Finding UNICEF USA’s new lifetime donors with Delve Deeper’s Audience-First Giving Pyramid.
In Short:
UNICEF USA was looking to improve long-term donor prospects in a crowded digital-media economy and fundraising landscape. Delve Deeper helped UNICEF USA achieve its goals by guiding the organization in its first significant push into first-party data and machine-learning modeling in digital marketing.
The Challenge:
Like many nonprofits, UNICEF USA has long relied on older audiences, namely baby boomers, for a significant portion of annual donations. Older generations tend to be wealthier, so they are a critical and large part of the donation landscape. But as baby boomers age out of their donation years, nonprofits like UNICEF USA need to recruit younger generations and grow them into long-term donors.
Still, with limited marketing dollars to spend, nonprofits can struggle to meet their donation goals, and they often don’t have internal resources to identify ways to improve their marketing efficiency.
The Approach:
UNICEF USA selected Delve Deeper to solve both its generational and efficiency issues.
We knew that we could identify new, high-value audiences, and one way to achieve that was by ushering UNICEF USA into the first-party data era. This would enable the charity to better understand its audiences and improve the efficiency of its marketing budget.
Using our proprietary Audience-First Giving Pyramid framework and leveraging 15 years of first-party historical data, we conducted six targeted tests aimed at boosting UNICEF USA’s reach to find newer, younger audiences to secure long-term donations.
Our integrated approach combined technology, data, and media to build predictive models that identified high-value donors — a cohort we coined “SuperDonors” — and serve them personalized content to generate interest. SuperDonors are individuals with a high likelihood of becoming monthly donors or contributing to specific causes, and we were able to identify audiences that had a high likelihood of being long-term donors.
Delve Deeper’s data science team utilized look-alike (LAL) audiences to find and engage net-new donors. UNICEF USA’s media investment was made more effective by focusing ad dollars only on those high-value audiences. Also, specific ads were tailored to these LAL audiences based on each campaign’s goals.
Summary:
Delve Deeper Results:
Our strategy helped UNICEF USA harness advanced data and technology paired with effective media activation.