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Using Database Models to Grow Your Donor Base
By Dub Williams, Vice President, List Brokerage
Belardi/Ostroy

Nonprofit organizations are increasingly faced with rising acquisition costs, softening acquisition response rates and fewer prospective donors to recruit. One way to overcome these problems is to use database models, which allow you to tap into large databases and access a new universe of names for more targeted direct mail marketing.

And, at the same time, your organization can receive valuable information about your donors – modeling companies often supply reports with detailed information about existing donors’ giving and consumer transactional history.

How it Works
To build a model, your organization supplies its list of donor names, including every donor’s full giving history. The donor names are matched against names on the modeling company’s own database in order to build a robust donor profile which includes demographic and other transactional data.

Modeling companies build their own databases through partnerships with many other for-profit and nonprofit companies and organizations, including some of the largest retailers and nonprofit organizations worldwide. The model is strengthened by each additional transaction it adds to an individual’s record.

Types of Databases
There are many types of models that can be built, and there are many different kinds of databases to model:

• Coop nonprofit databases - the mailer must be a nonprofit and is required to join and supply names into the cooperative in order to use the model.
• Consumer-based databases - include catalog buyers, retail buyers and subscribers to publications, as well as various nonprofits.
• Household databases - have demographic, lifestyle and response information from numerous sources of marketing and promotions.

Types of Models
The most common model is the donor profile/response model for new sources of names. Names that the organization provides are matched and then tagged with a wealth of information, such as: donor history to other organizations, categories of these organizations, gift amounts and giving frequency. Additional information including demographic, lifestyle and consumer purchasing history are also tagged to the name.

This information is then analyzed to find the people most like an organization’s existing donors and those that are most likely to give to a request for donations. The names are put into categories and ranked to indicate most likely responders. These rankings allow for more targeted universes to test in acquisition mailings.

Another type of model looks at an organization’s own in-house names for new donor sources. Many organizations have in-house lapsed and prospect names (such as volunteers, grateful patients and memorial donors) available to mail. These names can be modeled, tagged and ranked to find the most responsive segments of each group; this often becomes a cost-saving way of mailing fewer in-house names while maximizing response and revenue.

Results
Results from these models tend to be significantly higher than general database names and can increase in-house list performance by as much as 50%. Most important, as the list market shrinks, the universe from the models and in-house list segments allows an organization to find new sources of highly responsive names.