I heard a great prospecting success story the other day and I thought I would share it. Now, this story has nothing to do with how likely someone may look to make a gift, what their past giving or relationship to you might be, or even what someone or something has calculated a prospect’s capacity to be. This story has everything to do with leveraging the data within your database to make smart and strategic decisions that can impact the programming you already have in place.
The organization (we’ll just call it the Tee-Up Charity) has an annual golf tournament, something very popular and very successful for a number of non-profits. This year, rather than only reaching out to the usual invitee pool of past participants, Tee-Up decided to branch out to new golf tournament suspects. Tee-Up wanted to make sure that it only invited people already invested in its mission, but it also knew that it would not make sense to invite everyone within their database.
Tee-Up data mined its database and searched specifically for interest codes on prospect records that said simply “golf.” Of the handful of new invitees, two prospects responded quickly and not only attended the tournament, but also became sponsors. Tee-Up never would have targeted these two prospects for the golf tournament or for major giving because their past giving to Tee-Up was just too low. But now, with successful segmentation by Tee-Up and self-selection by the prospects, these two golfers have also been identified as potential major gift prospects.
So, you might be asking: “how did Tee-Up have interest codes on file?” Tee-Up happened to use data from Larkspur, a database that synthesizes data from more than 70 different data sources to isolate a few million high net-worth individuals. In addition to interest codes such as golf, yacht ownership and pilot, it also provides ranges for salaries and assets, company affiliations, religious and political views and presence of children in the household.
Larkspur isn’t the only source that you can use to embark on such a project. Who’s Who®, a self-reported biographical type data source, also has valuable information that could have also helped with this type of prospecting. In this case, rather than looking specifically for a clear indicator that says ‘golf,’ instead look for people listed as being members of golf clubs or country clubs in your community.
There are many other ways to approach this type of task that do not involve outside data sources. For instance, those of you who have done constituent surveys may have clues for varying programming at your fingertips. For educational institutions, tracking student involvement/activities can help you make strategic decisions once a person becomes an alum. For organizations that have member/donor logins to their website, you may be able to track click-through codes for varying mission-based content.
The list of suggestions can go on. The key is collect relevant data on your prospects beyond just transactional giving information, and to be creative by leveraging the data stored within your database.
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