How nonprofits can boost efficiency with AI-driven insights.
Here's how they got there in four steps.
Riley Children’s Health is Indiana’s largest and most skilled pediatric system, with over 50 locations across the state. It also has the only pediatric research hospital in Indiana, ranked among the top in the nation according to U.S. News and World Report.
Riley Children’s Foundation raises funds and stewards foundation assets so all children can get the best care possible at Riley Children’s Health through pediatric research, education, and other programs. It fundraises through businesses, as well as through thousands of one-time, periodic, and sustaining individual donations.
To support the foundation’s mission, its data analytics team created resources to help gift officers spend their time as efficiently as possible. But optimizing a donor prospect database of 700,000 was difficult with a limited staff and limited predictive modeling expertise — until they transformed results with a data-driven technology approach.
Here’s how they got there in four steps.
Step 1: Supercharge donor database analytics in one place.
Riley Children's Foundation started with Nonprofit Cloud to consistently track its donors and time to donation, known as the “cultivation lifecycle.” Connecting the dots with its donors was crucial since it can take several years or more to build a relationship prior to giving.
To further their data-driven technology approach, the team added CRM Analytics with Einstein Discovery to Nonprofit Cloud. The new advanced analytics solution consolidated Salesforce data sources with external data sources, and empowered gift officers with AI-powered, actionable insights about their donors directly in their workflow with no coding required.
Step 2: Predict donor outcomes using dashboards.
These dashboards are embedded directly in Salesforce and enable gift officers to drill down to see contextual information on an account, such as if donors supported clinical care or family support programs at Riley Children's Health, or donated community-based gifts or legacy gifts. The key is in understanding the data by interests, location, donation timing, and other factors.
To identify patterns and themes, the team turned to AI-driven insights fueled by machine learning capabilities in Einstein Discovery. “The data points that I look at make up the model and then the model tells us what to do with it,” said Samantha Lame-Farley, Manager, Fundraising Data Analytics. For instance, this modeling can predict the probability that a household turns into a major gift donor.
“Gift officers can easily interpret what they're seeing, so any time they look at an account they'll see a field and see if a person has a high likelihood to become one of our high-level donors, indicating they are passionate about our organization. Or maybe this person doesn't, and then we can think about what we can do to change that,” Lame-Farley said.
Step 3: Improve donor relationships and giving impact.
Armed with strategic insights about the donation pipeline, gift officers prioritized donor efforts and cultivated or reignited donor relationships, to ultimately spend their time most efficiently.
For example, the analytics team also served up insights that supported fundraising communication for direct mail and other donor outreach programs, and are hoping to provide insight for digital pieces in the future. Lame-Farley said, “It’s about communicating a message that resonates with donors on the right channel at the right time so that we’re making it easy for them to think of us as a top philanthropy priority.”
Step 4: Develop metrics and plan.
A strong data-driven approach made a difference. One of the big successes after adopting this technology was the amount of time gift officers spent finding the right data to do their job. In fact, powered by AI-driven insights, the team is on track to reduce the large donation cultivation lifecycle by 50% in the next two years and is working toward increasing the number of donors giving $10,000 or more to the foundation.
Lame-Farley pointed out that a clear understanding of the end goal you're trying to accomplish is critical, along with having champions on your leadership team that encourage dedicating time to dashboard analytics. “People have been incredibly positive about the work we're doing. Many leaders have been very supportive and plan to incorporate these insights into their one-on-one discussions,” she said.
Though much has been done to support the data culture at Riley Children’s Foundation, the team has big plans. Lame-Farley said, “We’re looking to develop a roadmap with leadership to identify priorities in the business and strategic plans so that our team can be most helpful in meeting those objectives utilizing our resources and talents.”
Most importantly, all their data analytics work ultimately ties back to Riley's mission: to ensure all children have access to world-class pediatric healthcare.
