Explore funding trends with Candid’s landscapes
Candid’s new interactive data visualization feature shows you who funds what and where, who receives those grants, which populations are served, and trends over time.
To ensure that philanthropic dollars are going where they’re most needed, we need rich, accurate, actionable insights into funding flows. Understanding where the money is going, who’s doing the work, and what patterns are appearing across regions and subject areas helps highlight gaps and opportunities.
But when someone asks, “What does funding for education in New Jersey look like?” most often they’re asking how many grant dollars are going toward education with New Jersey being the geographic area served by the grants, not where the recipients or grantmakers themselves are located.
This is where Candid’s landscapes feature shines. Using Candid’s enriched grants-based data, landscapes provides you with more depth than public data from IRS Forms 990 alone. And funding is coded using Candid’s Philanthropy Classification System, built for the field and reviewed regularly with input from the community.
What is Candid’s landscapes feature? What can I do with it?
Landscapes is a new data visualization tool in Candid Ultimate. It turns Candid’s grants data into clear, interactive visuals of who funds what and where—so you can spot trends, benchmark against your peers, and show your impact in minutes.
Here’s how:
1. Define your landscape. Select from criteria such as subject area, geographic area served, or population served. Each criterion allows you to select multiple options or exclude specific ones to better focus your landscape.
Tip: Have a list of organizations already in mind? You can limit your landscape to those organizations.
2. Create your landscape. The summary tab gives you a clear overview of the total grants and top funders. View the total number and value of grants, plus the numbers of recipients and grantmakers.
3. Explore your landscape. Click through tabs dedicated to grantmakers, recipients, and grants. Interactive charts enable you to drill down into the details, including breakdowns by grant size, organization type, and top grantmakers/recipients, as well as a list of organizations.
4. Interact with the maps. Choose a country, state, or county to see where grantmakers and recipients are located and where funding is concentrated.
For detailed step-by-step instructions, please see “How to create a landscape.”
How we built landscapes
In my mind, even more important than the numbers is the human care and nonprofit expertise that went into landscapes behind-the-scenes. At a time when AI makes it possible for anyone to pull in public data and turn out numbers with little effort, it can be difficult to know what insights are trustworthy and, more importantly, whether this data is really answering the questions you think it’s answering. And because funding flows are used to help make funding decisions, getting it right matters.
As my team and I were building landscapes, we were acutely aware of the importance of both the accuracy of aggregated data and how users, both those familiar with the nonprofit sector and those who are not, could interpret it.
Our team included software developers and experienced researchers from Candid’s research team. As we iterated, we discussed each chart, each aggregated number, each filter, even the labels and text used. We applied those conversations across landscapes to make it easier for users to navigate the data. For example, we pre-selected the five most recent years for which we have the most complete data available, given the times it takes the IRS to release Forms 990. Users can also differentiate grantmakers by the funder type based on their grantmaking and organization coding, identify organizations that both give and receive grants, and filter for funders located in the region they fund.
As we continue to improve landscapes, we’re dedicated to providing the critical funding insights needed—because with better data, the whole sector gets stronger.
About the authors
