The University of Michigan's Philadelphia Story

It all began with our very own Philadelphia Story. Sort of.

Our story captured not just the qualification work of a highly motivated gift officer, but a collective team effort.

In October 2015, the University of Michigan’s associate director of prospect research delivered to her intrepid business school gift officer a list of 47 names of potential Philadelphia-based prospects. Eight months later, we were able to tell exactly what happened with those prospects within minutes. Happily, the gift officer had visited and rated one-third of the prospects.

Had this list been delivered a year earlier, we would have been playing the classic prospect research parlor game of “whatever happened to that list?” And if we really wanted to know, it would have taken us hours of digging through individual records on our database — hours we don’t typically have stored in the bank. But because we are driven to understand our own return on investment, we developed a system within our database to monitor the names we deliver so we can determine how they are being used.

Efficient Tracking

The tool we use to track prospects is actually simple: a tag. Through a carefully thought-out system of tagging, we are able to keep track of all identified prospects and deliver to our gift officers.

We conducted many meetings about what to include in each tag. We didn’t want the system to be more clunky than necessary, but we wanted it to be thorough enough to work in our decentralized development system. Conversations boiled down to what we wanted to get out of the tags: to be able to re-pull lists we had previously sent to gift officers; to allow for greater transparency among our own team about which prospects had been sent out; and to be able to “prospect” within our past projects and recycle or repurpose names as appropriate.

We use affiliation tags within our customized Blackbaud CRM database. Whenever we find promising prospects, we assign them a “referral,” “identified” or “pre-identified” tag, depending on the strength of our recommendation. “Identified” tags have solid indicators but are less known to us. “Pre-Identified” tags look good on a first pass, but would need more vetting before we could recommend them to a gift officer. We put the most work into our “referral” prospects and consider these to be the closest we can offer to a personal referral. We update these prospects’ records as much as possible to provide our best possible introduction for the gift officers.

Of course, not every prospect seems so promising. We also have the option of tagging constituents as “research exclusion” if our research suggests they do not have the capacity or inclination to make a gift. This allows us to quickly exclude them if they appear on future lists — this way, we don’t waste time recycling dead-end names.

When we tag prospects, we always include the username of the research analyst who identified them, the area within the university for which the prospects were identified, the name of the project we did and the type of project it was (e.g., a general prospect identification project or a board match). We are exploring the idea of adding additional information such as geographic region and gift officer name to the tags, but that is still in the experimental stages.

Visualizing Efforts

We are fortunate in our department to have recently added Tableau to our arsenal of tools. Our team created a dashboard that allows us to dynamically view the tags added into the system.

The dashboard allows us to easily visualize trends in the tags. For example, we can see when a unit repeatedly requests the same type of prospecting project. We can also see trends in the prospect’s gift officer visit based on location, age range and professional background. The dashboard gives us a high-level overview of added tags, and it also allows us to break the lists down by different criteria, such as fundraising unit or fiscal year.

So what, exactly, is our ROI? To an extent, we are still determining our impact, and because of the nature of the gift cycle, the prospects we discovered this year may not make gifts for a year or more. With a lot of the infrastructure in place, it’s now easier for us to measure our impact than ever before. We can follow up with gift officers on specific projects in ways we couldn’t before using our reports and our Tableau dashboard.

Importantly, the tagging system has also led to new focus and collaboration within our team. Last fall, we rallied around the idea of creating a team goal to identify $100 million in new prospect capacity from July 2015 to June 2016. Our count was based on capacity ratings that gift officers assigned when they qualified prospects tagged by our team. We used the gift officer rating because it provided a more immediate indicator of whether the prospects we delivered were quality prospects worthy of major gift cultivation.

The $100-million goal allowed us to better collaborate as a prospect development and analytics team by working through our conflicting policies to gift officers (“take these new prospects” and “don’t overfill your portfolio”). The conversations at those goal meetings helped keep all team members on task in a coordinated, thoughtful way.

Word started getting out about our challenge — and gift officers thought it was a great idea. It turns out a group that has become beholden to metrics also liked seeing us beholden to metrics.

We have learned more about gift officer behavior, and that has helped us adapt our delivery techniques to better meet their needs. Because every prospect delivered now gets a tag, we are being more selective with the quantity and quality of the prospects we send out. Tagging prospects based on the strength of our recommendation has added another dimension to our conversations with gift officers. Our tagging system has also helped us recognize and celebrate those gift officers who do discovery work well, such as our business school gift officer traveling to Philadelphia. That gift officer was widely recognized in the development community for his discovery efforts, and his success was built, in large part, on the lists provided by his research analyst.

A less tangible part of our ROI was that our team learned to revel in our own successes. Having a simple way to track our work also meant that we were able to celebrate what we had done. We had coffee and fried bagels when we reached our first goal. We watched “Moneyball” when we hit $50 million in qualified prospects. We celebrated with a trip to the local ice cream parlor to cap off the year.

While we didn’t meet our $100-million goal, the lessons we learned have paid dividends. We learned to identify a singular goal, consistently monitor our progress and bolster our results. We learned that we must work more closely with our gift officers to ensure they qualify and rate the prospects we deliver. Our failure to meet the goal also brought to light another interesting trend — gift officer ratings were consistently lower than the ratings our research team assigned. Had we used the ratings assigned by the research team, we would have met our goal. We have increased efforts to educate gift officers on rating prospects and are paying closer attention to discrepancies between research and gift officer ratings.

We’re already starting to quantify next year’s goal. We learned to better collaborate as a prospect development and analytics team, deliver prospects to gift officers in manageable batches, track our own work within our database, look at the holistic picture of a gift officer’s portfolio and celebrate our own accomplishments — big and small. In short, we became better.

Kim Huebner is a development prospecting analyst at the University of Michigan. She is motivated by delivering quality names to gift officers (and by coffee and ice cream).

Katie Linder is associate director of foundation relations at the University of Michigan and former assistant director of prospect development and analytics. She is a huge fan of “Moneyball.”

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