AI-powered personalization in philanthropy: Transforming the donor experience

How can nonprofits create personal donor experiences at scale? Brandolon Barnett of Giving Compass explores how AI can revolutionize engagement, boosting connections and impact. 

The donor journey in the modern era

Every journey to giving is deeply personal, shaped by individual stories and experiences. For me, this path began as a young professional committed to making a difference, though my own limited resources made it challenging to find where I could have the most impact. Through my work with international NGOs and community nonprofits, I gradually found causes that aligned with my values: global education for underserved students, support for grassroots nonprofits like those in the Giving Compass network, and the creation of a more inclusive philanthropic infrastructure where diverse voices could be part of the work of bettering our world.

These priorities guide my decisions on where I volunteer, give, or serve on boards. This journey isn’t unique to me; every donor reaches their own set of causes and priorities. There is tremendous opportunity for nonprofits to connect with donors earlier in that journey. But how?

Understanding donor preferences

Nonprofits have long used data to try to answer this question and better understand donor behavior. Breaking down donor characteristics can reveal specific, actionable data points, such as:

• Demographics: age, location, income level
• Giving history: frequency, donation amounts, preferred causes
• Engagement preferences: communication style preferences, such as email, social media, or in-person events
• Values and interests: particular causes like social justice, environmental impact, or education
• Timing and response patterns: seasonal giving, preferred timing for appeals, and responsiveness

These data points form a holistic picture, helping nonprofits understand and even predict each donor’s motivations, interests, and needs.

Generative AI as a tool for analyzing donors

To understand the potential of generative artificial intelligence (AI) in this space, consider how consumer platforms like Netflix, Spotify, or Amazon use sophisticated algorithms to understand and even predict user preferences. They don’t just provide content; they create experiences that align with personal tastes. Yet for most nonprofits, achieving this kind of precision and scale has been out of reach.

Instead, traditional engagement with nonprofits often involves updates, newsletters, and general appeals that are not customized. Matching communications and engagement to each donor’s specific preferences requires extensive time and resources. In most cases, this would mean a team member documents and tracks each individual’s preferences manually—a challenging task, especially for smaller nonprofits. In short, this is time that the vast majority of nonprofits simply do not have.

This is where generative AI can become a valuable tool. With natural language processing, AI can automate much of the process, interpreting donor engagement data to suggest the most relevant next steps even for those organizations without dedicated data science teams or in-house engineers. Let’s imagine how it could work.

Game-changing AI applications to boost donor engagement

Here are just a couple of simple scenarios imagining how AI could revolutionize engagement through accessible, straightforward applications. Imagine:

• Customer relationship management (CRM) data + application programming interface (API) connector + large language model (LLM) API integration: Donor notes and interaction histories stored in a notes field in an organization’s CRM could trigger an AI model whenever that field is updated. That AI model could examine that field’s contents, retrieving the data through an API connector application (think Zapier, Make). Upon retrieving that data, the AI could cross-reference those fields with an “engagement database”—a curated list of options, from events, to donation types (recurring, one-time) to blog articles that align with the donor’s interests. Within moments, the AI would generate a match based upon its textual interpretation of the contents of the CRM note field and the engagement options. A final process within the API connector could send that data—tailored recommendations—back into the CRM into a new field that could be used to guide manual or automated actions or next steps.
• AI-powered note-taking + CRM: During donor meetings or calls, AI note-taking software could capture the entirety of a conversation. The notes could be processed by a generative AI note-taking tool and summarized (in a process similar to the one outlined above) before being sent back into a CRM into one or more summary fields. A nonprofit could produce an annual report with an export of all the notes for each donor, along with what actions they took during each time period. A tool such as Anthropic or ChatGPT could analyze that data to help discover correlations between language in summaries and, say, giving amounts, or other key decision points. This could help with giving some level of insight into potential future behaviors.

Neither of these imagined solutions require significant technical expertise. All are possible with today’s technology and affordable even to smaller grassroots organizations. The hope is that they demonstrate how, by pairing existing tools with generative AI, nonprofits can build and test innovative solutions that customize donor engagement at a scale that was not possible before.

Key considerations for nonprofits embracing AI

As nonprofits consider ways to integrate AI tools for donor engagement, they should keep these essential factors in mind:

•  LLM agnosticism: Leveraging generative AI applications without depending on a single language model provider can help with maintaining flexibility and control, which allows nonprofits to adapt to changes in technology.
•  Data security and integrity: With AI analyzing significant amounts of data, it’s critical for organizations to adopt best practices in data encryption and management to maintain donor trust. In this world, CRM and data practices are not tools of the past but are actually even more vital for success.
•  An engagement database: Consider curating a database of resources, like events, volunteer roles, and content, that AI can use to match specific donor interests with engagement options. This database can serve as the foundation for AI-driven personalized outreach.

A future vision of AI in philanthropy

AI has the power to reshape nonprofit engagement, allowing each donor journey to feel more personal and impactful. By intertwining individual stories, preferences, and real-time engagement data, AI empowers nonprofits to foster meaningful connections. In a future shaped by AI, every interaction becomes an opportunity to honor the donor’s unique journey, helping them feel like an essential part of making the world better. That feeling is more than just a feel-good outcome. It can be a key ingredient to driving higher donation rates, higher donor engagement, and greater impact.

The views and opinions of third party content providers are solely those of the author and not Fidelity Charitable. Fidelity Charitable does not guarantee the accuracy of the information provided by such third parties.