Why Advanced Analytics Are Critical for Healthcare Fundraising Improvement | npENGAGE

Why Advanced Analytics Are  Critical for Healthcare Fundraising Improvement 

By on Sep 29, 2017


Example of a doctor using advanced healthcare analytics for fundraising

Healthcare organizations are part of an increasingly competitive landscape for donor dollars in the philanthropic market. Understanding how organizations can leverage analytics and data is critical to fundraising success. 

In this blog post, we will cover the ways that advanced healthcare analytics can be used to:

  • Understand constituents
  • Ask for the right donation
  • Determine one’s interest to give
  • Develop an analytics-driven strategy

This information will help your healthcare organization develop more efficient and effective fundraising strategies, which is critical in today’s competitive market.  

Get to know the Constituents

Healthcare organizations spend a lot of time collecting information from their constituents. They solicit information such as names, addresses, phone numbers, email addresses, and marry those with gift information and event attendance to detail what they know about a donor or prospect. Occasionally, organizations also collect advanced data, such as interests and communication preferences. While this data can be very helpful, this data alone often doesn’t paint a complete picture of the constituent. 

Without the complete picture, organizations may ask for the wrong gift amount, engage constituents with the wrong message, or communicate in a way that is not the most ideal for each person. Without the complete picture, organizations may also struggle converting a first-time donor into a life-time donor.  

The data that constituents provide through interaction with a foundation isn’t the only data that is available. Data providers have access to even more publicly available information that augments the initial data captured by organizations. For example, some services can provide information regarding major gifts given to other non-profit organizations outside of your own institution.  Additional services can provide data such as (but not limited to):  Assets (e.g. property), Stock Holdings, business interests and purchasing habits. 

By combining the data provided through constituent interaction with publicly available data and specialized analytics and strategies, healthcare organizations can better understand and engage the community of donors. 

Capacity–Ask for the Right Donation

Numerous organizations struggle to create effective giving programs, whether it’s a major giving program or a sustaining gift program. Grateful Patient programs are the most common healthcare giving programs that can effectively convert the hospital patient into the foundation’s donor. Understanding a constituent’s capacity to give will help organizations maximize their entire community’s giving potential. 

Wealth can be an overall indicator of a constituent’s capacity to give. Data such as Assets (e.g. property), Private Company Ownership, Political Giving, and Public Holdings can be used to estimate a constituent’s wealth.  This type of information can help guide an approach or ask amount. Data can either be returned as a specific append or used as part of the predictive modeling process to further refine the correct ask amount for an individual. 

By understanding a constituent’s wealth, organizations can begin to engage in activities, such as identifying new major gift prospects and adjust appeal gift ask strings. 

Affinity–Understand the Interest to Give

While estimating wealth is important, determining a constituent’s affinity, or propensity to give, is also critical in engaging donors. For example, a constituent can have a high net worth; however, may have little affinity towards your healthcare foundation for a variety of reasons. Or, he/she may have no affinity at all towards philanthropies. Understanding a constituent’s affinity will help in assessing the level of effort in converting a prospect into a major donor or receiving the critical second and third gift from a current or prior donor. 

The following questions can help determine donor affinity: 

  • How does the organization’s priorities align with the donor’s interests? 
  • What is the current relationship with the donor? 
  • What is the donor’s past giving history? 
  • What other philanthropic involvement does the donor have with the foundation or other like-organizations? 

As previously mentioned, data sources allow prospect researchers to view major gift donations to non-profit organizations.  These researchers can easily view whether a constituent has supported like-organizations.  Additionally, specific data sources, such as GuideStar, can be used to view philanthropic relationships, such as board and trustee memberships. 

Create an Analytics-Driven Strategy 

Analytics can arrive in a variety of formats: raw (detailed) data, numerical scores, letter codes, and personas. For example, data received may be a “Likelihood to Give Score” ranging from 1-1000 or as a range of philanthropic personas from “Casual Donor” to “Philanthropist.”  Understanding these values is critical to developing an effective strategy.  

Items to consider when receiving data or models: 

  • What is my plan to leverage this data in my CRM? 
  • How can we display or output the data to reports and dashboards? 
  • What are the staff education needs to utilize the data or models across our giving programs? 

Once the data or models have been integrated with the CRM, organizations then need to decide how to deploy the analytics across the organization.

One strategy includes creating reports to initially sort constituents into groupings, such as: principal gift donors, major gift donors, mid-tier giving donors, and annual gift donors. Once the groups have been identified, further reports can be created to prioritize principal donors through mid-tier gift donors. 

Annual gift donors can be further segmented using query tools.  Analytics that include augmenting traditional RFM (recency, frequency, monetary) segments with likelihood models and creating segments based on philanthropic personas are just one way of identifying the donors worth the staff’s time and efforts. 

It is important to note that good data, even aligned with good analytics, is useless without a forward-motion strategy applying what has been learned to give clear direction as to the next steps for development officers. It is also important to know that many analytic data and model providers offer implementation and strategy services to help healthcare organizations make their fundraising more efficient and effective in today’s competitive market.  

For more information about healthcare data, analytics and strategies, please visit our Healthcare Analytics page. 


As the principal solutions consultant for Blackbaud Healthcare Solutions, Gregory Heath utilizes his extensive experience in managing the team of solution engineers assisting healthcare organizations and institutions in evaluating their fundraising solutions and practices.

Joining Blackbaud in 1997, Gregory Heath has served as a support analyst for Blackbaud’s financial solutions, a custom solutions developer for Blackbaud Professional Services, a solutions engineer for Blackbaud Canada and Blackbaud Enterprise Market Group, and an account executive for Blackbaud Healthcare Solutions.  Additionally, Gregory Heath has held a variety of management and leadership positions at Blackbaud.

Gregory has a Bachelor of Arts in Biology with a minor in Chemistry from the College of Charleston.  Prior to joining Blackbaud, Gregory served as a radiochemist at General Engineering.  Gregory volunteers with the Charleston Chapter of the Surfrider Foundation.

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