You can tell a lot about your donors by looking through information points such as past donation history, biographical facts, and interactions with your organization. Reviewing how much a donor has given you, time of last gift, and how many times they have donated – also known as RFM history – is probably the first stop for any fundraiser to help decide which prospects to contact, with what message, and with which ask amount.

Using this information is a safe and easy way to help plan your next campaigns. But what if you want to learn more? This is where the right data and analytics can help fundraisers become smarter with targeting and drive more efficient fundraising efforts.

Let’s look at a few examples to see how analytics can help inform your contact strategy:

Hello to Hillary.

She lives across town in a nice neighborhood and is married with two children. Her donation history seems fairly involved with two gifts over a five year span of $550 each to your main annual fund campaign. This would determine she is a good target for your next year end mail campaign. But let’s look a little further…

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With some additional wealth data research you find out her husband owns an investment business downtown, and between the two of them they hold over $3 million in real estate assets. Looking at giving to other charities you then find out that she and her husband have collectively donated over $50,000 each to their university and other organizations around the country. Applying enhanced wealth and philanthropy scoring she returns a Major Gift Likelihood score of 950 out of 1,000, and her targeted ask amount rating shows a range of $10,000 – $25,000. Her Echelon Power Segment confirms this target by placing her in the first group, identified as Ultra-Affluent Golden Years with income above $200,000 a year.

With this new information, would you still keep her in your annual fund direct mail campaign? Or would you invite her to a behind-the-scenes event for local VIPs? She is currently unassigned for a major giving portfolio, should she move over?

Announcing Anita.

This is a very loyal donor to your organization with a combined giving of over $7,000 and lives in the next town over. Most likely she is already on your radar and has been in communication with one of your Major Gift Officers. She is in your portfolio with a targeted next ask of $5,000 to follow her current giving levels. Sounds like a sure deal, right?

The first review of new data looks at conformed assets to infer overall wealth, namely real estate holdings. Her current donor profile shows her address in the next town, but with the screening you learn she actually has another home in the upstate, and a vacation home in Utah. Combined, her real estate holdings total over $6 million in value.

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Next, we add modeling with wealth information and ranking against your donor files. The model determines she is in the second highest tier, which means she could have the capacity for a $250,000 gift. While wealth indicators show ability, looking at giving to other organizations shows propensity to give again. A search through a collection of public giving data shows that she has been donating to large healthcare research charities with gifts greater than $10,000 each. This new information determines that maybe the Major Gift Officer should be increasing the planned next ask amount as well as increasing the amount of stewardship through the year.

You may still be interested in learning more. An internet search returns a recent award where she was promoted as one of the top leaders in her industry. Within that article she talks about her passion for charities. Clearly, you now know she is highly philanthropic. To complete the research lets also run a Planned Giving Likelihood score. This review ranks her as a “very good” prospect across all age groups. Perhaps it is now time to expand some of the conversations when she attends your next event?

Meet Mike.

In the previous examples, we were able to find some extraordinary major gift prospects. But analytics does not have to be reserved just for six figure gifts. Take for example, Mike. He has been a constant supporter for your organization with seven gifts over the last three years combined totaling about $1,000, and the most recent gift of $25 was from an email appeal. Advanced analytics can also help you manage annual fund and direct response campaigns.

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His Loyalty Insight report puts him in the “Habitually Generous” group which means he gives frequently to you and other organizations. With a little more research you then learn he has given over $2,000 to a private school in another state.

Combining this information then provides better segmentation criteria for your next annual fund campaign.  While you may not double his giving immediately, you can safely decide to move him to a higher direct mail package treatment and stewardship track. Knowing his giving history, you can tailor the ask strings to focus on upgrading instead of just renewing at the level of the most recent gift. Keeping him engaged now will help move him up the giving ladder later on.

Knowing Neighbors:

While giving history alone can help direct strategies, having actionable data and better insights into giving propensity and capacity can create a deeper understanding of donors for smarter fundraising campaigns. Finding wealth and asset information drives the ability to tailor asks so that you know you are not asking too much – or too little – from your constituents. Comparing giving patterns between your own organization and other charities helps you to find your most loyal supporters for further stewardship and donors with a probability of increasing commitments.  Modeling and scoring bring it all together and help streamline your segmentation process so that you have more time to focus on more impactful donor interactions. 

While the names of the donors and organizations have been removed to protect privacy, these are real life examples of the information found through Target Analytics data modeling and appends.


John Wilburn is currently a marketing manager for Target Analytics. In his prior career he managed direct response programs for a variety of nonprofits, resulting in countless donors and dollars going to fund some incredible missions.

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