Webinar Recap: Optimizing Portfolios with Modeling and Screening Results with David Lively and Solas Group
In July, we were fortunate to host a webinar presented by David Lively, author of Managing Major Gift Fundraisers: A Contrarian’s Guide and Senior Associate VP and Campaign Manager at Northwestern University, along with Ron Eisenstein and Erin Lynch Moran, co-founders and partners at The Solas Group, a Tableau Alliance Partner. This presentation was an engaging look at how to leverage innovative analytics tools to support major gift fundraising performance.
If you missed it, you can watch the webinar recording here. Check out some of the Q&A’s from the webinar here:
Q: What can you do to find prospects that are hiding in plain sight?
A: The fact that there are prospects hiding in plain sight is one of the best reasons to make sure you are actively using a predictive model to identify prospects. Sometimes people may not surface to your attention based on either their giving or their lifestyle. However, they may have attributes that are common among individuals at your organization who are ready to make a major gift, and a model will help you discover that. It’s a great idea to take the highest propensity prospects and run them through iWave to see if they have hidden wealth. Some people own multiple properties or companies and may not “look” to be the strong prospects that they are.
Q: How do you avoid having multiple fundraisers contact the same prospects since those prospects are not assigned before being qualified?
A: When you institute a program of limited portfolio sizes, it’s vitally important that fundraisers file contact reports promptly when they are doing outreach to qualify new prospects. We impress upon our team the reason they need to file contact reports quickly, and after that, we establish a policy that fundraisers must check to see if there are existing contact reports filed within, for example, three months. If a fundraiser sees that the person they want to contact has been contacted by another fundraiser in that timeframe, they are responsible for working with the other fundraiser to coordinate a strategy. One thing to keep in mind is that when you have limited portfolio sizes, there are far more unassigned prospects who are available to qualify, so it becomes far less common for fundraisers to struggle to find individuals they can approach.
Q: What are some key indicators that identify affinity?
A: Measuring affinity is very complex. In fact, CASE is currently working with an advisory board to attempt to come up with a common way of measuring affinity. But essentially, affinity is about the passion constituents feel for your organization, either as a whole or one of its component parts. From that standpoint, anything they do to engage with your organization could be seen as an indication of affinity. Our dashboards include an affinity filter for organizations like universities that want to filter their results by, for example, a particular college or program. However, our dashboards are designed to help users analyze a constituent’s giving likelihood, which is more straightforward. We measure giving likelihood by developing a customized predictive model that identifies the commonalities among each of our clients’ major gift donors, and then we use several advanced techniques to make the model more predictive.
Q: How does the focus of prospect management shift once dashboards are in place?
A: Prospect management still plays an active role in helping development officers continue to analyze their portfolios and identify great prospects. But having these tools in place helps them better manage the full fundraising cycle, such as helping fundraisers make sure they have enough solicitations in the pipeline, ensuring that managed prospects are being actively engaged, and managing the flow of prospects in and out of the stewardship stage.
Q: What are the criteria that make a difference between “high propensity” and “low propensity”?
A: Great question! It’s tricky, because sometimes the criteria change depending on the nature of the organization. For example, women may have a higher likelihood to give to women’s health organizations than men do, but they may have the same/similar likelihood to give to their alma mater. Every organization’s donor base is a little different because different types of people are drawn to support the missions of certain kinds of organizations. A good predictive model is designed to identify the most likely prospects for your organization specifically.
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