In our recent Water Cooler Chat, we talked about using sentiment analysis for getting a glimpse into the minds of our constituencies. For instance, is there a way to understand our donor clusters? Do donors to the new computer lab like to give cryptocurrency, for instance? Gift data itself is the most tracked data that we have, since it is audited. This blog post explores more deeply the idea of uncovering donor interest through relationships among pieces of giving data.
Relationship mapping helps identify natural clusters of constituent characteristics, which can then be used to form segmented solicitation efforts. In other words, moving from a “September direct mail” campaign to an “Online donors who give in September to the computer lab” campaign would help us connect much more personally to members of our audience.
In the Water Cooler Chat, I showed the machine learning technique, cluster analysis. Here is the illustration from my presentation.