Rental List Donor Acquisition Case Study: Compiled Lists vs. Managed Lists
What Kind of Rental List Works Best for Donor Acquisition?
We wrote, designed, printed and mailed three acquisition mailings for a conservation society, using two different rental lists.
One was a list of consumer households modeled for propensity to give to an environmental cause. The list was pulled from the top 10% of the propensity-to-give ranking.
The other list was recent donors to a similar nonprofit, National Audubon.
The recent National Audubon donor list outperformed the consumer propensity-to-give list by more than 10 times in response rate and nearly 18 times in dollars raised.
And when those who didn’t respond the first time were mailed again, the response rate was still nearly 10 times higher, and dollars raised were more than 8 times higher than the consumer propensity-to-give list.
The conclusion, and it is consistent with my past experience, is that a donor list rented from a similar nonprofit is likely to outperform a consumer list, no matter how well modeled.
What Are These Two Types of Rental Lists?
Compiled Lists
- While such compiled lists are useful for marketing consumer goods and services, they work best for a geographical focus around a well-known organization, such as a local hospital, Visiting Nurse Association, or Humane Society. Those local consumers usually know the brand. They often know people or relatives who have used the services or they have used the services themselves. They likely already know, understand, and believe in the mission. This awareness is important. I have had success with compiled lists in these situations.
- It is possible to select for income levels, home ownership, presence of children, etc. Keep in mind that this information is often decided by the operation of an algorithm. Presence of children might be inferred from the purchase of children’s clothing or toys, etc.
- They also use all those data points to model consumers for the likelihood of becoming a donor. This may include some purchased information about consumer donations to nonprofits. They may add this as a select for a compiled list, using terms such as, “Community Involvement: Environmental”. This additional select may improve the list’s propensity-to-give accuracy.
- Data companies may also generate lookalike lists of consumers by using a nonprofit’s donor list to create a ‘lift’ model.
- This is similar to uploading a customer list to Facebook to create an Advantage+ lookalike list.
- The difference between doing this with Facebook Advantage+ and with direct mail is that Advantage+ lookalike allows Facebook to dynamically make updates to the lookalike list that reflect where they are seeing better performance.
- With direct mail you only get one chance; there is no process for dynamically improving the list.
- I’ve had success with lookalike lists in the situation under point 1 above, where the organization is local and well known.
- But to create a viable lookalike list, at least 3,000 donors need to be uploaded for the algorithm to create the model.
Managed Lists
Some nonprofits market their list through a broker who manages the rental process for them. This type of list is often called a ‘managed’ list.
These lists
cost 3 or 4 times more than a compiled list,
require minimum purchases of 5,000, 7,500, or 10,000 records,
may not have nearly enough records in your target geography for a mailing,
require advance approval of your copy and mailing date by the list owner,
and it may be hard to locate an appropriate list, because very few nonprofits market their list.
In the right situation, it is possible to get a much better response with such a list.
And that is what we found in these three tests.
Results: Propensity-to-Give Consumer List vs. Similar-Nonprofit Donor List
| Date | Rental List | Mailed | Gifts | % | Amount | Ave Gift |
| 2025 Fall | Propensity to donate to Environmental Causes, most likely top 10%, $150K+ income | 2,276 | 2 | 0.09% | $250 | $125 |
| 2025 EOY | National Audubon Enhanced, 24 Mo, $10+ Donors | 4,873 | 64 | 1.31% | $4,465 | $70 |
| 2026 Spring | National Audubon Enhanced, 24 Mo, $10+ Donors, repeat | 4,775 | 43 | 0.90% | $2,084 | $48 |
| *repeat = mailed rental list prospects in the EOY mailing who did not respond | ||||||
Mailing Format and Specifications
The mailer for both the 2025 Fall and 2025 EOY mailing was a 2-sided, 8.5 x 11 letter, with a 7.5 x 8.5 reply form, mailed in a #10 regular envelope with a #9 reply envelope.
The mailer for the 2026 Spring mailing was the same format, but with an additional 8.5 x 11, one-sided “What Your Gift Can Do” insert.
Letter writing was consistent between the three mailings. The layout of the reply card was the same for the three mailings.
They were all mailed with an affixed nonprofit-class stamp.
What Do These Results Mean for Your List Rental Strategy?
Response rates >=0.5% are considered good for direct mail rental list acquisition. The National Audubon list performed way above this benchmark for this organization, and for this letter format.
These results illustrate that donors rented from another, well-aligned nonprofit can significantly outperform compiled lists.
However, this is not a guarantee that such lists will normally deliver a response rate in the 1% range.
Other factors with strong influence on the performance include whether the nonprofit has any brand awareness with the acquisition targets, the messaging and style of the letter, the time of year, and perhaps other variables.
I have rented lists from other nonprofits that have performed well in one case but not in another case. Testing is the only way you can find out whether the list will work well for your specific situation.
When your geography is limited, for instance a town or county, it can be impossible to find a similar non-profit who rents their list and who has enough donors in your geography to make it worthwhile. That’s when a compiled consumer list is the way to go. It can work in that situation, because many residents are interested in supporting local non-profits.
Typical Sources of Consumer Information Used by Acxiom, Data Axle, and Other Data Compilers
Public Records
County and municipal data: County recorder files, property deeds, and real estate transactions.
Tax assessments: Property valuations and local tax rolls.
Government registries: Voter registration files and new business/resident filings.
Directories: White pages, yellow pages, and published telephone directories.
Proprietary and Commercial Partners
Utility connections: New hookups, disconnects, and service transfers for electricity, gas, or water.
Financial and transactional signals: Credit header data (via authorized credit bureau partnerships), payment processor insights, and banking relationships.
Consumer behavior: Catalog requests, retail purchase histories, warranty card registrations, and magazine subscriptions.
Donation records: Charitable contributions and political donation filings.
Digital and Self-Reported Sources
Online interactions: Web browsing behavior, IP addresses, location signals, and mobile device IDs.
Surveys and questionnaires: Self-reported lifestyle interests, hobbies, and warranty or sweepstakes responses.
Verification programs: Millions of outbound verification phone calls and continuous database hygiene sweeps (such as National Change of Address updates) to confirm contact accuracy.
Written by Gary Henricksen
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