Targeting Chronic, Lost Non-Responding Donors

October 18, 2016       Rick Witt      

Fundraisers are continually optimizing their marketing efforts for better response and improved return on investment (ROI). A crucial part of this effort involves evaluating the non-responsive names on a house file or an outside lists, and determining when to stop promoting to them.

These Chronic Non-Responders (CNRs) might have given once long ago, or never given, yet made it onto a prospect list for any number of reasons.

Non-responsive is, of course, a subjective description based on variables unique to each organization. For most nonprofits, a CNR typically hasn’t donated after receiving multiple appeals during 12 or 24 months or perhaps some other time period unique to the organization’s fundraising strategy.

CNRs are also found in large numbers on suppression lists supplied by outside service providers. When deciding who to mail, fundraisers compare their own or an outside CNR list with a proposed mail file. Any names found on both files are suppressed from the final mailing.

Fundraisers who omit CNRs from their mailings assume they are eliminating those who are highly unlikely to give, thus improving overall response rates and ROI. However, this approach can have its drawbacks. By cutting CNRs from the mail files, fundraisers might be creating a self-fulfilling prophecy — donors who never give because they are no longer asked to give.

There is another problem: Using a CNR file from an outside provider might seem like a reasonable tactic, but doing so means relying on a limited subset of information about the individual prospect. This potentially overlooks subtleties hidden in additional available data about their donation and transaction behavior. This limited data keeps ever more prospects out of consideration because CNR lists grow larger over time.

Suppressing a CNR file does not account for the fact that prospective donors are not static. People change. When a significant life event (a birth, a death in the family, retirement, an inheritance, a medical diagnosis, etc.) or a change in income occurs, a prospective donor on a CNR list might eventually have new motivation and capacity to give. As such, it is important not to freeze CNRs in time, but rather have the ability to analyze additional data about their evolving purchasing and donation behavior.

It is also important to remember that just because a CNR hasn’t donated to one organization does not necessarily mean the donor hasn’t given to similar nonprofits. If fundraisers rely solely on their own CNR file or a single list from another organization, they are only seeing a part of a much larger picture.

But if donor profiles are modeled on the basis of multiple data sources, a clearer picture emerges of their capacity and likelihood to give. That, in turn, informs decisions about frequency, ask amount and creative treatment.

So how can fundraisers make sure they are not suppressing potentially valuable donors currently regarded as CNRs? The solution is to gain access to more robust, detailed data — a modeled list produced by analyzing multiple data points, which sometimes can produce curious, unexpected correlations.

By analyzing an individual’s total donation history and consumer behavior, it is possible to identify CNRs who are likely to respond to an appeal, and even become long-term value donors. This kind of donor modeling can also identify the channels — direct mail, email, digital display — in which CNRs are most likely to respond. A CNR when it comes to direct mail, for example, might turn out to be a CDR or Chronic Digital Responder.

The more data that fundraisers have for evaluating CNRs, the better they can determine who can be expected to donate in the future.

The first step to validating potential pockets of responsive donors within a CNR file is to test the names that appear to be the most promising. If CNRs who score high on a modeled list produce good results in a test, the model is likely to produce many more good prospects worth pursuing. If they score lower in the model or in a test mailing, it confirms suspicions that the targets were not a good match.

Test-mailing a CNR list will require a statistically valid sample. There is no right or wrong number here, but if the goal is a minimum of 100 responders at a response rate of 1 percent, it will require testing at least 10,000 names.
In determining how to treat CNRs, a rigorous, data-driven approach will yield the best of both worlds: identifying good opportunities from among previously unresponsive names, and removing the truly unresponsive ones.

In other words, when it comes to CNRs, fundraisers can know with confidence when to hold ’em…and when to fold ’em.
* * *
Rick Witt is senior vice president of client services at Wiland, a marketing intelligence and data-driven fundraising solutions provider. His email is rwitt@wiland.com