After witnessing the world spiral in the past few months (and seeing how far we must go to achieve social justice), I think we all can agree that there are no quick routes to work through the social injustices around us. In fact, our efforts must go beyond bringing alive the concepts of diversity, equity, inclusion and accessibility to frontline fundraising and donor relationships only. Regardless of our titles and departments in the organization, each of us must ask ourselves, what is my role in contributing towards equity through my work? I do the same as a research and analytics professional.

In this article, I want to share 4-ways in which I pushed for a different than usual flavor of research and analytics for my consulting engagements. Ways that were aimed to bring all constituents together so the decision-making informed by the analysis would be inclusive of the whole community they served. In each of the four examples I will share not only what we did but also how those research activities shaped the conversation about next steps.

1. During engagement analysis: extend RFM and include all constituents.

My task was straightforward – based on the available data, evaluate the engagement of donors. But, instead of restricting to the current donors, the Campaign Director and I decided to include all constituents. Thus, this constituent group had volunteers, gala attendees, members (as a membership-based organization), former supporters, and all board members. This decision took our number of records from 450-ish to close to 1500. Including all constituents in the analysis allowed us to expand the team’s outlook of “engagement” beyond current mid-level/major donors only. Besides, they were a team of 4 fundraisers with not an entirely optimized portfolio. So, broadening the population for assessing engagement also created a path for portfolio optimization later.

Now, because we included a broader population than the donors, I realized data for RFM score (Recency, Frequency, and Monetary aspects of giving) would not be available for all constituencies. So, we decided to extend RFM to a score composed of

• giving
• volunteering
• participation (event and online program participation)
• relationship (where a current volunteer/donor/member has higher weightage than former volunteer/donor/member; former being anyone not associated, in any form, for the last three years).

This analysis allowed us to look at the constituents from a broader lens than pure giving. Outcome? We sparked conversations about holistic portfolio optimization and how to leverage the engaged names for their upcoming fall campaign.

2. During a stewardship survey: extend the participant list to all constituents.

Last year, I was a pro-bono research advisor for an immigrant mentorship organization that wasn’t very old. The organization was celebrating its third anniversary when I volunteered with them. Back then, the organization had about 1,500 constituents – primarily volunteers, mentees, and mentors. About 70-75 of those constituents were the organization’s donors. My job was to develop a survey tool for stewarding their donors.

The Director of Development and I decided to evaluate whether a strategy change could be worth it instead of jumping straight to questionnaire design. And we began with the question, why do we only need to steward the donors? I loved the direction of the conversation that followed! We decided to survey everyone with some association with the organization and, of course, with a valid email address (duh!).

That survey was so wildly successful that it led to two reasons for celebration:

• We crafted a focused strategy for 2021 summer and fall programming (that has been so far very popular)
• They used the results of the survey in securing their corporate sponsorship. Not only did they secure funding more than needed, but they also opened channels for more mentors and mentees from those corporate offices. Win-win!

3. During a campaign dashboard assessment: ensure inclusivity for all dashboard users

A few months back, I was working for an organization in the middle of their seven-year campaign. They had a lean (and vital) prospect research team for roughly 35 fundraisers. The organization had set up necessary dashboards to track their campaign progress. I was brought as an interim program manager to evaluate dashboards and identify any inefficiencies in campaign-related processes.

Two issues (as observed for many organizations) were abundantly clear from the start:

• The dashboards lived in two places (SharePoint and DropBox) in 2-3 different formats: PDFs, images, and linked URLs.
• Of the 35 fundraisers (including the campaign leadership team), only 7-10 accessed the dashboard regularly to follow the real-time updates. Others either depended on the bi-weekly strategy meetings (when the campaign progress was announced) or asked their colleagues for printouts. Upon a closer look to understand the why behind this behavior, it seemed the dashboards, even though they reported the correct numbers in visual charts, lacked some inclusivity basics.

We composed a subset team consisting of a representative of their IT team, two fundraisers who were very engaged with the dashboard, and two who weren’t so engaged with the dashboard. From there, we identified the critical challenges in the holistic usage of those dashboards. We concluded our final discussion with four major action items:

• Remove all redundant formats of the dashboard to keep only one linked URL to the live dashboard.
• Develop a “help” page on the dashboard to explain all metrics, calculations, and underlying data.
• Create a limited-time lunch-and-learn session, for no more than 7-10 fundraisers at a time, where the nuts and bolts of the dashboard were shown and discussed. This strategy created a safe space for the fundraisers to ask their technical questions without hesitation.
• Build in 20 minutes in every team-wide donor strategy meeting agenda to chat about “so what does this mean?”. The Campaign Director was encouraged to welcome different fundraisers for every meeting to share their perspectives. That way, no fundraiser had to feel pressured to explain the metrics/charts but could still bring forward their questions/perspectives/interpretation.

Though initially it took some time to pick the pace for adopting the ideas (especially the lunch and learn), the organization is now at a robust place where the overall comfort level of all their fundraisers is higher than before.

4. When predicting major gift donors using predictive analytics: review how you set up your algorithm.

Machine learning-based analytics can be used to predict if your prospect is likely going to be a major gift donor or not. That is what I did in my engagement with a mid-size, membership-based cycling advocacy organization. My task was to leverage their data and identify their likely major gift donors for their year-end campaign. To give a simplified version – in predictive algorithms, we use a set of independent variables (e.g., giving, volunteering, event participation, etc.) to predict a dependent variable (e.g., an indicator for “major gift donor?” that can be a yes/no).

In setting up our model, we changed how we defined that dependent variable (i.e., the indicator “major gift donor?”). Usually, it would be described as – someone who gives more than the major gift threshold dollar amount is set to be is “yes”, otherwise is “no”. Instead, we approached it differently. The Director of Development shared that the organization was old (more than 25 years old), but the fundraising team had always been lean. Their retention was notoriously low, so he suspected that the organization never really had a solid approach to identifying and soliciting major gifts. That means the major gift donors were those whom the current fundraisers asked for gifts. To give numbers – this organization had about 5,000 constituents, and they had roughly 150 major donors. The Director of Development suspected that number should have been way higher with the proper research long back.

So, I went back to conduct an engagement analysis and a screening from their prospect research tool. Combining those two, I created a score to identify who was likely to make a major gift. And that changed our dependent variable described above (i.e., the indicator “major gift donor?”) to include not only those who had made a major gift but also those who were likely to make one (based on their engagement and wealth). This modeling allowed us to understand engagement patterns from a much broader population than merely the 150 major donors.

Remember, to achieve that equity we strive for, we must take a closer look at our “usual” research practices and be willing to change those practices with a clear why. It is not going to be easy, but we must take the first step.

Meena Das is a Fundraising Analytics Consultant with a U.S.-based consulting firm. She specializes in designing and analyzing survey-based research tools. Meena appreciates spending her time outside work as a mentor to immigrants and pro bono research advisor to Nonprofits. Her two recent favorite projects are working on making data-based research tools more DEIA (Diversity, Equity, Inclusion, and Accessibility) compliant and designing the second season of her podcast “Being and Unbeing parents of an Immigrant”, where she wants to bring together the families of immigrants left behind in the home country. Connect with Meena on LinkedIn.