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By Matthew R. Kraemer, CPA, CIDA

Running a not-for-profit organization is always full of challenges, but the difficulty level went through the roof over the past two years as many organizations’ large in-person charity events were replaced with virtual events and fundraisers. Not-for-profits had to become more creative in driving donations and creating meaningful interactions with their constituents and donor bases.

Overall, the nonprofit sector did this successfully. Total charitable donations increased in 2020 compared with 2019, and they are on track to increase again in 2021 compared with 2020. According to reports, these increases were largely due to increased donations by individuals as opposed to corporate giving. This emphasizes the importance of connecting with individual donors. One way to track progress in connecting with a donor base is through data analytics.

Here are some examples of how nonprofit organizations can incorporate data analytics and data visualization to gauge organizational performance and community engagement.

Scatter Plot: Donor Engagement and Contributions

The above scatter-plot chart shows the dollar amount of donations to the organization on the Y axis and the number of engagements the organization had with each donor on the X axis. (An engagement is considered any point of contact with the donor – personalized email, mass email, physical letter, phone call, or attendance at an event). Each individual donor is represented as a dot on the scatter plot. This visual also includes a third metric using conditional formatting of the individual dots. As you can see by the legend at the top of the graph, the color of the dot correlates to the number of events the donor attended.

I find the easiest way to interpret the results of a scatter plot is to think in terms of quadrants. In this example, donors in the blue quadrant (upper left) are donors that have not had many interactions with the organization but have made significant financial contributions. These would be donors that respond well to the organization’s interactions with them. Donor 1 is a great example: this donor made the largest financial donations to the organization and had less than five total interactions with the organization (only attended one event). By contrast, donors that are in the red quadrant (bottom right) represent donors that have relatively low donation amounts but a high engagement level. These donors are not responding well to the organization’s interactions. Donor 2 is a prime example: this donor attended all three events hosted by the organization and had the most interactions, but has yet to make any significant financial donations. Drilling through to Donor 1 and Donor 2 to identify which events they attended and what interactions they had will add to the understanding of which events and correspondence are the most effective at communicating the organization’s cause and purpose.

Interaction Success Rate with Hierarchies and Drill Down

Another helpful analytic for not-for-profit organizations is the tracking of the success rate of email interactions. Many organizations use email marketing companies to manage their email correspondence with the donor base. Many of these companies can obtain data on sent emails to identify which recipients open the email, how many clicked on links within the email, and how many recipients opt to unsubscribe from future emails. This data can help organizations understand the quality of their interactions with recipients. But this data is only valuable if it can become actionable. By using hierarchies and drill-down features, nonprofits can quickly and easily understand exactly which interactions, based on email subject, successfully reach the organization’s donor base. An added layer of text analytics can identify key words and phrases used in the body of the email that led to a high click-through rate. This is another measure of quality of interactions with an organization’s donor base.

Constituent Conversion Rate

A prime performance indicator is the measure of an organization’s success in converting a constituent who has had an interaction with the organization into a financial contributor or supporter. The numerator of this measure is the total number of individuals making a financial contribution to the organization. The denominator is the total number of individuals interacting with the organization. This can be calculated for a certain period, where both the numerator and denominator are only limited to a certain month, quarter, or year. Another way to determine the quality of interactions with their donor base is by identifying what interactions seem to communicate the organization’s purpose the most clearly. We have seen organizations calculate this measure by specific events, specific interactions, certain campaigns, initiator of the interaction, and more.

Frequency, Recency, and Monetary Value

Regardless of the industry, it is often more expensive acquiring new customers compared with retaining existing customers. This applies to not-for-profits in terms of donors. Performing a donor analysis based on the frequency of donations, the recency of the donations, and the average monetary value of the donations allow a nonprofit organization to identify the most financially valuable donors to their organization. This can also be used to identify what campaigns, events, and interactions led to high frequency, recency, and monetary value of donations.

Fundraising Efficiency

It is vital to know the efficiency of raising each dollar in terms of the actual cost incurred by the organization. The calculation is simple: total fundraising expenses divided by average total contributions to the organization. Like all analytics, the value of this measure is only as good as the data going into it. To drill down to understand which campaigns, events, or interactions were the most efficient, the organization must track the fundraising expense by campaign, event, or interaction. Too often, this type of data is not collected by not-for-profit organizations.

Donation per Interaction

Another way to think about fundraising efficiency is to calculate a donation dollar amount per interaction. This allows you to drill down to individual donors to gain insight into which donors saw the value and importance of your organization with limited interactions and which donors were not reached as profoundly. In the chart in this section, “Raised Amount” represents the total donation amount, and “Number of Interactions” represents each communication with the donor. This analysis reveals that although Ardisj Whenham donated nearly $3,000 total, the effort investment (26 interactions) was much higher than that of Ellmo Kelle, who donated $511 after only one interaction. Kelle is a much more efficient interaction than those interactions with Whenham. When we select an individual and drill through to the underlying detail, we can see what interactions were most successful based on the Raised Amount per Interaction.

There are many ways to measure community engagement and fundraising efficiency. Data analytics and data visualization are great ways to lift insight out of the data that most organizations already collect. The key is identifying the metrics that are meaningful to your organization.

Note: All of the examples noted in this article were executed in Microsoft Power BI.

Matthew R. Kraemer, CPA, CIDA, is a senior manager of ADAPT (Automation & Data Analytics Process Team) Consulting Services at Schneider Downs & Co. Inc. in Pittsburgh. He can be reached at mkraemer@schneiderdowns.com.

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