# Nothing entered, something gained - Link: https://fundraising.co.uk/1999/02/11/nothing-entered-something-gained/ - Published: 1999-02-11T00:00:00+00:00 - Author: Guest Blogger **What do you do when you are missing data for your fundraising appeal? Peter Wylie sees missing data as an opportunity and not the drawback that you might think.** **Author: Peter Wylie** If you’re not involved in direct marketing/appealing, what I have to say here may put you right to sleep. But if you ARE involved, I may have a little pick-me up for you. It has to do with the whole issue of missing data. ## Advertisement Now I’ve been playing around with databases on and off for more than 30 years. And for the lion’s share of those three decades missing data has been a pain in the butt for me. An example. Say you’re a fund raiser with a database of 150,000 actual and prospective donors. You don’t have a whole lot of information on these folks, so you send your entire list of names to a third party list enhancer (like Polk Direct or Donnelley or Dun’s Marketing Database) to see if you can get info on their ages, income, likelihood of giving to charitable causes, and so on. They send you back the enhancement of your names on a zip disk or a CD. But when you take a look at all the fields they’ve added, you find a lot of those field are less than fully “populated.” Only 40% may have an age estimate. Only 60% may have an income estimate. And more than 20% may have nothing at all in any of the fields. A big pain, right? Not necessarily. What I’ve been finding over the last several years is that “missing data” in ANY field in a database is often an excellent predictor of purchasing behavior, giving behavior, and “staying” (retention) behavior. Some compelling examples: a. In a construction industry trade association interested in predicting member retention, I found that members who had an entry for SIZE OF COMPANY were half as likely to drop out as members with no entry: 12% versus 24%. The difference was even greater for members with E-MAIL entered versus those without it entered: 4% versus 21%. b. In an educational foundation I found that prospective donors who had given at least once in five years were four times as likely as non-donors (44% versus 11%) to have some entry for AGE. c. In a professional association whose members had the option of participating in an insurance program, missing data in the AGE field was even more telling than in the above example. Fifty-seven percent of the participators had some entry for AGE while only 2% of the non-participators had any entry at all in this field. ( What was even more striking to me is that the association had no knowledge of this difference and, of course, completely ignored it in their aggressive direct marketing campaign to sign people up for the insurance program.) d. In another trade association that sold lots of different products to both members and non-members, missing data in the field PREFIX was very predictive of how much people bought. For people who had an entry in that field the average amount purchased was $63. For people with no entry in the field the average amount was $23. Well, if you’re at all like most of my clients, your natural inclination is to ask:“ But why? Why is the lack of data in these fields so strongly related to buying or giving or retention?” It’s an intriguing question, no doubt about it. Maybe it’s something as simple as the fact that committed buyers, donors, or members are more likely to fill out forms whose information is then put into databases. I don’t know. But from the standpoint of your role as direct marketer/appealer, IT DOESN’T MATTER. Now maybe that’s not a very intellectually curious attitude on my part. But I’m sure of myself on this point. What matters is not WHY this relationship between missing data and spending behavior exists. What matters is that it DOES exist. Because you can use that relationship to save lots of money and generate more revenue. And how do you do that? The details can get a little complicated because database management for direct marketers/appealers is still in its infancy. But here are some suggestions: 1. Get someone on your staff to go through your customer/donor/member database and FORAGE for relationships between missing data in ANY field and buying/giving/retention behavior. (If you don’t have someone on staff capable of doing that, hire a consultant who can teach you how. Their fee will be chicken feed compared to what you can save and make on your direct market bottom line over the next several years.) 2. Develop a missing data “score” for everybody in your database based on those fields that show a strong relationship with buying/giving/retention. 3. Immediately start testing the effectiveness of this scoring system in your next available direct mail promotion/campaign. Do an analysis of the return rates you get by the various levels of missing data scores. If the people with higher scores are buying less, giving less, or sticking around less, build those scores into your marketing/appealing database. Mail more and more often to the people with low scores, and less and less often to the people with high scores. You’ll save hugely on mailing costs, and (depending on your goals) you’ll sell more product or bring in more donations or hang on to customers/members longer. --- **Peter Wylie holds a doctorate in industrial psychology from Columbia University. He is an expert on how non-profit organizations can do a far more efficient job of fund raising by carefully mining their donor databases. His business phone is( 202)332-7571; his e-mail address is [pb\*\*\*\*\*\*\*\*@\*ol.com](https://www.fundraising.co.uk/pbradwylie@aol.com)** ## More posts by Peter Wylie * **[Are donor dollars related to how long their names are?](https://fundraising.co.uk/2000/09/01/are-donor-dollars-related-how-long-their-names-are/)( 1 September 2000)** * **[Using your database to find major donors](https://fundraising.co.uk/2002/01/15/using-your-database-find-major-donors/)( 15 January 2002)** ## Books by Peter Wylie * [**Baseball, Fundraising and the 80/20 rule: studies in data mining**](https://fundraising.co.uk/books/baseball-fundraising-and-the-8020-rule-studies-in-data-mining/) * [**Data Mining for Fund Raisers**](https://fundraising.co.uk/books/data-mining-fund-raisers/)