Quilting Qualification: A Museum Prospecting Story

By Anne Dean, managing director of research and relationship management, development and alumni relations at George Washington University 

In July 2019, George Washington University’s (GW) vice president for development and alumni relations (DAR) heard pleas from major gift officers (MGO) for an increased quantity of prospect leads to be pushed to them proactively. GW was one year post-campaign, and donor fatigue — coupled with MGO turnover — had left the pipeline a bit stagnant. The vice president’s charge to research and relationship management (RRM) was to proactively push 50 qualification suspects to each MGO in FY19 as soon as possible. Her single criterion was that the suspects have major gift capacity ($50,000+ at GW); beyond that, RRM was empowered to determine which suspects were selected for qualification.

Sketching Success

Early in the project, it was important to define what successes might look like. How would we know if the project was going well or not? How would we know whether to repeat this qualification initiative in future years, or not? The vice president was seeking pipeline movement as measured by two groups of indicators:

This project excluded the Family Philanthropy, Grateful Patient, and Corporate and Foundation Relations teams due to the uniqueness of these programs, existing churn in prospecting, and this project’s purposeful focus on individuals rather than organizations.

Canvas Criteria

For us to achieve success, we needed to create some criteria for selecting which suspects would be chosen. We called on a focus group of MGOs who we felt could help ask and answer the right questions. Among this group, we made sure to include MGOs from our less traditional, non-degree-granting areas of athletics, libraries and museums to join us. As a follow up, museum fundraisers had a separate discussion with their own request: “Don’t pull our segments last,” and “Don’t give us the dregs!” The Textile Museum had 90 years of history with constituents prior to reopening as The George Washington University Museum and The Textile Museum in 2015. Prioritizing the museum ensured they would receive quality suspects and not just those suspects who had nowhere else to go. In the end, this conversation was pivotal to the largest project successes, as it led to some of our biggest wins.

General criteria for all MGOs included:

After crafting the criteria and receiving the results of a complex data request from our partners in technical services that kept the scope tight, we used Excel to segment suspects and identify the best MGO to qualify each suspect. For the MGOs, their designated suspects for qualification were nearly all based on the following segmentation logic.

To create these segments, I started with our museums, utilizing one additional unique criteria for the museum suspects that no other school/unit could employ: museum members. Each suspect provided to the museums for qualification was also a current museum member. Membership indicates affinity in a way that we were not able to measure for other schools/units, and it was an easy way to segment the museum list first. The resulting file from technical services contained 54,000 individuals. Honing in on current members only, this brought the population to start segmenting for the museum to a very manageable 325.

Generally, I did not need to go beyond career/industry when aligning suspects with MGOs:

Read more Connections articles to learn how other organizations are overcoming challenges. Jacob Astley explains one of his victories in “Discovering New Prospects Using a Social-Media Driven Approach.”

Composing Collateral

Our Leadership Annual Giving team partnered with RRM to support this effort by tweaking existing documentation their office uses to qualify larger volumes of alumni for all MGOs to use as desired. This 13-page toolkit covered a variety of topics that we thought could come up at any time during the year:

Why Museums Are Unique

  •  Museum fundraising focuses on a different constituency than in higher education. Museum constituents include members, donors, exhibit ticket purchasers and newsletter recipients.
  • Museum constituents are passionate about the work of one museum and may have zero interest in another museum, particularly if the two museums focus on different topics or approach their foci differently (for example, research vs. advocacy).
  • Within the United States, some tight-knit regions have a few museums where local philanthropists support all of the museums — with some museums receiving nominal support/membership and other museums receiving major and principal gifts depending on the philanthropist’s passions and interests.
  • As museum constituents age, there is an increasing focus and reliance on planned giving, particularly bequests.
  • Museums affiliated with higher education institutions function more independently with regard to fundraising than other school/unit-based offices at the same higher education institution because of the unique programs and constituencies.
  • The Chronicle of Philanthropy’s 2018 America’s 100 Favorite Charities, an annual ranking of charities based on cash support received by cause-driven nonprofits, lists museums and libraries at No. 1, with the Metropolitan Museum of Art in New York City at 75.
  • The 2018 U.S. Trust® Study of High Net Worth Philanthropy shows arts and culture as receiving 2% of total giving, with 24% of households donating to arts and culture. 

Lessons Learned

Having a clear batch of data from technical services was key. A few future enhancements might include automatic removal of:

  • Spouse A, if spouse B is managed by an MGO, even if they are not on the same prospect record
  • Current DAR staff

Throughout the project, MGOs provided feedback on what was working and what was not. A few themes emerged:

  • One or two allocations/funds were found to be solely faculty driven, to the extent where if an MGO contacted the donor, the donor would be confused as to why GW was contacting them. In the future, we would exclude donors from this project who only give to those allocations/funds.
  • Some MGOs found the yield to be too low for them to rely on the 50 newly identified prospects, plus their portfolios (totaling ~120 prospects), to hit high visit goals, desiring far more suspects. During the project, the focus was on delivering these 50 suspects, but this project allowed us to determine yield at macro and micro levels (see below).
  • Because suspect segments for a given MGO were most regularly based on the largest donation area in the last five years, some found that the suspect was now a better fit elsewhere based on more recent giving, rather than largest gift. In the future, we would want to take into consideration both largest gift and recent gift areas in segmenting.

Unveiling Outcomes

Throughout the project, we reported progress at four-month intervals in two ways: micro-level and macro-level. To see the output we used to analyze the project, click here.

Celebrating Successes

  • Micro-level: We employed shout-outs to successful MGOs via email (including their managers) and on DAR’s intranet.
  • Macro-level: We conducted an analysis of the project as a whole, mirroring the success criteria outlined at the top of the article:
    • Contact saturation
    • Donations and opened proposals
    • Percentage of suspects actively managed, new or updated strategies, gift officer ratings, stage updates and interest codes
    • Biographical updates: record type, address updates, children, employment, other relationships, non-GW degree information, marital status, deceased

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Gifts received from the segmented suspects to date are $2 million, with more than $1 million supporting the museum. The three largest donations resulting from this project were all planned gifts (which was not surprising given the focus on recent and frequent donors); these three donations alone totaled $1.4 million.

Comparison With Control Group

When comparing the 1,676 suspects segmented for MGOs and another 1,156 suspects who looked promising but were not segmented for MGOs, the biggest wins were found to be in the percent of prospects contacted, and the total, largest, and average donations.

Suspect to Gift Yield

Now, almost 18 months later, this project allows GW to rely on a solid set of data around our yield of suspects, contacts and gifts. Knowing this yield for GW’s specific population is critical to RRM being able to adequately onboard new MGOs to their prospect portfolios and the amount of qualification work required at our institution. RRM will be able to measure how this yield ebbs and flows as DAR hits the 24-month mark after segments were delivered to MGOs, which will span the typical 18-to 24-month timeframe for a major gift from qualification to donation.

Museum Specific Outcomes

The museum, in particular, experienced some of the biggest success of the project, including the largest donation. A few key pieces specifically aided in the museum’s success:

  • They spoke up early in the project to voice their concerns, and we listened and implemented the project differently based on our conversation.
  • They had an MGO who was able to focus on qualifying the suspects surfaced (a list without an MGO to work it doesn’t do any good).
  • The yields above point to a more successful yield for the museum from suspects to major gifts, which would indicate a more engaged and philanthropic constituency when compared with the fuller population; however, we would want more data before a full conclusion.

As a team of two MGOs within a higher education institution, one museum MGO was able to focus on qualifying the suspects delivered. The MGO noted that having the list to work through helped focus her time. Her experience with these prospects included the following:

  • Hearing from suspects that, while they are members at museums around the Washington, D.C. area, GW is the only one to have called them
  • Securing visits and year-end donations from suspects, as well as membership renewals and upgrades
  • Documenting a seven-figure bequest intention, which allows the museum and GW to properly steward and engage a new donor

Exhibit Closing

Overall, this project prioritized our MGOs partners’ need for new leads while also allowing RRM to show and celebrate our direct impact on DAR’s bottom line — a 1900% increase in giving as compared with the control group. As GW continues toward its bicentennial, we completed a comprehensive wealth screening on approximately 415,000 constituents. In verifying a triaged group of results in summer 2019, MGOs received a new batch of suspects who were directly assigned into portfolios; as a result, GW is not renewing this same project in FY20 but continues to monitor results from the FY19 efforts.

Fast Facts

  • CRM: Ellucian Advance
  • Vehicle: Excel
  • Living alumni base: approximately 290,000
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