behavior


Low likelihood scores and low target giving ranges

Minimize investment Consider reduced resource

application

SEGMENTATION FOR ACTIONABLE RESULTS

Combining Likelihood and Capacity

Highest scores and high assets

Further qualification and research May need individual cultivation

Lower likelihood scores, but high target giving ranges and assets

Need to be sold on your mission

Longer term cultivation

High likelihood scores and low or mid-level target giving ranges

Targeted upgrade, mid-level gift strategies

Increase annual giving

givi

ng li

kelih

ood

giving capacity

Low PotentialLong Term Prospects

High TouchUpgrade or

Acquire


Predictive modeling is far more effective at identifying major/principal donorsOnly 31% of the revenue came from new donors with publicly identifiable assets

Only 13% of the revenue from the test group had publicly identifiable wealth.

Modeling is very effective identifying mid-level and planned gift prospects

Wealth data alone very ineffective at identifying annual and planned gift prospects

LESSONS FROM 21 YEARS OF ANALYTICS


THE CHANGING LANDSCAPE OF PROSPECT RESEARCH

• More research professionals are comfortable or proficient in analytics- More emerging experts

• Demand for ongoing metrics and analytics is increasing• Wealth is becoming harder to quantify, let alone obtain• Growing interest in determining affinity, engagement, as more

professionals accept the dominant role of affinity in the giving equation• Better, more accurate behavioral, financial, and demographic data

available for analytics• Terms such as BI (business intelligence), BIG DATA, and analytics are

found everywhere• The question is: Are we doing the right analytics?


ANALYTICS/PROSPECT SCREENING

• Using data mining, predictive modeling, and wealth/hard asset appends to augment your knowledge of donors and prospects

• To provide a rating or ranking system that allows you to differentiate or segment your prospects- Increase effectiveness and efficiency

• A process that begs for an implementation plan• A process that begs for implementation


WHAT DRIVES SCREENING PROJECTS?

• Identifying the Needs of the Organization• Planning for the Research• Develop Consensus and Commitment• Application of the Results- Owning the Results- Distributing the Results- Initial Action Items- Relationship Management

• Evaluation


FAIR WARNING: THERE WILL BE MATH IN THIS PRESENTATION


STANDARD DEVIATIONS AND OUTLIERS


IDENTIFYING THE SCREENING NEEDS OF YOUR ORGANIZATION - WARNINGS

• “There is great pleasure to be gained from useless knowledge” Bertrand Russell (1872-1970)

• The screening info you need is the data you use…everything else is fluff…don’t buy fluff

• Prioritize the needs of your organization• If you are screening with a vendor, make sure they care

about and respond to your needs- Beware of packages- See ‘fluff’ above


SCREENING NEEDS - TIMING

• “Should we screen?” has been replaced by “When should we screen?”• “When should we screen?” may be as painstakingly simple as “we will

screen when we have the budget”• Avoid budget limitations by undertaking internal data mining whenever

possible- Simple strategies presented later in PowerPoint

• Increase the likelihood that you will have future budget funds by implementing your current (next) screening effort fully


IDENTIFYING THE NEED FOR SCREENING

• “Wisdom outweighs any wealth” Sophocles, (496 B.C. – 406 B.C.) Antigone

• Don’t be seduced by wealth data alone, even if your needs are primarily in major giving and principal giving

• Propensity combined with capacity provides the best comprehensive measure of a prospect- This has been tested and proven



• Annual fund screening – the best place to start?- Remember the pyramid and ultimate giving

• Annual fund questions?- Who makes annual gifts? Is a member?- What does a loyal donor look like?- Who can give more?- Who is unlikely to give again?- Which lapsed donors are likely to be recaptures- Who gives at the same time every year?- Who gives via direct mail? Email? Telemarketing? Website?- Who is most likely to make an unrestricted gift? Restricted gift?



• Major giving or capital campaigns?- Identifying emerging major gift prospects- Pre-campaign screening- Mid-campaign screening- Post campaign screening

• Planned giving• Wealth Identification• Membership modeling/cluster analysis- Likelihood to be a member, renew, etc.- Membership groupings and characteristics

• Which other questions would you like answered?


INTERNAL DATA MINING – RFM ANALYSIS

• RFM Analysis- Recency (most recent gift this year, last year, or more distant)- Frequency (gave in each of the last three years, one of the last

three years, none of the last three years)- Monetary value (largest gift in three years > $100, $50-100, < $50


PLANNING FOR THE RESEARCH

• “A goal without a plan is just a wish”

Antoine de Saint-Exupery (1900-1944) author The Little Prince• Whether DIY or hired research, your goal should be to have the outline

of a plan in place before receipt of the results.• What are the key elements of the plan?


OBSTACLES TO PROSPECT DEVELOPMENT: THE SILO APPROACH

Annual giving

Donor relations

CRM

Shadow database

Membership

Special events

Major giving

Planned giving

Prospect Research

Prospects


KEY ELEMENTS OF THE PLAN

• Integration into your database/CRM software (priority)- Plan in advance to have technical resources scheduled for

incorporation of results into database- Speak with vendor references to identify potential issues for

software upload- Seek deadline from technical resource staff

• Utilization of delivered software- May be best place to house wealth data detail and conduct

additional searches- If upload into CRM is delayed, this software becomes more critical



• Creation of an implementation team- Include representative of each functional area to receive results or

to be affected by implementation- Opportunity to eliminate silo barriers- Team should explore cross-functional implementation ideas- Team leader should be “owner” of the data with authority granted by

advancement leadership.• Use deadlines rather than meetings to move action items forward- For example, discussion items for meetings to be shared in advance

along with specific implementation proposals



• Creation of an implementation team- Include representative of each functional area to receive results or

to be affected by implementation- Opportunity to eliminate silo barriers- Team should explore cross-functional implementation ideas- Team leader should be “owner” of the data with authority granted by

advancement leadership.• Use deadlines rather than meetings to move action items forward- For example, discussion items for meetings to be shared in advance

along with specific implementation proposals



• Distribution of the data to users- Research and development services staff probably best owners of

the data- Create business rules for data use

• Access rules• Update rules for wealth data

• Warning- Avoid data manipulation, replace with results implementation!- Vendor delivered tools can be very addictive- Data addicts often fail to implement



• Implementing wealth results- Will wealth data supplement modeling scores or serve as a stand-

alone rating system?- Will you share wealth results with development officers without

verification?- How will you use this data to identify new prospects?- What criteria will be used to eliminate or remove prospects from

existing portfolios?- How do you capture verification data from development officer call

reports?


ANALYTICS ON YOUR OWN

• Simple age analysis by size or type of gift• Gift size and frequency of solicitation• Years of giving before first major gift• Creating an engagement score- Quantity and quality of internal information


INTERNAL DATA MINING – RFM ANALYSIS

• RFM Analysis- Recency (most recent gift this year, last year, or more distant)- Frequency (gave in each of the last three years, one of the last

three years, none of the last three years)- Monetary value (largest gift in three years > $100, $50-100, < $50


• Grouping individuals of similar characteristics into respective categories

• Way of taking a lot of data and grouping people into subsets in a meaningful way

• Mosaic, PRIZM, PersonicX, Niches are all pre-made cluster data overlays you can purchase

CLUSTER ANALYSIS


• Mosaic Clusters- http://

www.experian.com/marketing-services/consumer-segmentation.html

• Example:

CLUSTER ANALYSIS

Autumn Years Established, ethnically-diverse and mature couples living gratified lifestyles in older homes

Aging in Place Middle-class seniors living solid, suburban lifestyles

Rural Escape Older, middle-class couples and singles living comfortable lives in rural towns

Settled and Sensible

Older, middle-class and empty-nesting couples and singles in city neighborhoods

http://www.experian.com/marketing-services/consumer-segmentation.html

http://www.experian.com/marketing-services/consumer-segmentation.html


CLUSTERS AND BEQUEST INTENTIONS

• Segment by known bequest intentions

• For example, 76% of bequest donors are described by 7 of the 26 clusters

• 24% of the non-bequest donors were also described by the same 7 clusters

• Concentrate on these prospects who are included in 1 of the 7 clusters for bequest cultivation and solicitation

Applications of cluster data

Mos

aic J

34

Mos

aic K

40

Mos

aic J

34

Mos

aic E

21

Mos

aic C

12

Mos

aic L

42

Mos

aic C

13

All Oth

er 'M

osaic

s'0

5

10

15

20

25

% of Bequest Donors

% of Donors


MODELING 101: 3 STEPS

What are you looking for? Common Denominators: The ModelScoring the Database

Annual donors?


QUESTIONS MODELING MAY ADDRESS

Annual giving likelihood Membership likelihood Transitional giving likelihood Major giving likelihood Principal giving likelihood Planned giving likelihood Bequest likelihood IRA contribution?

Target Gift Range Cause/Mission/Fund Restricted or Unrestricted giving Event attendance to giving Engagement modeling CRT likelihood Annuity likelihood Gifts of real estate?


Giving History

Biographical Information

Relationship analysis

ANALYTICS THROUGH MODELING

Gift Level Segmentation

Capacity and Wealth

Inclination and

Behavior Data

Your Data

Principal

Giving

Major Giving

Mid-Level Giving

Annual Giving or Members

hip


SAMPLE SEGMENTATION


75

725

1100

2450

Tier 1

Annual Giving

Mid-Level Giving

Major Giving

Principal Giving

P

P

P

P

P

P

P

P

P

P

P

P

P

P

PP

P

Tier 3

Tier 4

Tier 2

SAMPLE RESULTS – DATABASE SEGMENTATION DATABASE 10,000 RECORDS


ANNUAL FUND IMPLEMENTATION

• Upgrade potential• Acquisition of new donors from current prospect pool• Acquisition of new donors from new prospect pool• Elimination of poor prospects from solicitation process- Saving solicitation money- Reallocating to more fruitful fundraising activities


MAJOR GIVING IMPLEMENTATION

• Proactive prospect identification• Highlighting new prospects• Eliminating comfort prospects• Cleansing portfolios• Placing emerging prospects into an upgraded annual fund solicitation


Bequest Annuity CRT

Excellent Likelihood 536 413 112

Very Good Likelihood 2284 1,134 287

Good Likelihood 3,436 3,185 531

Planned Giving Segmentation


PLANNED GIVING IMPLEMENTATION

• Avoid concentration on older, wealthy individuals• Integration of communication strategies with annual giving and donor

relations• Train major gift officers on the basics of planned giving- Create awareness of split gift opportunities

• Recognition of loyalty• Put planned giving prospects into a relationship management system


RESEARCH IMPLEMENTATION

• PROACTIVE RESEARCH!• Become the architect of a prospect identification strategy• Expand the borders of prospect research• Career success and personal rewards• Think beyond traditional practices• Think globally, include prospects of all types• Have a plan for everyone- include those who will not be solicited- Use analytics to determine:

• Those who should be solicited• Those who should be personally solicited• Those who should be solicited less• Those who should not be solicited at all


INDIVIDUAL RESEARCH FOR THE NON-RESEARCHER


WHAT DOES THE PROFESSIONAL RESEARCHER HAVE THAT YOU DON’T?

• Time• Resources• Training• Experience


WHAT DO YOU HAVE?

• A need to know specific information about a prospect’s capacity• Access to public information• Personal knowledge of the prospect


WHAT DO YOU NEED TO KNOW?

• Where does your prospect live?• Does she/he own property?• Where does your prospect work?• Does that employment contribute to gift capacity?• Does the prospect give elsewhere? How much?• Where is your prospect connected in the community?


THINGS YOU WILL NEVER BE ABLE TO FIND

• Your prospect’s net worth• The size of his/her bank account• Documentation of conspicuous consumption• Most investments• Inheritances or family money• Almost anything the prospect wants to keep private


COUNT THE COST BEFORE YOU BEGIN

• Nothing worthwhile is free – even if you don’t pay money• Sometimes it’s worth it to pay a little money if you can- Trade cash for convenience - Vendors improve access to public data

• Don’t get trapped in analysis paralysis• Know that misinformation is mixed in with the information on many

sources• Give yourself a time limit- As you’re learning to use these resources, you might need more

time- As you gain proficiency, you should shoot for about 1 hour per

prospect


REAL ESTATE

• Assessment data is available on all US properties• The kind of home a family owns usually reflects its economic status• Primary source is the assessor for the county or township where the

property is located• Two values to look for- Assessed value- Market value

• Links to assessor’s websites:- www.pulawski.net 1 2 3 4- publicrecords.netronline.com

http://www.pulawski.net/


REAL ESTATE

• If you don’t know the county for the property, look it up here: zip4.usps.com/zip4/welcome.jsp 1 2 3- Search for the address- USPS server returns the standard format and a link to “mailing

industry information” for that property- Click on that link to get the county

• Get a rough idea of the market value at www.zillow.com. • Willing to spend a little money?- www.knowx.com has indexed real estate information from most

counties across the country- Search many counties simultaneously- Retrieving a single real estate record costs about $7.


DONATIONS

• Political donations benefiting federal candidates are reported by the Federal Election Commission

• Gift sizes are limited, but can total $115,500 in a two year election cycle

• Not a charitable gift, but…• Strong correlation between political giving and charitable giving• FEC report may also show home address, employer and business title• You’ll learn which way they lean politically


DONATIONS

• Go to herndon1.sdrdc.com/fecimg/norindsea.html- Enter the prospect’s name - You may need to try nicknames to get more complete results (John

Smith and Jack Smith)- Results screen shows all political donors by that name- Narrow down the results by noting the donor’s city and state

• Willing to spend a little money?- No legal requirement for charitable donations to be reported- www.nozasearch.com has collected over 50 million donation

records from annual reports- Can search by many different parameters including name and zip- Annual subscription costs $800

http://herndon1.sdrdc.com/fecimg/norindsea.html




PUBLIC COMPANY INSIDERS

• Insiders must disclose stock holdings in companies with which they have one of these relationships- Director- Top officer- 10% shareholder

• Most people who own stock are not insiders• Insiders typically are 1% or less of a nonprofit constituency• Go to www.j3sg.com 1 2- Quick Search- Insider Reports- Enter your prospect’s name and click Go

http://www.j3sg.com/


INCOME

• If your prospect is an insider, you’re in luck. Find insider top officer salaries here: - swz.salary.com/execcomp/layoutscripts/excl_companysearch.asp

• For most prospects, you’ll need to depend on salary surveys to get a ballpark estimation- www.salary.com - www.jobs-salary.com

http://www.salary.com/


OTHER PROFESSIONALS

• Lawyers: Martindale-Hubbell (www.martindale.com) • Doctors:- AMA (webapps.ama-assn.org/doctorfinder/html/patient.jsp)

- AIM Docfinder (http://www.docboard.org/docfinder.html)

• ZoomInfo: General profiles on professionals automatically compiled from Internet sources (www.zoominfo.com)

• LinkedIn: A social networking site for professionals (www.linkedin.com)

• Hoovers: A business directory searchable by executive name (www.hoovers.com/free) 1 2

http://www.martindale.com/


SOCIAL MEDIA SEARCH

• search.twitter.com – search Twitter on keyword• www.google.com/updates - search various social media on keyword• www.technoriati.com – search blogs

http://search.twitter.com/

http://www.google.com/updates

http://www.technoriati.com/


WHY NOT START WITH GOOGLE?

• A large portion of the Internet is invisible to Google• Google returns a lot of junk that must be filtered by hand• Targeted research yields targeted results• Use key words learned early in your research to improve your Google

search as the final step


STREAMLINING YOUR PROSPECT RESEARCH

• Do you have more time or more money?• If funds are available, vendors enable one stop shopping for prospect

data from public sources• Searches multiple public sources simultaneously• Enter a name and address to gather information that could take you

hours to collect manually


Phi

lant

hrop

ic

In

tere

sts

Har

d A

sset

Dat

a W

ealth

In

dica

tors

The largest collection of public donations available with more than 90 Million philanthropic gift records; NOZA adds over a million donation records to its database each month

An enormous database of corporate information: public and private company officers, private company ownership, officer bios, company descriptions and valuation

Public stock holdings/transactions by corporate officers, directors, major shareholders; transaction histories, updated stock prices through BATS Exchange

Primary and secondary holdings of real estate, estimated property values, including properties in trusts

Detailed self-reported biographical information including education, interests, children, etc.

Indicators of wealth, including presence of luxury items like planes, yachts, investments, income and net worth estimates

Identifies officers of two kinds of nonprofits: public charities (grant seeking) and private foundations (grant making – includes family foundations)

Market Guide from Reuters provides biographical and financial data on pubic company officers and directors

In-depth information on more than 2 Million federal elections contributions including amount and recipientFEC

WEALTHPOINT® DATA SOURCES


WEALTH IN CONTEXT

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

11.0%

14.0%

9.0%

17.0%

13.0%

9.0%

15.0%

10.0%

3.0%

Distribution of assets across net worth

Households with a net worth of $1.5M-$10M, 2004 IRS data, published in 2008[2] Includes cash and cash management accounts.

[3] Includes all government bonds, bonds issued by corporations and foreign governments, mortgages and notes, cash value life insurance, and diversified mutual funds.

[4] Includes Individual Retirement Accounts, annuities, and self-employed or Keogh plans.

[5] Includes non-corporate businesses, farms, and limited partnerships.


RESEARCH DONE, NOW WHAT?

• There is no magic formula that translates research data into the perfect ask amount

• Research is no substitute for good relationship building• Goals of your research- Find evidence of philanthropy - Suggest a gift vehicle- Rank prospects based on evidence of capacity- Estimate gift capacity

• Some estimation methods- A prospect may give 5-10% of annual income- Total real estate x 4 x 5% (only when real estate value >= $500K)- Total stock holdings x 4 x 5% (only when stock value >= $100K)- 5% of all known assets (only when assets ≈> $1 million)


PROSPECT IDENTIFICATION

Your best prospects are

already on your own database

Corollary:

Just because someone is wealthy doesn’t mean she’ll give anything to you


INTERNAL DATA MINING – PEER SCREENING

• Your board members and key volunteers are anxious to help you raise money

• A screener can review 100-200 names in 30 minutes or so• Questions- Do you know the prospect?- Estimated wealth and income- Rate sentiment toward the organization- Are you willing to make an introduction?

• Ideal conditions- Well connected screeners


CAN’T GET ENOUGH?

• www.lambresearch.com has an annotated list of links useful for doing additional prospect research, including alternatives to the sites shown here

• Your public library may have access to online and print resources that you would have to pay for

• www.wealthengine.com • www.blackbaud.com/targetanalytics• Need to hire a freelancer? Go here for an incomplete list of reputable

firms: home.comcast.net/~lambresearch/OtherPages.htm#ResearchFirms

http://www.lambresearch.com/

http://www.wealthengine.com/

http://www.blackbaud.com/targetanalytics

http://home.comcast.net/~lambresearch/OtherPages.htm





PUTTING IT ALL TOGETHER


PRINCIPLES OF RELATIONSHIP MANAGEMENT

• Moves management was implemented as a major giving tool- Personal relationships are the basis of successful major giving

programs• Need a more expansive view• Integrate research, cultivation, solicitation and stewardship into a

cyclical strategy• Need a new name for the process- Relationship management- You can take steps to strengthen a relationship that would not be a

‘move’


RELATIONSHIP MANAGEMENT

• Definition: Strategically developed global and personalized activities designed to cultivate and strengthen relationships based on the belief that each prospect is unique

• Prospects emerge from different sources and paths• Solicitation styles should reflect multiple paths


RELATIONSHIP MANAGEMENT

• What do you need for a successful relationship management process?- Commitment- Database management- Research- Outreach- Oversight


COMMITMENT

• Why do the research, if you are not going to implement the results?• Is your organization ready to do things differently?• Use the plan as a guide, but…for example- If the research results reveal great planned giving potential, but the

plan ignores or downplays planned giving, you alter the plan- In other words, do what presidential candidates do in debates:

• pivot


DATABASE MANAGEMENT

• Commit to good database practices- Integrity- Updates- Appends/screening/analysis- Call reports- Tracking cultivation and solicitation progress


OUTREACH

• Cultivation and Solicitation- Development officers hired with specific contact goals- Professional training

• Include mentorship• Enlist donors to help with training– Focus groups

- Creating the right priorities for development officers• Try to avoid job responsibilities that conflict with contact goals – Trust me, this is a HUGE issue


OVERSIGHT

• Management- Do not install a relationship management process if there will be no

oversight or accountability (waste of time)- There MUST be observed movement (accountability)- Portfolios must be fluid

• Leadership- Successful development practices may be implemented from the

bottom if- They are not practiced at the top


EVALUATION

• Easier to receive screening/analytical funds if successes are documented

• At specific intervals review the achieved/non-achieved goals- Don’t wait longer than six months for the first analysis- After that…

• Annual giving evaluations should be ongoing• Prospect movement through relationship management system to be

reviewed at least quarterly


SUMMARY AND QUESTIONS• Contact:[email protected] 843-991-9921

• White Papers: http://www.blackbaud.com/company/resources/whitepapers/whitepapers.aspx

• My thanks to David Lamb, my long-term colleague and friend for his assistance in the preparation of this presentation:

[email protected]

mailto:[email protected]

http://www.blackbaud.com/company/resources/whitepapers/whitepapers.aspx

mailto:[email protected]

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Target Analytics 1 © 2014 Blackbaud PROSPECT RESEARCH: BUILDING A BRIDGE TO FUNDRAISING SUCCESS