The Wilderness Society almost double their regular giving conversion response rate with AI
Katrina – 12 May 2022
Using Dataro’s AI-powered propensity modelling, the Wilderness Society implemented a monthly Regular Giving calling campaign and almost doubled their baseline conversion response rate. By calling existing cash donors with the highest likelihood to convert to regular giving, the Wilderness Society team were able to convert 48 new regular givers over 5 months with an ROI of 2.2. Assuming each regular donor gives a further 18 monthly gifts, the calling campaign will raise an estimated $14,172 in net income in monthly gifts, with a cost per acquisition of $137.
- Increased regular giving conversion response rate from 6% to 11% on average
- Estimated campaign return $14,172 over 18 months
- Estimated campaign ROI 2.2
- $137 cost per acquisition
How we did it
Dataro’s Convert to Regular Giving propensity model was implemented directly within the Wilderness Society’s Blackbaud CRM.
Using machine learning, the Dataro model generated propensity scores for all of the Wilderness Society’s active cash donors, providing a prediction of how likely each donor would be to convert their occasional giving to a regular donation, if asked. These scores were then seamlessly integrated into the Wilderness Society’s CRM against the donor record both as a percentage and rank.
The Wilderness Society team set up a monthly query in their CRM to pull a list of the top 250 donors with the highest RG Convert Scores.
Armed with the list of donors with the highest likelihood of becoming a regular giver, the internal Supporter Engagement specialists implemented a monthly RG Conversion calling campaign*. The objective of the call was to thank donors for their existing support, share the impact of their previous donations and present them with a new opportunity to give in an even more meaningful way – by signing up to become a regular giver.
*The organisation previously ran a regular giving calling campaign every six months.
Analysing the Results
Previously the Wilderness Society ran larger regular giving conversion calling batches twice per year, making selections using the recency frequency value model. The calls were made by an external agency.
Using Dataro’s AI propensity model, the Wilderness Society Supporter Engagement team were able to accurately identify which cash donors would likely respond to a regular giving ask, moving to calling smaller lists more regularly. Calling the right donors each month, with the right message of thanks and a well-framed request for further support, the new internal calling team successfully converted 11% of donors called – almost double their typical calling campaign response rate of 6%.
The team also reported having quality conversations with all donors called, improving donor engagement in the process.
Converting more regular givers
Four months after the regular giving convert calling campaign was implemented, we saw:
- Dataro’s predictions were accurate, almost doubling the standard regular giving call conversion rate.
- Based on Dataro’s predictions, the Wilderness Society are estimated to generate $14,172 over the next 18 months by converting the right donors.
- Improved donor engagement, regardless of conversion result.
Nonprofits using AI to identify their most likely regular givers can improve their calling campaign conversion rates and lower their cost per acquisition. That’s because they are calling only those most likely to respond to a regular giving ask.
Charities not using machine learning are at risk of wasting time and money, calling donors who are not likely to become a regular giver and potentially not calling donors who would have converted. That means money for their cause is being left on the table.
Also, regular givers typically continue their giving for more than two years and the LTV of a regular giver is higher than that of one-time donors. Cash donors who convert to regular givers typically also continue their cash giving and have lower churn rates, so these donors are among the most valuable to nonprofits.
What they said
“It's much easier and more cost effective to convert existing cash donors to regular givers than it is to attract new donors. With the help of Dataro's AI software each month we can predict which of our existing cash donors are likely to respond to a regular giving ask from us at that particular point in time. By targeting the right people, at the right time, we've been able to more than double the conversion rate we’ve achieved previously. We’re thrilled with the results. ”
Supporter Care Manager
More Case Studies
The Fred Hollows Foundation NZ saved an estimated 211 regular givers from churning over a 7 month period, using Dataro’s AI prediction software and a well-timed intervention thank you calling campaign. With Dataro’s AI-powered donor churn propensity scores implemented directly into their CRM, The Foundation were able toRead more
Dataro recently joined forces with the team at Prostate Cancer UK to test how AI predictive modelling would perform against traditional list selection methods in an Autumn Appeal. The results showed that Dataro’s selections increased revenue by over £11,000 and attracted more than 440 new gifts that otherwiseRead more
Parkinson’s UK increased revenue in its September Appeal by over £15,000 using AI-driven supporter predictions. In a pivot from the charity’s existing propensity model, the research and support organisation introduced Dataro’s appeal predictions to attract 411 new gifts that otherwise would have been missed, raising critical funds forRead more
Victor Chang Cardiac Research Institute saved an estimated 296 donors from churning over 3 months using Dataro’s software. With Dataro’s AI-powered donor scores, VCCRI was able to identify which regular givers were most ‘at risk’ of churn and funnel them into a rolling fortnightly telemarketing program to thankRead more