Does your nonprofit client want new donors? Know the target market. Research and modeling of a charity’s contributor base identified potential new donors and successfully predicted which groups would produce the highest ROI.
The challenge to simply maintain, let alone improve, current donation levels faces every nonprofit (and their marketing agencies). Do your nonprofit clients make full use of their current supporters’ data to identify new potential donors? Donor analytics should be an integral component of any acquisition campaign. Analyzing and modeling even bare bones data is as important to a successful acquisition push as the campaign’s messages, creative, and how it’s pushed out.
When the Canadian Breast Cancer Foundation decided to embark on an acquisition campaign, they knew that a “spray ‘n pray” approach would waste precious resources. They started by investing in an analysis of their current donors’ data. Donor profiles were sifted for past and present donation status, what appeals they had responded to, and their different attributes. For example, one group of donors might be male, over 45, married with at least one daughter, have an average income of $60,000, live near the financial district of their city, and enjoy sports.
Canada Post’s Data and Targeting team and the Foundation’s Direct Response department worked together to:
- Examine the donation history of existing donors and produce a profile of common donor attributes.
- Analyze and assign a weight to each attribute and apply a geographic overlay.
- Give each postal code a score based on these donor attributes.
- Divide postal codes into 10 groups, based on how well they matched donor attributes.
The foundation used its predictive targeting model with rented lists and sent out 125,000 Addressed Admail™ pieces. “Revenue per thousand donors was 47 per cent higher for the top two deciles versus the bottom four deciles,” says Kersti Kahar, Senior Manager, Direct Response, of the Canadian Breast Cancer Foundation. “Canada Post’s Analytic Essentials have been invaluable. Now we have a better idea where we should target our future acquisition campaigns for optimal results.”
Use data mining to create predictive models that improve the ROI of a current acquisition campaign. This approach also keeps future acquisition costs down, as efforts can be directed at targets that analysis predicts are most likely to respond to your client’s appeals.
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