Append Second-Party Data to Your Donor File: Not for Profit Transformation Series

This is the seventh article in our eight-part series dedicated to helping NFPs develop data-driven marketing and advertising strategies to drive sustained donation growth.

December 17, 2021

Learn how other organizations’ data can help you identify net-new donors to target in your advertising.

In our previous article, Learn More About Your Current Donors, we described how to start finding net-new donors by executing several basic qualitative and quantitative research projects. Next, we want to talk about how to identify specific groups of people who may be a great fit for your NFP, but who aren’t in your core file yet—especially donors who are Gen Z, Millennials, or even Centennials—by using second-party data. 

What is Second-Party Data and Why Does it Matter?

Second-party data is essentially another organization’s data that can be used by your organization. An example of second-party data may be data from Experian, or any other credit bureau. As a credit bureau, Experian knows buying patterns, demographics, and has other information about the majority of US consumers. 

Nonprofit organizations must go beyond basic demographics and donation history and build data-rich records on each existing donor to identify not just who they are, but what they care about. This exercise helps the marketing team develop a lens by which to define lookalike audiences for targeting to support their net-new donor campaigns.

As discussed earlier in this series, enriching your current first-party data files can begin with simple email techniques to collect implicit and explicit data. However, you can fast-track the process by adding first-party data collected by other organizations that can be made accessible to you. The value of acquiring second-party data is to accelerate your ability to fill gaps in your first-party data so you can better identify “net-new” (younger) lookalike audiences and personalize messaging to engage them. 

As simplistic as this may seem, if we know what your best donors look like, or where specifically they live, it’s likely that their neighbors resemble them. People in the US tend to cluster, with like-minded individuals opting to live in the same neighborhoods. If you have a donor in their 60s living in a specific ZIP Code, it is likely that others who are in their 20s, who are similar to those more mature donors, may also be likely to donate to your NFP. 

Common Challenge: Lack of Data Augmentation Skills 

Because data is central to effective marketing campaign design, data skills are critical to your marketing team—whether in-house or via an agency partner. The problem is that there are few options for training marketing teams on the basics of data science and how to apply them to nonprofit fundraising. From data collection to data integration and subsequent analytics, data is fundamental to segmentation, targeting, and media production. This includes both first-party data (data you collect directly from donors) and second-party data (data another company collects from donors and shares with you to enrich your first-party data).

Segmentation and Targeting

When considering what second-party data you may want to add to your first-party data file, start by looking at the gaps in your existing donor data that could aid in campaign segmentation, targeting, and message personalization.

If your core donor file is limited to basic demographics (gender, marital status), contact (name, address, email, phone), and donation information (amount, frequency, payment method), consider going further by also adding valuable psychographic information (e.g. opinions, values, attitudes, interests, lifestyle). By gaining more visibility into what content people consume, how they spend their leisure time, and what causes they support, nonprofits can paint a richer picture of how best to engage their current donors and target lookalike audiences of net-new potential donors.

This can be accomplished with a simple, 3-step process:

Step 1: Provide the donor-level data file to a data append vendor, who returns the supplied donor file with additional columns of appended demographics and psychographics. The return file will show a 40-70% match rate, depending on how much identifying information is included in the original donor file. Returned files will include hundreds of columns of demographic and psychographic attributes, some of which will be data collected at the individual level, and some of which will be data extrapolated from US Census data survey data, with the later data types showing aggregate census block group statistics. 

Step 2: Apply machine learning clustering techniques (usually “k-means clustering”) to winnow down hundreds of donor append attributes to find the “most interesting” ones for the final cluster model. Once the cluster model’s “features” are selected, the resultant output includes a data-driven cluster (or segment) labeling of each of your donors. During this modeling phase, a decision is made on the total number of segments (usually, 5, 10, or 15) for the final model to output. Each segment includes donors who “look like each other” (in a statistical sense).

Step 3: Summarize and analyze various KPIs for each of your segments. (e.g., average annual donation frequency and amounts, total lifetime donations, upsell campaign response, etc.) Powered by the segment-based demographic/psychographic insights generated by Step 2, future campaign strategies can take advantage of a more thorough understanding of the traits and preferences of your target donor base. Depending on segment profiles, different segments can be used to deliver smarter campaigns—from digital lookalike campaigns to personalized email upsell campaigns and direct mail reactivation campaigns.


As discussed at the beginning of this series, many nonprofit marketing organizations continue to rely on legacy channels (direct mail, email, events) supplemented by limited paid search and Facebook. The key to finding and engaging net-new audiences is to realize that they may be active in channels where your organization is not consistently present—hence why you don’t have them as donors. By enriching your first-party data with second-party data, and then using this enhanced “lens” for targeting new potential donor audiences, your Media team or agency has more insight to inform their paid media strategy (audiences, messaging, channels, etc.)

Just as ad testing and landing page testing are critical to performance optimization of your campaigns, so too is channel testing. Different net-new donor audiences will prefer different combinations of digital touchpoints. This means nonprofit marketers must be prepared to engage across channels (Pinterest, Instagram, Tik Tok, etc.) using a combination of organic content and posts, plus paid media to tell stories and create emotional connections with the motivational drivers of Millennial and Centennial audiences.

In Summary

Finding net-new donors, who may be interested in becoming recurring monthly donors, starts with your NFP learning more about its current donors, enriching your own first-party data files and then appending second-party data from credit bureaus to that first-party data. 

Next, we will talk about another often overlooked and powerful data type, intent data. We believe that NFPs should shift focus to various types of intent data, especially as third-party cookies disappear in 2023. (In fact, at DELVE we see intent data perform especially well in programmatic advertising, outperforming pre-packed third-party data audiences.) We also encourage you to read our NFP Manifesto as well as our latest research on reaching Millennial Donors.

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Reaching Millennial Donors

Want to gain a deeper understanding of how and why Millennial donors 25-35 years of age give to social causes? Start with our 2021 Research Report, created in partnership with Aspen Finn.