AI for Fundraising: AI Analysis vs Human Intuition


When you begin implementing fundraising AI, you may receive pushback from people saying “why do we need AI to do that when I can do it myself” or “a computer won’t be able to fundraise, fundraising is about people”. 

While it’s true that human fundraisers play a critical role in fundraising, and that fundraising is about people, AI for fundraising offers nonprofits valuable insights and efficiencies to make their fundraising better. This is because AI is capable of analyzing huge sets of data and spotting patterns, this leads to predictions that are more accurate than human intuition. 

When you have an AI nonprofit fundraising software looking after your data, it frees up time for your fundraising team to focus on building donor relationships. 

How AI Makes Predictions

One of the biggest opportunities of AI for fundraising is the ability to make predictions about a donor’s next gift. An experienced fundraiser may be able to do this using human intuition, but AI will be more accurate in more cases. 

Predictions from both human intuition and artificial intelligence are spruced from past behaviour and data. But AI can analyze and access more data than a human can, making the result more accurate.

Here’s an example:

If you’re standing at the side of a racetrack and a car passes you going 30 kilometers per hour, then a second car passes going 40km/h, and a third car going 50. Based on this you would expect the fourth car to be going at 60km/h.

If an AI was standing next to you at the racetrack, it might actually tell you that the next car will be going 70km/h. 

This is because the AI is not looking at just one car, it’s not even looking at just the three cars that passed you. The AI could have a data set from 500 cars that have driven on this racetrack that shows the most likely speed for the car that is coming will be 70km/h.

How AI supports Fundraisers

We can apply a similar scenario to donors. Imagine that you have a donor who has made an annual donation of $25 every year for four years. Then, out of the blue, they suddenly give $400. 

Depending on your organization size this could be considered a big gift or a small gift. In this scenario let’s imagine you work at a large nonprofit and your mid-level giving starts at $500. In this case $400 doesn’t seem like a considerable amount, so this donor would stay in your mass fundraising program. 

If you were putting together a direct mail solicitation that included this donor their gift matrix could place the ask on an array of $100-$400. Based on current strategy, this would look like an appropriate ask amount. 

However, fundraising AI could flag that the sudden increase in gift size is a marker for a major donor. Within your database there could be donors who gave smaller annual gifts over the years then suddenly made a similar jump in giving just like our $400 donor did. 

Then following this sudden jump these donors went on to give as much as a 1000% increase on their giving on their next gift. This increase made them mid-level and maybe even major gift donors. 

You are planning to ask this donor for a donation between $100 and $400, but AI for fundraising would know that the subsequent gift in this case can actually be 3x their highest gift: $1,200.

That’s a difference of $800, not to mention the increased lifetime value of this donor that would come from migrating them into your mid-level giving program, adding them to a fundraisers portfolio, and sending them personal stewardship touchpoints. 

The type of predictions AI can produce would take skilled analysts or fundraisers countless hours. Instead, the computer can provide it almost instantaneously, allowing fundraisers to focus on the relationship, while the AI provides new insights.

When it comes to AI for fundraising, there are things that AI can do that a human fundraiser cannot. It would take hours of data analysis for a human fundraiser to even come close and still miss the mark most of the time. That fundraiser’s time is better spent doing something that a machine can’t do: connecting with donors! 

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