How SOS Méditerranée used Predictive AI to identify its highest-potential mid-donors and cut campaign waste by 90%.
Corinne Melet leads fundraising efforts at SOS MEDITERRANEE, a European maritime-humanitarian organization dedicated to rescuing people in distress in the Mediterranean Sea. Operating across France, Germany, Italy, and Switzerland, the NGO has conducted over 900 rescue missions and saved more than 38,000 lives sustained largely by a community of over 40,000 private donors, who contribute 91% of its funding.
She shares how Predictive AI helped SOS MEDITERRANEE sharpen its fundraising strategy, save time, and raise more funds.
SOS MEDITERRANEE operates in a shifting fundraising landscape: the overall pool of donors is shrinking, but the average value of individual contributions is rising. This creates both a strategic opportunity and a pressure — the organization must work smarter to capture greater value from a more selective donor base.
To respond, SOS MEDITERRANEE set two clear fundraising priorities, both supported by Allyy:
Like many nonprofit organizations, SOS MEDITERRANEE had accumulated years of rich donor data — but lacked the capacity to activate it strategically. Identifying potential middle donors and monthly givers at scale was difficult, for several compounding reasons:
The organization needed a solution that could transform historical donor behavior into actionable, campaign-ready insights — seamlessly integrated into existing CRM workflows — so the fundraising team could focus their efforts where they would have the greatest long-term impact.
Allyy applied predictive AI to rank donors by their likelihood to respond to the next direct mail campaign and, over time, become middle donors or convert to monthly giving.
Using eight years of historical donation data, Allyy engineered over 120 behavioral features — including donation recency, frequency, growth trajectory, and channel mix. A machine learning model was trained to assign each donor contact a score between 0 and 1.
Rather than a binary yes/no prediction, this is a ranking system: the goal is not to predict with certainty, but to prioritize intelligently.
Allyy connects directly to SOS MEDITERRANEE's CRM, extracts the relevant data, and continuously performs modeling and scoring. The ranked scores are delivered back into the CRM, where the fundraising team selects top candidates for each campaign, particularly those with the highest middle-donor and monthly-giving potential.
By replacing guesswork with data-driven prioritization, SOS MEDITERRANEE significantly improved the efficiency of its high-value donor fundraising:
The precision of the predictive model was striking:
By narrowing focus without sacrificing fundraising potential, the team was able to run more efficient campaigns and dedicate more time and resources to the supporters most likely to deliver lasting, long-term value to the organization's mission.
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