Using Data Analytics In Fundraising

How to raise $50,000 in 30 days using 7 AI prompts (you’ve never thought to use): AI won’t replace fundraisers. But fundraisers who use AI strategically will absolutely outperform the ones who don’t. These 7 prompts aren’t basic. They’re engineered to unlock human behavior, decision-making psychology, and funding at scale. 1. Prompt: “Analyze our past 10 email campaigns. Identify the emotional tone, structure, and CTA that drove the most clicks and donations. Suggest 3 new email angles based on behavioral trends.” Why it works: Donors respond to patterns. This prompt uses your own data to reverse-engineer what actually moves people, not what feels right. 2. Prompt: “Write a donor pitch using the ‘Commitment-Consistency’ principle from Cialdini, reference a donor’s past actions and show how giving now is aligned with who they already are.” Why it works: People are more likely to act in ways that align with their self-image. Donors who’ve volunteered, signed petitions, or shared your content? This is how you turn engagement into dollars. 3. Prompt: “Create a 3-part story arc for LinkedIn posts that subtly shift a corporate contact from passive observer to strategic partner, without ever asking for money.” Why it works: It’s called affinity priming. AI scripts the story. LinkedIn builds trust. You close the deal. 4. Prompt: “Generate 5 donor thank-you messages tailored by giving tier, use loss aversion and social proof to increase chances of a second gift.” Why it works: “Thank you” is a sales moment in disguise. This prompt makes it count. One client turned 23% of first-time donors into recurring givers using tiered messaging like this. 5. Prompt: “Draft a voicemail script for a lapsed donor using the Ben Franklin effect, ask for a small favor instead of a gift, to reactivate the relationship.” Why it works: People feel closer to those they help. Use it to rebuild trust without making an ask. Often, the donation follows. 6. Prompt: “Identify 3 psychological barriers to giving on our donation page. Rewrite the copy to reduce friction using clarity, scarcity, and immediacy.” Why it works: Most pages leak donations. This prompt fixes that, leading to real revenue recovery. One org tested this and saw their average donation increase from $48 to $71 just by shifting copy. 7. Prompt: “Write a short pitch that reframes our mission as a business case for corporate ESG leads, focused on risk reduction, brand lift, and employee retention.” Why it works: Companies don’t give because of charity. They give because it aligns with strategy. This prompt flips the frame, and unlocks five-figure partnerships. These are just a few of the 40+ AI scripts inside our AI Launchpad Cohort, a hands-on experience for nonprofits ready to raise more with less guesswork. Comment Launchpad and we’ll send you details about the upcoming cohort. With purpose and impact, Mario

Charity Leaders & AI: Where Do We Start? 🤖 I've spent the last few years helping charities embed digital (and increasingly AI) into their core mission. AI was today's topic on the Third Sector Lab x SCVO Digital Senior Leaders Programme with me, John Fitzgerald and Maddie Stark Here's the questions charity leaders need to ask plus a few practical ways to move the conversation from hype to strategy 👇 The Big Questions We Need to Ask❓ - Where is AI already affecting our mission—positively or negatively? - How empowered (or anxious) do our staff and volunteers feel about AI? - Which parts of our work could AI actually improve (reach, impact, efficiency)? - Do we understand the risks—data, ethics, trust? How will we keep our values central? - Who else in our network is experimenting with AI and what are they learning? Five Practical Steps for AI-Ready Leaders 5️⃣ AI Impact Mapping 🗺️ Bring your team together. Map every touchpoint where AI could play a role - from fundraising and supporter comms to governance and frontline service. Pinpoint where the real wins and risks are for your charity. Staff & Volunteer Pulse Check 🩺 Run a session where people role-play different AI scenarios. What opportunities and anxieties bubble up? (Be ready for honest feedback!) Use it as a way to shape your AI literacy and support plans. Debate Real-World AI Use Cases 👥 Share case studies: the good, the bad, and the complex. Chatbots for helplines? Automated grant app sorting? Data-driven supporter segmentation? Debate - don’t sell - the practicalities and ethical red lines. Risk & Governance Tabletop 🎲 Role play as trustees, comms, digital leads, service staff—respond to an data breach as a result of AI usage or staff concerns about AI bias in recruitment. Work out who needs to be in the room when things go wrong, and what new protocols may be needed. Quickfire AI Experiment 🧪 Have your team test a popular AI tool - draft a donor email, summarise a board paper, generate a campaign image. Use Co-Pilot, ChatGPT, Perplexity, Claude, Gemini or whatever tool is most relevant to your needs. Compare notes: What worked, what failed, where was human oversight crucial? Make Space for Messy Conversations 🪢 - Is AI use visible or happening “off the books?” - What would success - or failure - with AI look like for us next year? - How can we work across the sector for stronger, more ethical approaches? - What are the values we refuse to compromise on, no matter what shiny AI tool we see? Don’t Forget: Make It Actionable 💪 - Finish your next senior team meeting with a commitment - Run a staff survey on AI - Pilot a small AI project - Join or create a sector AI peer group If you’ve taken baby steps, had a tough internal debate, or even failed spectacularly, or you just want to share a handy resource - I want to hear about it in the comments 👇

Could social media help raise $5.5M in just 24 hours? The The University of Georgia's annual Dawg Day of Giving campaign rallies students, alumni, and supporters to donate in a single day. High stakes, 100+ social posts to manage, and a small team of three strategists covering 400,000+ people. This year, they 5x'd their social-attributed revenue. How? They listened before they posted. Using social intelligence, they tracked real-time conversations across the Georgia Bulldogs community - fan-generated content, emotional alumni moments, trending topics they would've missed otherwise. They turned those insights into content that resonated. Their analytics revealed something counterintuitive: static image carousels were outperforming video. So they stopped pouring resources into video production and doubled down on what was working. Data killed their initial assumptions. And they were able to generate better results with less effort. The outcome: → $5.5M raised in 24 hours → 522% increase in revenue attributed to social → 54% YoY increase in digital giving revenue → 1M+ Instagram views on a single campaign Social isn't just a brand awareness play. When you combine listening with data-driven content, it becomes a revenue engine. What business impact could your organization be driving with social?

One year ago, my team set out with a simple but ambitious idea: could a Virtual Engagement Officer engage donors independently and deliver meaningful results? Today, with more than 70,000 donors managed, the answer is yes. The scale of Autonomous Fundraising is remarkable—and among the most compelling reasons is the quantifiable data. With a wide spectrum of use cases and organizations across nonprofit verticals, sizes, geographies, and donor demographics, we can now confidently answer a common question: which donors respond best to Autonomous Fundraising? What strikes me is how the data confirms certain assumptions and challenges others. When the goal is dollars in the door, recency matters more than giving capacity: •Over 88% of the top-dollar donors engaged by a VEO had lapsed no more than one year. •Only 9% had lapsed more than three years. •A current $500 donor is often a better bet than a $1,000 donor last seen five years ago. As a fundraiser, this isn’t surprising at all. While we all have stories of long-lapsed or first-time donors suddenly surfacing with major gifts, they’re far less statistically likely in both traditional and autonomous fundraising. The best performing portfolios consider both today’s revenue and tomorrow’s prospects, balanced with: •75% current donors with upgrade potential.  •25% recently lapsed donors with strong giving history. That mix consistently surfaces donors ready to graduate into a gift officer’s portfolio. Demographically, donors between ages 50–72 show the highest engagement and strongest giving. Donors who reply, click, and open messages—even modestly—become some of the most loyal over time. Of those who readily engage with the VEO, nearly 50% have given at least once, and more than 25% have made multiple gifts since being assigned to a VEO portfolio. The VEO’s purpose is to strengthen connections that lead to giving, and this data shows it is delivering on that promise. These patterns hold across very different contexts—from organizations with hundreds of thousands of active donors to smaller nonprofits with only a few thousand. More importantly, they provide a framework for designing portfolios aligned to specific goals: immediate revenue, building tomorrow’s pipeline, or re-engaging donors during the window when they’re statistically most likely to return. One year in, the lesson is clear: many donors thrive in Autonomous Fundraising portfolios, and now we know who they are. The bigger opportunity is what comes next. With 97.5% of donors traditionally unmanaged, this framework gives us a way to reach them with the attention they deserve—and a foundation for exploring how strategies evolve, how donor perception shifts, and how growth carries forward into year two.

AI is only as powerful as the problems it solves. For nonprofits, one of the most fundamental challenges is knowing how much to ask for, and when. Ask too high, and you risk discouraging a gift. Ask too low, and you leave potential impact on the table. That’s why we’ve taken Intelligent Ask Amounts to the next level for GoFundMe Pro partners. Grounded in deep user research and powered by GoFundMe’s AI models, this improved version gives nonprofits the ability to dynamically optimize campaigns for what matters most: one-time revenue, conversions, recurring gifts, or a balanced mix. The ask amounts adapt in real time to donor behavior and campaign goals—helping nonprofits drive more sustainable giving. The best part? These improvements are to a product that has already delivered results. For example: the National Civil Rights Museum used Intelligent Ask Amounts during key giving moments and saw a 62% increase in average gift size on December 31st year-over-year, along with other strong gains. (I’ll link the case study with more details in the comments!) What makes me proud isn’t just the AI, it’s the teamwork behind it. Three product pods, Applied Science, Research, CX, Legal, Marketing, Comms and more all came together to turn a complex fundraising challenge into a solution that’s both powerful and practical. Because at the end of the day, innovation is only meaningful when it helps nonprofits raise more with less friction—so they can focus on their mission. 👉 Learn more here: https://gfme.co/47CvtSc 

My nonprofits in the community - are you planning a donor survey in the next two months? Here are some examples of how you can ensure that the data does not sit silently in your work folders but actually lets it help you take meaningful actions. Example 1: Say your survey question is: "How likely are you to continue donating to our organization in the next year?" ● Data says: If 60% of donors say they are "very likely" to continue donating, but 30% are "somewhat likely" and 10% are "unlikely," this indicates a potential drop-off in donor retention. ● Turning that data into action: Focus retention efforts on the "somewhat likely" group. Create a targeted campaign that re-engages these donors by highlighting recent successes, impact stories, or new initiatives they might care about. Additionally, reach out to the "unlikely" group to understand their concerns and see if any issues can be addressed. Example 2: Say your survey question is: "Which of the following areas do you believe your donation has the most impact?" ● Data says: 50% of respondents say their donation has the most impact on "Education Programs," while only 10% say "Healthcare Initiatives." ● Turning that data into action: Understand the why and promote the success and need for your "Healthcare Initiatives" more prominently, aiming to increase donor awareness and support in this underfunded area. Example 3: Say your survey question is: "What is your primary reason for donating to our organization?" ● Data says: If the top reason to engage is "Alignment with my values" (40%) followed by "Transparency in how funds are used" (35%). ● Turning that data into action: Emphasize your organization's values and transparency in all communications. Regularly update donors on how their funds are being used with clear, detailed reports, and align your messaging with the core values that resonate with your donor base. Example 4: Say your survey question is: "How satisfied are you with the level of communication you receive from our organization?" ● Data says: If 70% of donors are "satisfied", 20% are "neutral," and 10% are "dissatisfied," there's room for improvement in communication. ● Turning that data into action: Understand the "neutral" and "dissatisfied" groups to pinpoint where communication may be lacking. This could involve increasing the frequency of updates, personalizing communications, or providing more opportunities for donor feedback and engagement. Sit with the data you collect. Read the numbers. Read the stories. Read the hopes, barriers, and interests of those humans in your data. The best possibility of a survey is to make the humans in that data feel included and belong by listening and acting on their perspectives. Co-create change with your community in those surveys. #nonprofits #nonprofitleadership #community #inclusion

Most AI tools for fundraising miss the point. They’re built by people who’ve never actually raised money. So they focus on surface problems: • Finding investors • Writing emails • Scraping data. Useful in parts for sure. But that's not where fundraises fail. The hardest part of fundraising isn’t sourcing names. Or spamming more investors via cold email. It’s building trust in real time. It’s learning how to: 1. Lead investor conversations 2. Read subtle signals, and 3. Manage momentum. And that’s where AI is quietly about to change everything. For the first time, founders can: • Practise their pitch against a simulated investor • Get contextual feedback on tone, pacing and clarity • Map their structure before a single meeting happens It’s like running 100 fundraise reps before your first call. My own AIs are already hitting 80 % of my live sessions. Which means founders can now use them between sessions: 1. To rehearse 2. To refine 3. To rebuild confidence daily This isn’t about replacing experience. It’s about compressing it. The tedious, messy, high-friction parts of fundraising are about to become fast, structured, and learnable. The human part (trust, emotion, narrative) becomes the main event again. Would you use this type of AI for your own fundraise if let you use it?

The purpose of fundraising analytics is not to explain what happened. It is to improve the decision before it happens. I learned that lesson leading business planning and analytics across a $15B organization, where every analysis ultimately had to answer one question: What decision will this improve? When I began working more deeply with Christian ministries, what surprised me wasn't the mission. It was how often fundraising analytics entered the process after the most consequential decisions had already been made. By the time the reports arrived, the donors had been selected, the appeal had been written, the package had been printed, the postage had been committed, and the campaign was already in the field. The analysis might explain the outcome perfectly, but it could no longer improve the decisions that produced it. Most organizations spend weeks optimizing the appeal. Very few ever validate whether they're sending it to the right donors. The biggest fundraising decision isn't what you mail. It's who you mail. RFM answers a historical question. Your next campaign is asking a predictive one: Who is most likely to respond now? In one validation, a ministry had already finalized its mailing file using RFM. Pulse Predictive identified fewer than 5,000 donors outside that mailing file who should have been included. Those donors generated more than $750,000 in net income and a 193:1 ROI. The opportunity wasn't outside the donor database. It was hiding just outside the mailing file. That's the difference between reporting and decision intelligence. Reporting explains yesterday. Decision intelligence improves tomorrow. That's why we built Pulse Predictive—to validate one of the most important decisions made before a campaign launches: Are we mailing the right donors? Using anonymous historical donor data, we make a blind prediction before the campaign is mailed. Your own results determine whether we were right. No software demo, no donor names, just evidence. If your next mailing file hasn't been finalized, let's validate it before you spend another dollar on print and postage. Comment "VALIDATE" or send me a direct message. 👇 At what point does analytics enter your fundraising process—before the decision or after the results? 🔁 Repost if better fundraising decisions deserve as much attention as better fundraising reports. 🚀 Follow Jerry Rassamni for practical insights on AI, predictive fundraising, and helping ministries maximize stewardship through better decisions. #Fundraising #NonprofitLeadership #ChristianMinistry #PredictiveAnalytics #LongGame

Donors are using Claude and ChatGPT to decide which nonprofits to fund. Most foundation CEOs I talk to still think AI is something their grants team will figure out next year. In the last 90 days, watching donor behavior through our Charity Navigator AI search pilot, we've seen the shift in real time: 1. Cause-based queries are replacing organization-name searches. People ask "who's doing the best work on maternal health in the USA" instead of typing in a nonprofit they already know. 2. Checkout rates doubled when AI surfaced the right org at the right moment. 3. Donate-button intent jumped 64% when the discovery experience was conversational instead of a search bar. The implication is uncomfortable. If your nonprofit, foundation, or platform isn't visible to AI, you're becoming invisible to donors. The infrastructure question for 2026 isn't "should we use AI." It's whether your data is structured so AI can find you, understand you, and recommend you. Most of the sector hasn't noticed yet. #Philanthropy #AI #Fundraising

I once worked with a university that struggled to meet its fundraising goals. They were reaching out to alumni randomly, hoping for the best. Then we introduced prospect research. The transformation was incredible. By identifying the right prospects and understanding their capacity and affinity, we increased major gifts by 150% in just one year. Here's what we did: Analyzed giving history: We looked at past donations to identify consistent givers and those with potential to give more. Researched professional backgrounds: LinkedIn and other public sources helped us understand career trajectories and potential giving capacity. Examined philanthropic interests: We investigated involvement with other nonprofits to align our asks with donors' passions. Leveraged wealth screening tools: These helped us identify high-net-worth individuals we might have overlooked. Mapped relationships: We uncovered connections between prospects and our board members or major donors. The result? More targeted outreach, personalized communication, and significantly larger gifts. The lesson? Don't underestimate the power of informed outreach. Prospect research isn't just for large organizations - it's a game-changer for nonprofits of all sizes. React 🎓 if you believe in the power of research! Have you had a similar experience with prospect research? Or are you considering implementing it? I'd love to hear your thoughts and experiences in the comments! Remember, effective fundraising isn't about asking everyone for money. It's about asking the right people for the right amount, for the right project, at the right time. And that's where prospect research shines.