How UNICEF USA Found New Donors with 2.7x Higher Conversion Rates
In short:
Delve Deeper partnered with UNICEF USA to transform their end-of-year (EOY) fundraising by identifying and engaging net new donors outside the existing loyal base with a high propensity to donate. Using advanced machine learning models and targeted digital activation, this approach drove a 2.7x increase in conversion rates among these new donors and a 44% lift in total donations, maximizing impact during a critical fundraising period.
The challenge:
The primary challenge for UNICEF USA was to enhance their fundraising initiatives during the EOY season, which historically accounts for approximately 40% of their annual donations.
The organization needed to identify and engage donors with a high propensity to donate who were not previously recognized within the loyal donor base, thereby expanding and diversifying their donor pool to boost overall contributions.
The approach:
In November 2024, Delve Deeper implemented a focused, data-driven strategy aimed specifically at acquiring new, high-propensity donors for UNICEF USA’s EOY campaign. This began with a comprehensive refresh of donor data to ensure accuracy.
Leveraging insights from prior campaigns, the team strategically excluded the established ‘Surefire Loyal Donors’—those with proven high conversion—from the modeling process, concentrating efforts on uncovering less predictable, untapped donor segments. Advanced machine learning models were employed to classify the broader donor pool into high- and low-propensity groups, enabling precise targeting of those new donors most likely to give.
These high-potential new donors were activated through carefully tailored campaigns across Programmatic Advertising and Search Engine Marketing (SEM), fully integrated with UNICEF USA’s CRM for real-time monitoring and dynamic optimization, ensuring maximized donor acquisition during the vital EOY period.
Summary:
Delve Deeper Results:
This targeted approach yielded outstanding results. The newly acquired donor segments converted at 2.7 times the rate of non-modeled audiences, validating the effectiveness of machine learning-driven targeting.
Overall donations rose by 44%, with total revenue from these net new donors tripling compared to traditional acquisition methods. Conversion rates improved across all targeted segments, underscoring the success of engaging previously untapped donors with high giving potential and setting a new benchmark for UNICEF USA’s fundraising strategy.