During the course of any given year a lot of patients come to our nation’s healthcare providers, but they arrive with very different lifestyles, experiences, and interests. And they engage in a variety of quite different treatments and patient experiences. From a fundraising perspective job #1 is figuring out who out of that large group o
During the course of any given year a lot of patients come to our nation’s healthcare providers, but they arrive with very different lifestyles, experiences, and interests. And they engage in a variety of quite different treatments and patient experiences. From a fundraising perspective job #1 is figuring out who out of that large group of patients could be interested in contributing to your cause … be it research in a given area, general healthcare for a community, or perhaps even raising up the under resourced in one of our inner cities … or something else.
High level there are three pieces of information that that are critical to figuring out who to approach, and with what message. Getting this right is essential to building an effective fundraising program. The three pieces of key information are: (1) each person’s capacity (how much money they have), (2) their connection to your institution (what was their experience with your provider side; and then have they subsequently engaged at all with your fundraising team by maybe clicking on your newsletter or coming to an event), and (3) their potential philanthropic interests (what they care about).
Most healthcare fundraisers have more than enough data to put this information together. But they don’t. They get caught up in HIPAA restrictions. Or they find its very difficult to integrate their disparate data sources. Or they are not allowed to put their patient data in the cloud. But when they do the results can be substantial.
From our work in this area we have seen impressive returns:
· Much higher yield rates on solicitations
· Higher major giving “ask” amounts
· Different “beat coverage”; the “areas” that people intuitively think may be the best to focus on … may actually not be the best. Happens every time
· Much higher acquisition rates on appeals
· Much lower cost vs. “screen everybody first”
· More money raised at less cost.
These results are substantial and something that we believe every healthcare fundraiser should be working towards.
Contact us to learn more.
Many major giving teams manage to the wrong metrics. As a result they do not achieve the results that they could. In particular, there is an over focus across the sector around fiscal year gift officer activity metrics. The problem is these are not necessarily the best measures of how the prospects are progressing, and the fiscal year is
Many major giving teams manage to the wrong metrics. As a result they do not achieve the results that they could. In particular, there is an over focus across the sector around fiscal year gift officer activity metrics. The problem is these are not necessarily the best measures of how the prospects are progressing, and the fiscal year is not a time frame that prospects generally think about..
Our goal is to work with teams so that they transition from a primary focus on "gift officer activities", to a more wholistic approach of using "prospect performance drivers" to highlight best practices. Those best practices then are shared interactively with gift officers and management in working sessions that help them grow and improve performance. The result is almost always more money, raised faster, and at lower cost.
Prospect Performance Drivers typically include:
1. Prospect Assignments: Are all of our highest capacity and most engaged prospects staffed? Are portfolios reasonably sized?
2. Portfolio Penetration: Are our portfolios of assigned prospects being connected with in a reasonable period of time?
3. Movement: Are we moving prospects forward at a reasonable pace?
4. Solicitation Levels: Are our asks at the right level relative to calculated ask amounts based on capacity and attachment / engagement?
5. Yield: Are we closing solicitations at an aggressive level?
Our work includes not only data systems that provide the performance drivers in clear and easy to use dashboards, but full hands-on coaching and discovery sessions to help your team(s) use them and improve performance.
Contact us to learn more.
Relationship Mapping has become an increasingly hot topic. While much of the focus has been on “scraping” social media for “likes” and LinkedIn connections, our experience has shown that that scoring the data that is already being collected in the CRM and other systems can be much more revealing. This works best in higher education where
Relationship Mapping has become an increasingly hot topic. While much of the focus has been on “scraping” social media for “likes” and LinkedIn connections, our experience has shown that that scoring the data that is already being collected in the CRM and other systems can be much more revealing. This works best in higher education where you "know" your alumni over a long period, but we've had success in healthcare as well.
We've found this approach to be a highly useful method to: (1) figure out the best ways to reach top prospects, (2) determine who could be the best [class] agents because of their connections to top prospects, (3) identify the best people to invite to an event with, say, a board member, and so on.
For example, if your team is trying to reach a key prospect wouldn’t it be great to find out that one of your key volunteers has been involved in many of the same activities and hence most likely knows that prospect? For example, maybe both were in the Glee Club in 1985, played ice hockey together, got an MBA from the same school with the same degree year, attended the Chicago Presidents Dinner in 2019, and are currently in the same country club? Or maybe you’re searching for the best people to become class agents for the upcoming class of ’94 reunion … so why not make the selection in part based on who has the highest connection scores to classmates with the highest giving potential??
The fundraising sector spends a ton of energy trying to mine social media data to infer relationships. Yet most have more and better data sitting in their databases … which they routinely ignore. And this is particularly true in higher ed … but also increasingly in healthcare and non-profits. The data is usually there, it just needs to be assembled and hooked together to create an effective mapping.
Contact us to learn more.
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