Three easy ways to get started with AI for fundraising

Artificial intelligence is driving change across all aspects of our lives. But the idea of using ‘AI’-driven tools in our jobs as fundraisers sounds daunting. Surely it will be too technically complex for most not-for-profits to implement? Actually, not at all. While the technology underlying AI-driven tools is very sophisticated, implementing these tools is simple and well within reach even for small organisations. In this article, we look at three easy ways to get started with AI for fundraising.

Converting More Monthly Givers

Growing a sustainable monthly giving program is a key strategy for many organisations. But finding and converting these regular donors isn’t easy. The cost to acquire and retain new monthly donors is significant, often hundreds of dollars per donor, and the risk that the new supporter with churn is high.

So how can AI – or specifically machine learning – help? Most charities aiming to grow monthly giving already have a solid base of supporters that participate in other programs like annual giving, volunteering or events. These supporters have a connection with your cause and have sometimes already made financial contributions, which makes them excellent prospects for conversion to monthly giving – if you know where to look.

Machine learning (a subfield of AI) solutions like Dataro allow you to use sophisticated predictive modelling to determine how likely these supporters are to convert. Using these predictive models, you can design a conversion program targeted towards the best prospects, allowing you to maximise monthly giving while keeping acquisition costs to a minimum. 

Increasing cash giving

Appeals are still the cornerstone of many fundraising programs. But charities often run them inefficiently by targeting the wrong supporters with the wrong ask amounts. Predictive modelling drives better cash giving programs in a variety of ways, including:

• Finding additional donors for each appeal that are more likely to give
• Optimising ask amounts for a better overall return
• Identifying donors more likely to give large gifts so you can ‘upgrade’ their ask
• Predicting the best channel to use to contact each individual for higher response rates
• Identifying donors more likely to convert into mid-level and major giving programs, so you can place them on appropriate stewardship pathways

Charities that understand which donors are the most likely to take each action can communicate better with their supporters. This better communication leads to more gifts.

Reducing wasted expenses & saving time

Most charities still rely on an  inefficient ‘shotgun’ approach to donor engagement. This strategy involves sending communications to as many people as possible to avoid missing out on potential gifts. But it results in a large amount of money wasted on mail, emails and calls to people who have practically no likelihood of responding, as well as a risk of alienating supporters by asking for too much too often.

AI-driven donor scoring leads to better personalisation. Critically, this reduces wasted costs especially on mail and telemarketing efforts with little chance of success. In addition, limitations in current software means fundraisers are forced to spend hours – in some cases days – figuring out  which supporters to include in which campaigns. AI allows these tasks  to be automated and to be better targeted. Fundraisers are then free to focus on strategic and creative tasks, rather than mechanical ones like building lists. In this case, AI-driven tools lead to increased efficiency for fundraising teams, by knowing who to contact and when, as well as increased  returns through less wasted expenditure in mail, telemarketing and email programs.