DID YOU KNOW?
DonorSearch Aristotle’s AI-driven models make specific recommendations on which prospects are most likely to make a gift within 12-months. Want to learn more about DonorSearch Aristotle?
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If you don’t contact enough donors you miss out on gifts. BUT, if you contact too many donors you increase costs and decrease ROI. Does this sound familiar?
Segmentation is the classic solution to this problem. In segmentation, a subset of donors is selected based on a handful of rules or characteristics. Classic segmentation involves boiling down your donor base by RFM:
- Recency (who gave in the last 12 months)
- Frequency (how many times they’ve given over the last year)
- How much Money they’ve given (their biggest, last, or total gifts)
When you use the classic RFM segmentation method, you can reduce the size of your campaign to a smaller number. BUT, how do you know you’ve got the right donors? For that matter, do you know the right message that will motivate their generosity?
Classic RFM segmentation is limited.
RFM segments are too broad. Each of those segments could include hundreds or thousands of donors, each with their own unique donor journey. What’s more, RFM is based on what the donor did in the past. It’s NOT a prediction of what a donor is likely to do next.
You need a way to predict which donors are actually going to give to your specific fundraising ask. Most importantly, the prediction should be based on everything you know about your donors and their journeys–NOT just three pieces of data.
DATA USED IN PREDICTING FUTURE GIVING
You can begin to understand your donor’s journey–and their future–with your organization by gathering these data points:
- Age, gender, location
- The number of emails, calls, or mail appeals they’ve received already
- The time of year they like to give
- Volunteer involvement
- Event attendance
- Programs they’ve given to
- Wealth/Financial giving capacity
- Giving to similar causes
- How you acquired them as a donor
- Preferred giving methods (online, by check, etc.)
- Preferred contact methods (phone, email, letter, etc.)
- Other unique ways they’ve interacted with your organization (for example, if you’re a healthcare provider, how many times did they receive treatment? Who was their physician?, etc.)
Nonprofits commonly use predictive analytics, the process of studying all of the possible data to make accurate predictions of future giving. It’s extremely hard, if not impossible, to handle on your own.
That’s where artificial intelligence/machine learning software like DonorSearch Aristotle comes in. We study your data to find trends and make predictions down to the individual level—no more clustering donors into vague RFM segments.
DonorSearch Aristotle and DonorSearch’s machine learning software makes precise predictions that completely replace the time-consuming process of studying your data to develop targeted campaign lists.
Want to learn more about DonorSearch Aristotle? Click Get a Demo below.
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You’ll raise more money for your mission without draining your team’s time and attention along the way.