Child Cancer Foundation Leverages AI Donor Insights to Reconnect with Lapsed Donors

The Child Cancer Foundation (CCF) has long been a lifeline for Kiwi children and families affected by cancer. Over the years, the organization has relied on its generous donors to fund its work supporting families with children on their cancer journey.

In 2021, staff changes left CCF with a gap in data skills and their appeal segmentation process. They temporarily outsourced their campaign targeting while rebuilding their internal data knowledge.

In 2023, CCF were ready to partner with Dataro to see if AI propensity modeling could improve their appeal targeting and help reactivate lapsed donors.

Using Dataro’s AI donor predictions, the Child Cancer Foundation NZ reactivated hundreds of long-lapsed donors in one campaign with 87% of revenue coming from the top 5,000 ranked lapsed donors.

Key results

Using Dataro’s AI donor predictions, Child Cancer Foundation:

• Saw their top 5,000 ranked donors contribute 87% of revenue from reactivated donors
• Reactivated hundreds of donors who had not been contacted for years, having fallen through the cracks of previous segmentation models

Background

With direct mail costs increasing and donors segmented differently over time, CCF noticed they were targeting fewer and fewer donors in their appeals over time. This had led to decreased response rates and reduced donor lifetime value.

Having run their own internal data analysis, the charity wanted to see if Dataro’s machine learning models could improve its campaign performance by identifying ‘ready-to-give’ donors and minimizing the accidental exclusion of potential donors.

What they tested

CCF aimed to re-engage unintentionally excluded donors and reactivate more lapsed donors while improving overall campaign engagement and donor lifetime value.

CCF developed a bespoke reactivation campaign that utilized direct mail and email to engage the large lapsed audience. This campaign excluded recent appeal recipients with messaging focused on re-engaging a long-lapsed audience.

Direct Mail Campaign:

• Designed a straightforward A5 flyer with a QR code for online donations. This flyer was cost-effective and personalized to their audience.
  

eMail Campaign:

• Extended their email reach significantly, contacting an additional 25,000 supporters. This ensured comprehensive engagement across multiple channels.
  

Recent campaign recipients were deliberately excluded from the reactivation campaign, which was tailored exclusively for long-lapsed donors.

How we did it

CCF has been working with Dataro since 2023 to improve its appeal selection process and drive better fundraising returns year on year.

In this case, Dataro’s Direct Mail propensity model was integrated with CCF’s CRM – Blackbaud Raiser’s Edge NXT.

Using machine learning, Dataro’s model predicted how likely each donor would be to donate to an appeal if asked. Dataro’s donor propensities were updated weekly in the charity’s CRM.  

Analyzing the results

The reactivation campaign reached approximately 10,000 lapsed donors via mail and 25,000 via email. Dataro’s model identified these donors as being ‘most likely to donate’.

Despite initial concerns about high direct mail return rates or low response rates, the campaign saw hundreds of long-lapsed donors reactivate.

Analysis revealed that the top 5,000 ranked donors, as identified through Dataro’s Appeal 24M Lapsed propensity, contributed 87% of revenue towards the campaign. This insight provides a strategic focus for future campaigns, ensuring resources are directed toward high-potential segments.

By targeting the right donors and opting for a simple direct mail and email approach, CCF efficiently reconnected with its ‘lost audience’ and successfully reactivated donors.