Testing: Proving women are easy and cheap!

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By Kim Cubine, Managing Principal

There are more women donors than there are male donors. For years, numerous nonprofit trend watchers and independent tracking groups have confirmed this fact.

What we really don’t know is why women contribute more frequently.

• Do women give more because they are more compassionate than men?
• Do women contribute more because they like to spend money?
• Do women actually have more free time than men?
• Do women give at the same level as men?

Well, I couldn’t really answer the first three questions outside of my own personal experience. But we could definitely test the giving level between men and women with organizations to determine if there was indeed a difference.

We decided to implement a "direct mail battle of the sexes."  Using a prospect control package we set up a series of ask string tests and split the file between men and women. The test panels were established as follows:

• Women received three ask string variations:  control ask, low dollar ask, and high dollar ask.
• Men received three ask string variations: control ask, low dollar ask, and high dollar ask.

Wow - women give at a higher rate but in every case they gave at a lower gift level than the men.

As a matter of fact, for the male test segments there was no statistical difference in the control and the high dollar asking string.

For women, the opposite was true. The low dollar test segment had a 20% increase in response rate over the control panel. And the lower average gift did not have a negative impact because the investment per donor was 13% lower due to the increased percent response.

Overall, it costs this organization less to recruit women than it does to recruit men.

This test was repeated in the house files and for some organizations we have now established different gender based asking strings depending on the test results.  

So by all means, if you haven’t pitted (I mean, “tested”) women against men on your donor file, do it today! And let us know what your results are!

Contextualizing Your Data

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By Brandon Hemel, Director of Analytics

In a deep, dark corner of the Adams Hussey & Associates office sits a team of over-caffeinated data heads, who wake up way too early in the morning and speak in a strange language called SQL.

As the Director of Analytics at AH&A and leader of our nerd-herd - btw that is NOT me :) I often get this seemingly simple request: “Can you guys go into our data and see what it tells us?”

Without fail, I find that I need to do additional research to figure out not just what happened but why it happened.

So to help you in case you are ever asked that question, I’m giving you an inside look at the most vital part of data analysis and you don’t even have to go through the pain of learning Structured Query Language (SQL).

The key aspect of investigation is adding perspective and insight into your results to get the why and not just the what.

Five Handy Things to Keep Around While Doing Historical Data Investigations

Unless your members and donors live in a vacuum, outside events will impact your fund raising efforts in both good and bad ways. But when looking back at your results after five or ten years has gone by, world events blend together. I find that Wikipedia.org and Infoplease.com are extremely helpful for these needs.

Along with event timelines, consumer, government and world financial indices are great ways to compare and contrast your data against real world measures. My favorites are the Consumer Confidence Index, the Consumer Price Index and the Gross Domestic Product Index.

As Direct Marketers, we live and die by coding structure.  If your data has inaccurate source codes or you have changed the schema – let your data analyst know this ahead of time (please!).

Deep sea divers always work in teams and so should your analysts. A fresh perspective is always helpful.

Most importantly – you should always have a

To understand the framework of what it means when you see a distinct change in your data (whether it is a huge jump in revenue or a deep decline in membership), old memos, year-end reviews, or at least a person with a really good memory are invaluable when contextualizing your data.

Tell us what you think. How does your organization add perspective to your data? Data for the sake of data may be fun (!), but it won’t help your strategy or grow your organization.