Smarter Donor Segmentation with AI-Powered Analysis
I LOVE donor segmentation. But for those of us who are not data whizzes, or don't have time to pore over a spreadsheet, it can be really intimidating to think about having to segment a bunch of donor data. And, while we tend to think about tools like jet GBT as writing assistance, we can actually use them to go beyond basic donor demographics and delve into donor motivations and giving patterns - without having to be data scientists.
Let’s take a look at what type of segmentation we can use, and how - exactly - we can make this happen. A few examples of the type of trends that an AI tool like Chat GPT and Google Gemini can find are:
Lapsed donors: AI can analyze donation history to identify donors who have previously given but haven't renewed their support recently. This could uncover patterns like recurring giving on an anniversary date or gaps in donations due to events like job changes. Targeted re-engagement campaigns can be designed based on these insights.
Event-driven donors: AI can identify donors who primarily give during specific events, such as a year-end campaign or a gala. Understanding these event-driven motivations allows you to tailor your communications and engagement strategies throughout the year to these donors.
Recurring donors with increased capacity: AI can track donation amounts over time to identify recurring donors whose contributions are steadily increasing. This points towards increased financial capacity and a willingness to give more. These donors could be prime candidates for a major gift or planned giving conversations.
Start With Your Data Sources
AI is a sidekick, not a shortcut, so you’ll still need to get your data together before you can start segmenting. Hopefully your donor database is in good enough shape that you can export:
Contact information
Donation History (with dates, amounts, and designations)
Event attendance
Volunteer history
…and any other notes, communication preferences, and more that you have tracked.
You would need this data accurate and organized regardless of whether you’re using AI, so if you are feeling insecure about your donor CRM, it may be time for some spring cleaning!
Read More: Ten Useful Ways You Can Use Your Nonprofit Database Better
Prep Your Spreadsheets
Choose a format: AI tools generally handle .CSV (Comma Separated Values) or Excel spreadsheets.
Clean and standardized data:
Ensure consistent date formats (e.g., MM/DD/YYYY)
Avoid blank cells or inconsistencies
Use clear column headers for easy identification
Merge data sources: If possible, combine data from various sources into a single spreadsheet. Match records using a unique identifier like email address.
Give Guidance
Upload your data: Follow the tool's specific instructions for how to upload your spreadsheet(s).
Ask focused questions: Instead of expecting the AI tool to generate insights on its own, start with specific questions like:
"Which donor segment has the highest likelihood to upgrade to major gifts?"
"What communication channels are most effective for re-engaging lapsed donors?"
"Are there common keywords or interests among our most engaged social media followers?"
Analyze and interpret: The AI tool will generate results, likely including tables, summaries, or visualizations. Pay attention to:
Correlations identified by AI
Donor segments or trends that emerge
Unexpected findings
Read More: The Simple Secret to Keeping New Donors That Most Nonprofits Forget
How to Use the Data Outputs
Once you've fed your data to the AI tool and received the analysis, here are ways to turn those insights into actionable steps for your fundraising:
Use identified donor segments to create tailored communications. For instance, if AI reveals a group of event-driven donors, create a special campaign highlighting your next gala. You might also note potential monthly donors based on their giving history.
Use predictive models to forecast campaign success. If AI suggests a particular segment is primed for a major gift ask, allocate resources accordingly.
Have AI assign affinity scores or name segments so you can start focusing on the subsets of your door data.
Let AI flag potential donor attrition risk. Proactively reach out to those identified as likely to lapse with personalized engagement.
Keep in mind that this is just the beginning. Concentrate on practical insights that you can actually use, such as recognizing donor attrition or even just organizing your data for you. It wont help to try to learn everything and get overwhelmed with all the data that you've extracted. And, of course, don't forget the human touch! At the end of the day AI is just a tool and the magic of fundraising still remains in building authentic relationships.
Read More: 5 Examples of How Automation = Better Fundraising
A Note on AI Ethics
Ethics continue to be a significant consideration when it comes to adopting AI. The commonplace use of AI is so new it still feels a bit like the wild west. AI is a very powerful tool for better resourcing small nonprofits and supporting different learning and working styles, but it’s also important to consider that bias in source data, data privacy, copyright, and many other ethical concerns as we adopt AI. Ethics and AI is a topic I am continuing to research and understand, which is why I’m not writing much about it - yet!