Wealth screening data gets a lot of attention and usage from nonprofits looking for a quick way to identify people more likely to make a major gift.
But how well does it really work?
Any gift officer will be able to rattle off stories about terrible leads that were added to their caseloads who had no desire or capacity to make a major gift, let alone any gift at all. They give off the “Why are you calling me?” vibe. Not exactly a response that makes the gift officer feel good about their job.
So how does this happen, and what role does wealth screening data play? Let’s dive in and see what wealth screening is, how it works, and why it so often generates terrible leads, in addition to the occasional success story.
Wealth screening attempts to determine the capacity to give a major gift.
Wealth screeners use a variety of data sources – not all of them of high quality – in an attempt to build a profile about high net worth individuals so that when nonprofits come to them for help, they can match up their data with the lists of names given to them by the organization.
Within those lists, the wealth screener looks for individuals already within the organization’s database who also appear to possess a high wealth capacity. Those people are filtered out and recommended for addition to the caseloads of the gift officers.
In addition, wealth screeners can find new potential donors not on the organization’s existing lists based on pre-written donor profiles.
Wealth screening sometimes gets used after an RFM analysis has first been performed. RFM looks at the past behaviors of a donor. It finds donors who have recently given a gift, give gifts frequently, and have given at a high monetary value. Recency, frequency, and monetary value.
The problem with RFM is that it only looks at past behavior. This means it can’t account for things like one-time surges in wealth such as a signing bonus or a mid-sized inheritance. Such an event may trigger a large donation, which will suggest a large ‘M’ value in the RFM analysis. But that one-time event won’t get repeated, and RFM has no way to catch this discrepancy.
Wealth screeners, in theory, can come in after the RFM and confirm that the donor who gave the large gift actually does have capacity to give such a gift again. Wealth screening data can ensure this donor’s gift wasn’t a flash in the pan.
Wealth screeners and some nonprofits focus too much on this question, believing that some data sources are of higher quality than others. While that may be true, here’s the bigger issue: Even the sources with “high” quality data are extremely limited.
So, your choices, if we’re honest, are between bad, weak, and so-so. There is no “good” wealth screening data when it comes to the purposes for which organizations seek it – identifying a consistently accurate crop of qualified major gifts donors.
For that, quantitative data simply can’t deliver on its own. You need qualitative data too, which we’ll say more about later.
All this said, let’s talk about the sources of wealth screening data for a bit.
Most of this data comes from publicly available sources, such as SEC filings, corporate websites, property records, tax assessors, employment history, and alumni data.
Various companies that sell wealth screening data will acquire their data from different sources.
One such source is Thomas Reuters, which collects data on the activities of high net worth individuals and families, and keeps track of their employment status, educational attainment, and location.
Another source, CoreLogic, tracks real estate data including tax assessments, property records, property value, and parcel maps. The idea here is to find wealthy people – including their addresses and other contact information – and use their property as one basis for determining capacity to give.
Other wealth screening data might track political contributions, stock holdings, businesses ownership, board memberships, and other affiliations typical of people who have wealth.
The sales pitch to nonprofits for buying wealth screening data is simple:
You can do it all from your basement without having to actually talk to anyone.
Like, say, a prospective donor.
Conversations are messy and unpredictable. Relationships are hard to develop and they take time. Just being handed a bunch of names is far less work. Plus, wealth screening data looks great on PowerPoint slides and is really easy to present.
Quantitative data like this can be obtained very easily. You just pay the company some money, send them your database information or a profile of what you believe to be your ideal donor, and they match up your information with theirs and send you a list of potential major donors.
What could be easier?
Actually, not much. It is really easy, and that’s the primary appeal of wealth screening. With very little effort, you find yourself in possession of a list of names. And at first glance, it looks like a big huge pile of money just waiting to be tapped.
But is it?
“Imagine,” a board member or nonprofit administrator might say, “if we could average just $10,000 from each person on this list, how much money could this mean for our organization?”
With that, and probably some additional pep talks, the newly screened lists are handed over to gift officers by salivating administrators, filled with hope and expectation that huge buckets of money will begin pouring in within some pre-determined time frame.
Meanwhile, the gift officer looks at the list and goes, “Uh… What am I supposed to do with this?”
The bigger the list, the longer the ‘uhhhhhh.’
Well, where do you start? Suppose you get a list of wealth screened donor prospects with 50 names on it. 50 names! Which one do you contact first? How should you contact them? What happens if they don’t respond? What happens if they do respond but not in the way you expected or hoped? How long should you keep trying to reach them? What about the other 49 names?
Had this donor been pre-qualified using more effective means, using qualitative data, the gift officer would be able to approach these conversations with far, far more confidence. They could create an actual plan, customized for each prospect, for how to reach out and what to say, because they will know each person’s interests, passions, relationship to your organization, openness to talking, and so much more.
Qualitative data makes that possible. Quantitative data cannot ever make that possible.
We could spend a lot of time on this, but let’s boil this down to two primary problems.
Problem 1 – Untrustworthy Data
The biggest problem with every form of quantitative data about people is that it can only look to the past.
Suppose one donor in a batch of wealth screening data possesses a $2 million residence and earns a mid-six figure salary.
What if that donor is getting divorced soon and will have to split their assets, pay for the divorce, and have their household income slashed? That’s not to mention the emotional state of the person. Would you feel like giving away huge chunks of money while going through a divorce?
What if that person is about to retire and have their income reduced to almost nothing?
What if their income comes from a business that is starting to struggle?
What if one of their parents needs full-time care?
What if the $2 million residence represents nearly all their net worth? The data might say they have a $2.5 million net worth, but with 80% of that wrapped up in their home, that figure is extremely misleading, to put it mildly.
No matter how much the wealth screening company might tout the “high quality” of their data, they can’t ever overcome these limitations on reliability. Ever. That’s why we said earlier that the best wealth screening data can only have so-so quality. It simply can’t tell you what it doesn’t know, and it can’t know these sorts of things.
Beyond all this, oftentimes the data is just wrong. It’s old. Data mining companies must constantly battle to keep their data updated, and it’s a Herculean task. Too often, wealth screening data just isn’t accurate, but you have no way of knowing whose data is accurate, and whose isn’t.
Problem 2 – Too Many Unanswered Questions
This goes hand in hand with untrustworthiness. No matter what data gets delivered to you, any thinking person will look at it and begin to ask a bunch of questions they can’t get answered.
Suppose the data says one person has donated $250,000 to political causes of a particular slant. If your organization’s mission aligns with their political leanings, does that make them more likely to donate to you? Well, compared to someone with opposite political beliefs, yes. But so what? How many issues could be important to someone who leans a particular way politically? Dozens!
A person who gives to climate change causes might not be interested in giving to social justice causes.
A person who gives to help veterans might not be interested in gun rights.
But this is the kind of data wealth screeners send you. You just don’t know enough about these people to really know what to do with this information. You need more.
The even bigger unanswered question is, what if the wealth capacity reported by the screening data is below the real figure? Some wealthy people have learned how to conceal their true net worth. Many wealthy people confine most of their net worth in assets, not bank accounts.
Donating assets, or working with the donor such that part of the value of those assets can be donated, requires extra work on their part and on your part. Wouldn’t it be preferable to know the status of their net worth before talking to them, rather than just a raw figure?
They could have much of their wealth in a private trust, for them or for their spouse. They might have inherited a very large sum, but in assets not cash, such as a retirement account.
Qualitative data can reveal these details before you talk to the prospect, so you don’t go into the conversation feeling like a salesperson, instead of a guide or a friend.
There are a few good ways to use wealth screening data, so hopefully that hasn’t been lost on you in reading this article. The main point for today is that you should not be exclusively relying on wealth screening data to identify and qualify major gifts prospects.
If you begin with qualitative data, sometimes it can be useful to take what the qualitative data reveals and add to that the wealth screening data.
So, how do you obtain this much more valuable qualitative data?
How do you learn things like the donor’s interests, values, or perspective on your organization? How do you find out how the donor learned about you, why they care, their true current financial status, their true willingness and ability to give, and other information like this?
The best way, and in our experience the only way, to acquire this is with consistent, non-pushy, automated communication. This is what MarketSmart’s software does. It’s why we exist. We want to help nonprofits win more major gifts, but with less work and lower stress for your gift officers.
Our track record speaks for itself, and it’s why we have a growing community of raving fans, as well as a 10:1 ROI Guarantee that we offer to every new customer. You read that correctly – a 10 to 1 ROI. You will make at least ten times what your organization spends on our software – we guarantee it.
Would you like to see how we do it?
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