May 2011

Transform Philanthropy

Periodic Essays on Emerging Philanthropic Trends and Practices

Affinity Models: Alumni Relations by the Numbers By Jennifer A. McDonough, Partner

As a critical component of university advancement efforts, alumni relations programs have continued to evolve in both their complexity and impact. The following ten attributes may be offered as a representation of some of the best practices for alumni programs nationally. 1. Increasing degrees of purposeful collaboration with development and communications as contributory to a fully integrated advancement model of constituent engagement. 2. Movement from the more exclusive “social” model to one of more diversified involvement. 3. Promotion of alumni as a means of positioning the institution to its current and prospective stakeholders. 4. Emergence of volunteer opportunities tied to partnerships with such institutional programs as admissions, student affairs, career services, and government relations. 5. Inclusion of more finite yet meaningful volunteer opportunities. 6. Evolution of alumni segmentation and involvement strategies that go beyond degree programs to affinity and extracurricular connections and relationships. 7. Incorporation of an increased emphasis on communications as involvement and connection. 8. Building community through e-engagement and social networking.

9. Evolution of the definition of alumni to include non-degreed alumni and adopted alumni as examples. 10. Quantification of program goals and outcomes and increased reliance on data to inform strategies and to demonstrate degrees of impact. It is this last attribute that will frame the content to follow. Development efforts have always been understandably quantifiable with a focus on dollars raised, donors acquired and retained, and the like. But even development programs have evolved to place an even higher value on metrics and more explicit measures of productivity in response to increasing expectations for results and stronger degrees of accountability. It follows then that alumni relations efforts would take a comparable path in their evolution towards greater quantification of their strategies and results. The benefits are significant and include the following: 1. Serves to unify alumni relations and development programs based on their shared reliance and value on specificity. 2. Provides a basis by which plans may be not only developed but evaluated based on discernible measures, targets, and characteristics. 3. Supports the evaluation of impact over both annual/fiscal years as well as multi-year time periods allowing for the demonstration of positive or negative trends. 4. Provides important return on investment information often required to support requests for sustained or additional financial (continued on page 2)

(continued from page 1) investment made that much more critical in these times of stretched institutional resources. 5. Elevates both the real and perceived appreciation for the critical nature of such programs. Increasingly, affinity models are being developed and used as a primary means by which alumni relations programs may be quantified and degrees of relationships scored. These models provide for the organization and documentation of myriad criteria all aligned with alumni characteristics and patterns of involvement. The following are the five key steps often involved in developing and implementing affinity models.

Affinity Models: Step One Decide What You Will Track The following are often the four major categories of data tracked and used in the explicit discernment of alumni engagement: 1. Demographic. Constituency type, degrees, student activities, and contact data. 2. Giving. Allocations, lifetime giving, largest single gift, giving levels, frequency, planned giving, and capacity ratings.

3. Interests. Affiliations, event attendance, signature event attendance, online participation, leadership positions, and volunteer involvement. 4. Relationship Management. Assignments, number of prior contacts, and recency of contacts. Elements tracked within each of these major data categories may include those listed in Figure One on the following page and would be based on and tailored to the unique characteristics of your own institution.

Affinity Models: Step Two Assess Your Data in Relationship to Affinity Model Categories and Values As is the case with development, the overwhelming majority of data for your alumni relations program should be housed and made available through whatever software platform your institutional advancement program employs. In some cases, special modules such as those supporting event tracking, for example, may be necessary. The simple template below (Figure Two) can be used in the data assessment process. (continued on page 4)

Figure Two: Sample Data Assessment Template Values

Current Data Available (Y/N)

Data Quality

Future Data (Y/N)

Next Steps

Demographic

Giving

Interests

Relationship Management

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Figure One: Sample Affinity Model DEMOGRAPHIC

A lum nus/P arent G raduated/D egree H olding A lum nus S urviving N on -A lum ni S pouse/P artner A lum nus/F aculty/S taff

 N on-D egreed A lum nus  A dopted A lum nus  Legacy A lum nus

Constituency Type

   

Degrees

 M ultiple D egrees  U ndergraduate D egree O nly  P rofessional D eg ree O nly

Student Activities

    

Contact Data

 A ccurate A ddress on F ile  A ccurate P hone N um ber on F ile  A ccurate E m ail A ddress on F ile

 A ccurate A ddress, P hone N um ber, and E m ail A ddress on File  A ccurate B usiness/P rofessional Inform ation on F ile

Contribution Allocations

 D egree G ranting U nit/s  U niversity-W ide F unds

 A thletics  S pecial or C om prehensive C am paigns

Lifetime Giving, Largest Single Gift, and Giving Within the Last or Current Fiscal Year

   

Frequency

 G ave in all of the past five years  G ave in tw o to four of the last five years

 G ave in one of the last five years

Planned Giving

 Irrevocable and D ocum ented C om m itm ent  R evocable and D ocum ented C om m itm ent

 U ndocum ented/V erbal C om m itm ent

Capacity Ratings

 P resence of any M ajor G iving R ating  P resence of any P lanned G iving R ating

 P resence of any Leadership A nnual G iving R ating

Affiliations

   

Event Attendance

 H ave participated in five or m ore events  H ave participated in three to four events

 H ave participated in one to tw o events

Signature Event Attendance

 R eunions  H om ecom ing  F am ily W eekends

 C onvocations  C om m encem ent

Online (cumulative)

 O nline C om m unity M em ber (Institutional)  O nline C om m unity M em ber (E xternal)

 H as P osted C lass N ote/s  H as R esponded to E lectronic S urvey/s

Leadership

 A lum ni A ssociation B oard M em ber  A lum ni A ssociation B oard O fficer/Leader  A dvisory C ouncil/C om m ittee M em ber

 A dvisory C ouncil/C om m ittee O fficer/Leader  C lub/C hapter M em ber  C lub/C hapter O fficer/Leaders

Assignments

 Individual is a P rospect and is N ot A ssigned

 Individual is a P rospect and is A ssigned

Number of Prior Contacts

 P rospect has had tw enty-five or m ore contacts  P rospect has h ad betw een ten and tw enty-four contacts  P rospect has had betw een five and nine contacts

 P rospect has had betw een tw o and four contacts  P rospect has had a single contact

Recency of Contacts (Actions)

 Last contact w as in the last six m onths  Last contact w as in the last seven to tw elve m onths  Last contact w as in the last thirteen to eighteen m onths

 Last contact w as in the last nineteen to tw enty-four m onths  Last contact w as m ore than tw entyfour m onths ago

(It is recommended that a partnership be developed with your student affairs colleagues to determine the set of the most prevalent or meaningful cohort of student involvement opportunities.)

GIVING INTERESTS

(Establish the timeframe and inventory of chosen events; or, list a specific inventory of standing events and assign a value to each event included in your inventory.) (Establish the timeframe and set of standing events included.)

RELATIONSHIP MANAGEMENT

(Actions, timeframe and what is meant by contacts.You may wish to distinguish between face-to-face interactions and all others.)

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S tudent C ouncil or G overnm ent A dm issions V olunteer R esidence H all A ssistant S tudent A thlete S tudy A broad

$1 m illion or m ore $500,000–$999,999 $250,000–$499,999 $100,000–$249,000

D ues-P aying M em ber C lub or C hapter A ctivity P articipant C areer N etw orks A ffinity P rogram P articipant

 G raduate D egree O nly  C ontinuing E ducation  C ertificates     

   

   

S cholarship R ecipient D onor H onors C ollege or P rogram A dvancem ent V olunteer or E m ployee F raternities and S ororities

$50,000–$99,999 $25,000–$49,999 $10,000–$24,999 $1,000–$9,999

C lass A gents A ffinity G roup M em ber S eason T icket H older A lum ni S peaker

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(continued from page 2) It is recommended that a cross-functional team of professionals within your advancement program be convened to make decisions about which data should be included in the affinity model. This team should incorporate staff members from advancement services or its equivalent, development, and of course, alumni relations. Outside analytics professionals may also be helpful. The data identification and assessment process itself represents an important opportunity to position data as a driver for strategy and action. Data improvements and augmentation identified by the team should be detailed in a prioritized work plan. Further, it is recognized that some of the desired data such as student activity information will reside outside of advancement. It is likely that significant time and attention will be required to ready that data for entry into your core system and inclusion in the affinity model. Therefore, the following four steps should be undertaken by the team: 1. Locations and sources for all data should be identified and documented. 2. Appropriate personnel should be targeted for discussions surrounding the importance of securing the data and affirming a process to first, secure the initial body of information, second, to make any necessary improvments, and third, provide for ongoing data transfers as part of a systematic data maintenance and improvement process. It is likely that even subsets of data already housed in the advancement system will require attention and improvement, especially if the data is incomplete or not current. Attributes and interest codes in particular often need more deliberate cleanup with consideration given to inactivating unused or unimportant values, developing

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sub-categories to provide for additional coherency across an often lengthy set of values, and targeting key attributes for more active research and sustained maintenance. 3. Data should be evaluated for currency and accuracy, and appropriate steps taken before transfer into the affinity model. Decisions not to include certain data initially identified by the team as valuable should be based on the degree of difficulty in locating the information, the availability of data found only or mostly in hard copy, and/or data that is significantly compromised by age and/or inattention. All decisions should be documented. 4. Timelines for data ownership, transfer, and maintenance should be established and documented and made part of an annual data plan supported by appropriate staff and budgetary resource allocations.

Affinity Models: Step Three Identify the Numeric Values for Each Data Set Ultimately, the affinity model will be used to score your constituency based on characteristics and involvement and so, each of the identified data sets must have a correlated and numeric value applied in a consistent manner once identified. There are several options available to such models, and models often incorporate several of the following for the various data: 1. Scores within a category may reflect a ranking with higher or more important characteristics assigned a higher number. For example, you may decide on use of a scale of between one and ten. In the case of constituency type, you might assign a numeric value of ten to a constituent who is both a degreed alumnus and a parent or faculty/staff member based on that individual having two significant points of connection with your institution. In that model, you may decide to assign an adopted or nondegreed alumnus a lower value. (continued on page 5) Bentz Whaley Flessner

(continued from page 4) 2. Scores may also be based on the number of qualifying behaviors or characteristics attributed to the constituent within a certain category. For example, within the student activity category, you may decide to assign a higher score based on a higher number of activities. If an alumnus is associated with five or more activities, they could be assigned a ten (again on a scale of one to ten) with those numbering less than five assigned a lower score. 3. Simpler and less complicated models may assign each value a single point. In these cases, the total score is basically the sheer number of qualifying attributes associated with each constituent or group of constituents.

Affinity Models: Step Four Define the Range of Scores After the model is affirmed, a quantification of the total cumulative values possible should be completed. Based on that “perfect” score, the values should be divided into categories associated with ranges of engagement rankings. For example, these ranges could correspond with four quadrants including no engagement, modest or low engagement, moderate engagement, and significant engagement. Each quadrant would be defined through a numeric range of scores based on the total correlated with the lowest and highest degrees of engagement. At such time as the affinity modeling team affirms the data is in sufficient form (recognizing that this will represent an iterative process with strategic improvements in the data scheduled as part of the overall data plan), the model should be run with scores documented for the overall alumni file and then by select segments. Scores would then be correlated with the engagement categories outlined above and a numeric breakdown produced for the number of total constituents and related percentage of the total constituent file

for each quadrant. At a minimum, your alumni program should incorporate explicit goals for increasing the number and percentage of alumni qualifying for inclusion in each of the engagement quadrants suggested. For example, if 75 percent of your alumni body has no engagement, you might consider reducing that percentage by five to ten percent based on new strategies for outreach and involvement each fiscal year. Subsequent to the initial run, the model can be processed on a monthly or quarterly basis. At each interval, new scores should be tracked, compared, and contrasted with prior values to ascertain degrees of progress within and across ranking segments.

Affinity Models: Step Five Strategically Apply the Model The use of such models is indeed limitless, but there are several key applications which should be considered and actively used in program planning, evaluation, and goal setting. Applications by Segment In addition to applying the model to your overall alumni body, consideration should be given to using the model for specific segments to ascertain these scores and to ascertain how they may differ from the baseline for the total alumni file, if at all. These segments may include the following: „„ Alumni by unit/degree. „„ Alumni by region/geography. „„ Alumni by age especially important as younger populations become drivers for giving participation strategies in particular. Applications by Category The four major categories of demographics, giving, interests, and relationship management mentioned earlier also lend themselves to scoring as subgroups of the larger model and also to (continued on page 6)

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(continued from page 5) cross-tabulation. For example, if your model differentiates among various types of events and event participation, you could look at the degree of correlation between these events and the range of scores associated with higher levels of engagement. It is recommended that an optimal or “perfect” score be determined for each of the four primary categories for data used in addition to the overall score. Evaluations should be completed to determine those values that seem to correlate the most with positive or negative shifts in engagement scores to support program planning and strategy development as well as decisions on resource allocations. Applications for Alumni Relations Dashboards Defined as the core categories of measurement to represent productivity, an alumni dashboard can be developed, which essentially pulls select data elements from the affinity model and tracks progress against pre-determined and quantifiable targets. Dashboard elements can include the following: „„ ALUMNI ASSOCIATION CHAPTERS, CLUBS, NETWORKS, AND COUNCILS –

Number of current members/participants.

–

Percent participation of alumni of record in region.

–

Number of new members.

–

Number of members lapsing.

–

Number of members renewing.

–

Loyalty members.

–

Number of current members who are also donors.

–

Number of current members who are also rated prospects.

„„ EVENTS (Events could be organized into the following categories: athletics, educational/professional development, cultural, social, and general interest.)

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–

Number of events.

–

Number responding to pre- and post-communications.

–

Number attending and percentage of total population/target audience (for specific segments including members, donors, volunteer leaders, prospects, etc.).

–

Number of new attendees.

–

Number attending multiple events within a current year or attending the same events in sequential years.

–

Number of volunteer and committee leaders.

–

Number of leaders and attendees who are also donors and prospects.

„„ COMMUNICATIONS –

Number submitting class notes.

–

Number responding to surveys/market research requests (and as a percentage of the total target audience).

–

Open and click-through rates.

–

Number of visits to website and to desired content targets within the website.

–

Number requesting removal from various communications vehicles (overall and by vehicle type).

„„ OTHER ENGAGEMENT –

Number of members of online community.

–

Number participating in “non-event” programs (career networking, mentorship of students, speaking on campus, admissions, advocacy, etc.).

–

Number serving in alumni volunteer leadership positions.

–

Number of alumni involved with students. (continued on page 7) Bentz Whaley Flessner

(continued from page 6) Number of students involved with alumni and with alumni programs.

„„ GIVING –

Number of alumni donors to the annual fund.

–

Percentage of alumni participating in the annual fund.

–

Number of referrals of alumni prospects to the major and planned gifts team.

–

Giving (dollars and donors) pre- and post-reunion involvement.

„„ CONTACT INFORMATION –

Number and percentages of correct addresses, email addresses, phone numbers, and business information.

Applications for Development and the Partnership with Alumni Relations Scores can just as easily be derived for a specific individual in the case of a major gift prospect for example, or for a group of constituents such as those alumni included in a gift officer’s portfolio. Alumni with higher engagement scores can be segmented for leadership annual and/or major giving solicitations, more substantive volunteer engagement opportunities, and increased attention by gift officers, volunteer leaders, and institutional leaders. It may be advisable to develop one overall score and also separate and composite scores for development and alumni relations as representative of the two major categories of alumni engagement. The alumni score would be developed from the demographic and interest categories and the development score from the giving and relationship management categories. Applications can be created which provide for various combinations of high and low scores and then used to influence segmentation and overall fundraising strategies (reference Figure Three).

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Additionally, detailed lists of individuals can be produced based on their overall score, by a specific value or values within the model, or some combination. Consideration should be given to adapting your prospect management system to provide for the inclusion of engagement scores produced through the affinity model for individually managed prospects and donors. Figure Three: Affinity Model Prospect Segmentation

Low to High Giving/Capacity

–

3 Purposeful Major Gift Cultivation

4 Major Gift Solicitation

1 Non-Priority

2 Leadership Annual Giving

Low to High Engagement The process of committing to a data-driven alumni relations effort and designing and implementing your affinity models and dashboards will yield many important outcomes and benefits, not the least of which will be the further integration of both colleagues and programs across alumni relations, development, advancement services, and institutional partner lines. Additionally, your data will be expanded, enhanced, and improved and put to strategic use in program documentation, evaluation, planning, and execution. Program and resource decisions will be better informed and more defensible and will yield both greater numbers of involved constituents as well as enhanced levels of involvement. n

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Jennifer A. McDonough is a partner at Bentz Whaley Flessner. Joshua M. Birkholz Christopher M. Cannon Margaret Sughrue Carlson James P. Daniel M. Bruce Dreon Bruce W. Flessner Thomas W. Grabau Kathy G. Hansen Cassie R. Hunt Judith M. Jobbitt Jeffrey D. Lockhart William R. Lowery Mark J. Marshall John S. McConnell Jennifer A. McDonough Ali R. McLane Alexander W. Oftelie Mayra Quirindongo Rachel A. Schaefer William D. Tippie Justin J. Ware

7251 Ohms Lane Minneapolis, MN 55439 (952) 921-0111 2461 South Clark Street, Suite 910 Arlington, VA 22202 (703) 413-5505 www.bwf.com

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