Transforming the Future of Pancreatic Cancer with AI Donor Predictions
Pancreatic Cancer UK is working to transform the future for everyone affected by pancreatic cancer. Through the generous support of their donors, they fund research breakthroughs, campaign for changes to treatment and care, and provide support to those affected by pancreatic cancer.
In 2021, Pancreatic Cancer UK partnered with Dataro to see if our AI donor predictions could improve their direct mail appeal performance and grow revenue while reducing costs and improving fundraising ROI.
In their first EOY appeal (2022) using Dataro to make their data selections, the charity achieved a 111% lift in net appeal revenue and a 142% lift in response rates, despite mailing 65% fewer donors. This translated into a direct mail cost saving of £3,899 and a campaign ROI of 268%.
Key Results
Using AI to find the best donors for their direct mail appeal, Pancreatic Cancer UK achieved:
- An increase in gross return despite mailing 65% fewer donors
- 111% lift in appeal net revenue
- 142% lift in response rate (10.2% response rate)
- £3.9 saved in direct mail costs
- 268% ROI
How we did it
Pancreatic Cancer UK has been working with Dataro since 2021 to improve their appeal selection process and drive better fundraising returns year on year.
In this case, Dataro’s Direct Mail propensity model was integrated with Pancreatic Cancer’s CRM – Blackbaud Raiser’s Edge NXT.
Using machine learning, Dataro’s model predicted how likely each active cash donor would be to donate to an appeal if asked. Dataro’s donor propensities were updated weekly in the charity’s CRM.
In addition to identifying which donors are likely to give (and which donors should be rested), Dataro’s machine learning model also provides suggestions for ideal mail file size to optimize campaign ROI.
The fundraising team used Dataro’s ranks, scores, and campaign size suggestions to make their direct mail appeal data selections.
Analyzing the results
Before using Dataro’s AI donor propensities, Pancreatic Cancer UK used to rely on segmentation methods such as RFM for their appeal targeting, which often led to missed gifts from donors and wasted outreach to supporters who were not likely to give.
After a period of testing in 2021, the charity used Dataro’s donor selections and campaign size recommendation in their 2022 EOY appeal to target a substantially smaller yet more engaged audience.
Despite sending 65% fewer letters than last year’s campaign, they increased response rates by 142%, up from 4.2% to 10.2% and increased net appeal revenue by 111%.
By mailing a smaller segment of donors the charity saved £3,899 in direct mail costs, without risking income. The increase in gross revenue and reduction in costs helped Pancreatic Cancer UK achieve an incredible campaign ROI of 268%.
Confident in their results with Dataro, Pancreatic Cancer UK prepared their data selections for the 2023 EOY appeal using Dataro’s donor predictions.
While Dataro’s donor predictions proved accurate again, the charity included additional donors outside those recommended by Dataro’s “recommended campaign size”. This resulted in a lower campaign response rate of 3% as donors with lower likelihoods of giving were included. Coupled with escalating mail costs, the 2023 EOY campaign achieved a lower campaign ROI of 72.38%. This outcome validated the reliability and effectiveness of Dataro’s predictions and campaign size recommendations.
The 2023 EOY Appeal results have given the charity confidence to rely solely on Dataro’s AI predictions and suggestions for their appeal targeting going forward.
What they said
“Dataro’s predictive models have been a game-changer for our fundraising. By leveraging their donor insights and campaign size recommendations, we’ve seen significant improvements in our direct mail appeal performance. We’re consistently raising more revenue from less outreach, which has saved us time and cost and is delivering us much higher campaign ROIs. With Dataro we know we’re engaging the right donors to support our cause.”
Katie May
Individual Giving Manager
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