ProspectAI’s Affinity Search allows you to go beyond simply categorizing prospects' affinities. Using Affinity Search, you can connect the best matching past prospects you’ve researched to projects and campaigns that you’re planning.
For example, instead of searching for someone who supports “animal welfare”, you can search for “someone who might support building an animal shelter”, and Affinity Search will return the prospects who, via their past giving and other online presence, would be most likely to support that effort.
How does this work?
In short, the combination of technologies we use (vector search and LLMs) work like a super large thesaurus that links every word with every other related word, as well as how related they are. We take your query, then apply this logic to it. For example, if you type in “someone who likes dogs”, the word “dogs” would be linked to the word “animal” in “animal welfare”, which might come up in someone’s giving history. Of course, this is an overly simplified example - in reality, the logic applies to phrases and combinations of words as well.
What sources do you use to generate these scores?
We use as much qualitative data as we can get on every prospect. This can include the names of organizations they’ve given to in the past, but also articles that feature them (e.g., biographies), or quotes from them.
How do I use this for my specific organization?
We’re excited to hear new ways you think of using this, but here are at least two: First, you can describe causes your organization advocates for in very specific ways. For example, instead of “someone interested in healthcare”, try “individuals who might support heart disease prevention in women”. Second, you can uncover donors most likely to support certain initiatives, like capital campaigns.
How often is the data updated?
The search is based on when you last ran the report.