November 21, 2024
AI Can Be Your Most Powerful Tool for Growing Midlevel Giving
Tips and best practices for building a reliable and efficient task management process.
As a not-for-profit aeromedical organization, Royal Flying Doctors Service Victoria rely on the help and generosity of the community to deliver essential health and emergency medical services.
While every donor has played an important role in keeping the Flying Doctor flying during a challenging few years, the growth of their major donor program has been central to the charity expanding their reach and impact.
Before partnering with Dataro to help build their major donor pipeline, the charity conducted triennial wealth scans and gift searches with partner agencies. This helped to establish a qualified pool of major donor prospects already existing in their donor database.
When the charity partnered with Dataro in 2021 the goal was to use machine learning (AI software) to:
1) confirm the capacity of their existing major donor prospects
2) prioritise which donors to steward for the best results
Dataro’s major donor predictions are now an integral part of RFDS Vic’s major donor prospecting and stewardship process. In the last year they have grown major gift revenue in excess of 15%.
Dataro has a strong track record when it comes to helping nonprofits improve their major donor prospect research, helping them to prioritise their existing prospect list and find new prospects in their database for stewarding.
In this case, Dataro’s Major Donor propensity model was implemented directly within the charity’s Blackbaud’s Raiser’s Edge NXT CRM. Using machine learning, Dataro’s software generated propensity scores for all of RFDS Vic’s active cash donors, providing a prediction of how likely each donor would be to give >$10,000 in cumulative gifts in the next 12 months if stewarded effectively.
Dataro’s predictions were seamlessly integrated into the charity’s CRM against the donor record as a percentage and rank and updated weekly.
RFDS Vic initially ran some tests, comparing their existing major donor pipeline list against Dataro’s list of donors likely to give a major gift. The test confirmed that Dataro had accurately predicted which of the charity’s existing cash donors had capacity to become major donors and identified additional prospects.
Using Dataro’s major donor ranks, the charity’s data team created their own internal ranking system to group top prospects into four categories:
A = Dataro major donor rank 1 – 100
B = Dataro major donor rank 101 – 300
C = Dataro major donor rank 301 – 600
D = Dataro major donor rank 601 +
Further categorising the top ranked donors would help the philanthropy team to easily prioritise their prospect research and stewardship efforts.
Supporters with an A or B internal Dataro ranking were easily identified and understood to be the most likely prospects yet donors with a C and D rank would not be neglected in stewardship efforts either.
The charity then allocated their major donors and prospects (A, B, C, D) into one of three stewardship categories: Build, Monitor, Maintain. This allocation process is re-done annually and relies on the judgement of the philanthropy manager who decides which donors to build and monitor. If a donor’s giving changes, they are recategorised.
Dataro’s AI-powered major donor predictions have helped RFDS Vic to confirm the capacity of major donors in their existing prospect list plus find new prospects in their database to add into the major donor pipeline. By confirming a prospects capacity it has given the RFDS Vic team confidence to continue building relationships with their top ranked major donors.
Dataro’s major donor predictions have helped RFDS Vic to grow their major gift revenue by +15% in the last year by finding more major donor prospects and reconfirming existing major donor prospects in their database.
Most importantly Dataro’s predictions have helped the charity to find the top priority prospects for further research and stewardship. This has enabled time savings and ensured the efforts of the team are directed to the most likely prospects.
With Dataro’s Stewardship Propensity Model, philanthropy teams can use machine learning to analyse their donor database and reliably identify their best major donor prospects. By regularly scanning their donor database using Dataro’s major donor ranks and scores, nonprofits can:
With prediction-based targeting Dataro will help you build a better major donor pipeline with less effort and higher returns.
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Philanthropy Manager
Dataro’s AI donor predictions has made our major donor prospect research and stewardship process far more robust! Dataro’s major donor ranks and scores help us prioritise our prospect list. It has confirmed which donors we thought had capacity and that what we are doing to identify and steward people is working.
Naomi Lehrer
Philanthropy Manager
Royal Flying Doctor Service Victoria