Geographical Analysis of Nonprofit Data: A How-to Case Study

This post presents an introduction to a full report on Geographical Analysis of Nonprofit Data.

All nonprofits can benefit from knowing where their patrons are coming from. Nonprofits regularly gather address data on their donors and attendees, and geographic analysis is one useful way to visualize and make the most of that information. MapTogether’s Illustrated Guide to Nonprofit Geographic Information Systems (GIS) provides an excellent and accessible guide to geographic analytical tools (also known as GIS, or geographic information systems). As MapTogether explains, geographic analysis places information in a “where context,” and deepens our understanding of where someone (or something) has been, where they are, or where we can expect them to be in the future. 

AMT Lab contributors have explored how geographic analysis can help increase programmatic effectiveness, but there are many other ways nonprofits may leverage their data with geographic analysis. Placing people (donors, funders, grantees, audiences, attendees, visitors) in a “where context” can elucidate and inform marketing, development, and programming strategy. Additionally, the map-based outputs of geographic analysis can be used to easily communicate gaps in current organizational processes and strategic opportunities for improvement.

Unsurprisingly, time, cost, and expertise are the primary barriers to the utilization of geographic analysis. We tend to underestimate the amount of time it takes to properly prepare to undertake this type of analysis, particularly when it is new to the organization. In reality, about 90% of the work happens before the software is even involved. As data maintenance is streamlined and the geographic analysis tools become familiar, conducting these analyses becomes quicker and easier.

The full white paper is a preparatory guide for those embarking on geographic analysis for the first time. The case study explores how one organization used this type of analysis to inform decisions about donor recruitment and retention. This guide aggregates useful resources, highlights important considerations, and outlines the process of geographic analysis step-by-step using a succinct case study.


The following case is built around the donor data of a mid-sized, Pittsburgh-based arts organization. The organization was interested in understanding what strategic insights they could glean from placing their donor data in a “where” context. First, they wanted to visualize the geographic distribution of their donors throughout the city of Pittsburgh. Then, they were interested in targeting current low, mid, and high-level donors to cultivate donors for larger gifts moving forward. In addition to donor cultivation, the organization wanted to identify geographical trends in donor retention, and gain insight into the location of current donors, LYBUNTS (those that gave last year but unfortunately not this year), and SYBUNTS (those who gave some year but not this year). Finally, they wanted to know what (if any) population characteristics correspond with areas of high donor concentration, which could inform future donor cultivation strategies.


This case study travels step by step to answer their research questions. (Check out some GIS-specific tips for framing research questions in this article). The case organization wanted to know how geographic analysis can inform future retention and recruitment strategies. Together we defined the following questions:

(1)    Where do the case organization’s donors live?

Understanding the geographic distribution of donors and the characteristics of highly concentrated areas could help the organization identify recruitment and retention opportunities.

(2)    Where do the organization’s low, mid and high-level donors live?

Donors live in geographic pockets and mapping low, mid, and high-level donors can identify high-ROI targets for cultivation and recruitment efforts. External trends such as neighborhood gentrification could influence the geographic patterns of their donor base, or perhaps the organization’s presence in a specific area has decreased, resulting in higher attrition. This question could reveal promising targets for recruitment or outreach strategies.

(3)    Where do the organization’s LYBUNTs (those that gave last year but unfortunately not this year), SYBUNTs (those that gave some year but unfortunately not this year), and current donors live?

Segmentation based on donation recency (current donors, SYBUNTS, and LYBUNTS) could help the organization identify areas where donors once were but are no longer.

(4)    What are the demographic characteristics of areas with high donor concentration?

By cross-analyzing geographic attributes such population, median age, or per capita income with traditional donor metrics such giving level and frequency, the case organization could deepen their understanding of the lifestyle and defining features of their donors.

Interested in seeing how to answer these types of questions with GIS? Check out the full how-to report here.