AI Donor Summaries for Foundations and Corporations

A few months ago, we launched our AI Donor Summaries feature for individual CharityCAN prospect profiles. Today, we’re expanding this exciting beta feature so that our users can create donor summaries for foundations and corporations as well!

One of the jobs prospect researchers are tasked with is compiling information on a prospective donor. Valueable information like past donations, areas of support, a quick biography, and more are found and compiled into a report that might be used for a prospect review meeting.

With our AI donor summaries, CharityCAN can now create these types of quick reports for each of the types of donors in our database with the click of a button. We take all of the real, verifiable information in our database of Canadian donors and ask a large language model to summarize that data into a few easily digestible paragraphs.

This means organizations and fundraisers without dedicated prospect researchers can use CharityCAN to help them quickly get a glimpse of a new donor, or enable a prospect researcher to quickly add a summary to a note in a donor database to justify further review.

These new donor summaries lend themselves so well to donor database use cases that we’ve also created a new add-in for our integrations with Blackbaud Rasier’s Edge NXT. With only one click you can create a summary of a constituent’s CharityCAN data and import it directly into your database.

To get started with any of these features, please reach out to us for a demo!

You can also check out these summaries in action over on our YouTube page!

How Accurate is CharityCAN’s AI Profile Summary Tool?

Donor Prospect Profiles contain a lot of data – donation records, relationship maps, real estate info, the list goes on – and typically, that’s a good thing. The more data we have, the better we are able to qualify (or disqualify) a prospect. 

That said, sometimes a high level summary will do. 

To help our users put together profile summaries, we decided to build an AI Profile Summary tool. Large Language Models (LLMs) are fantastic at summarizing large amounts of data. And LLMs are AI tech that is here now – not something that may be transformative in the future.

The video below is quick examination of the accuracy of CharityCAN’s AI Profile Summary tool:

Prospect Profile Additions

Our prospect profiles just got some new additions this past week. We’ve got a lot going on, so let’s dive in!

Profile Snapshots

The first thing CharityCAN users will notice is that Prospect Profiles have a new front page summarizing things like donations, recent board positions, connections and household data. We’re bringing out recent or important information and putting it all on one page. From the snapshot you can jump out to view more detailed profile information, so you can dive into the nitty-gritty.

We think this will be a great first starting point when researching a new potential major gift donor.

AI-Generated Summaries (Beta)

The other thing that appears on our snapshots is our new AI-Generated summaries. We’re using Open AI‘s GPT language model to summarize raw profile data into easily digestible text summaries.  This is one of the new features we’re most excited about, as we think there are a lot of possibilities for these summaries. This feature will enable a researcher or a fundraiser to get a quick paragraph to add to an email, profile, or donor database. We’ll dive a little more into how we’re putting these together in a future blog post.

This feature is in beta and will probably be updated in the coming weeks and months, so we’d love to hear how you’re interested in using it!

Relationship Donation Filters

Every Prospect Profile has a full list of relationships. These are connections to other individuals through charity and company boards or other known organizations. We’ve taken that list of relationships and overlayed our donation data, so that not only can you see your prospect’s connections, but also which of those connections are donors to other organizations.

What’s more, you can now filter this relationship list to find donors by cause, amount or location. You can bring up a profile of a volunteer and quickly see if they have any new prospects in their network.

A Prospect Profile Snapshot

 

Profile Snapshots

 

AI-Generated Summaries (Beta)

The other thing that appears on our snapshots is our new AI-Generated summaries. We’re using Open AI‘s GPT language model to summarize raw profile data into easily digestible text summaries. This is a beta feature, so we’d love to hear your feedback!

Relationship Donation Filters

In the Prospect Profiles Relationships section, scroll down to the Full Relationship List to try filtering relationships by donation data. You’ll see prospect connections filtered by donation cause, amount and locatoin so you can easily mine relationships to find new potential donors.

New Data Now Available In Donor Screening

We’re pleased to announce that all the new data we’ve added over the last year in CharityCAN is now available as part of our donor screening data.

Now when you use CharityCAN to screen your donor database, we’ll return three new data points:

  • Federal Corporation directorships that match your donor
  • Aircraft ownership
  • Boat ownership

For additional fees, we can also append:

  • Matching obituary data
  • Detailed donor demographics detailing overall charitable behaviours

While we were in there adding these data points, we also improved our matching algorithm and our output format, so you get more information in your output file and more transparency about what kind of matches we were able to find.

Best of all, you can now use custom graph relationships while screening to see if a donor has a relationship to your organization.

Don’t forget, we can always work with you to integrate your donor screening results back into your donor database so you can slice, dice or analyze it to your heart’s content.

Or are you looking for something more sophisticated like predictive modelling? We’d love to hear about your project goals and work with you to come up with something that fits your organization.

Please contact us if you’d like to see some examples of our new screening output or to talk more about how we can help you get more out of your donor data.

Maximize the Potential of Giving Tuesday with Donor Screening

Giving Tuesday is one of the most important days of the year for Canadian charities. Every Giving Tuesday, thousands of charities across Canada receive millions of dollars from donors.

In 2021, CanadaHelps estimates that Canadians donated $43.6 million on Giving Tuesday. As Giving Tuesday continues to grow in popularity, it’s a safe assumption that this number will continue to grow, as well.

In 2021, Canadians donated $43.6 million on Giving Tuesday

– CanadaHelps

It is clear that Giving Tuesday has a positive impact on Canadian Charities. One, it is extremely effective in encouraging people to give (some of whom will be brand new donors) and two, it raises the profile of philanthropy in Canada generally, creating an increased awareness of Canadian charities, the work they do, and the funding required to do that work. But is there a way Canadian charities can benefit from Giving Tuesday beyond the gifts made and the recognition received?

Consider a charity that receives $100,000 in donations from 2000 new donors on Giving Tuesday. Fantastic, right? $100,000 in incoming donations from people who have never given to the organization is an amazing accomplishment and  should be celebrated.  But is that organization maximizing the benefit these donors could provide?

To truly maximize the benefit of Giving Tuesday, charities should look beyond the initial gift, and funnel new donors into their pipelines. The best way to do this is through screening and segmentation. 

Here’s an example:

Consider the charity that received $100,000 in donations from 2,000 new donors on Giving Tuesday. If that organization screens and segments those donors, the impact of Giving Tuesday will be far beyond $100,000.

Let’s say, if after screening, the breakdown of the group’s 5 year total giving capacity is as follows:

Suppose, if after segmenting: The top 5% (100 people) are funneled into the Major Gifts pipeline.  After careful cultivation and stewardship 10% (10 people) of them make a major gift with an average size of $10,000 (which is just a fraction of this group’s total 5 year giving capacity). The result is $100,000 in additional revenue stemming from Giving Tuesday, just from the Major Gifts segment of the screened Giving Tuesday donors.

Giving Tuesday is an important day for Canadian charities. It generates fundraising revenue, increases recognitiion, and creates awareness. Screening and segmenting the new donors a charity acquires on Giving Tuesday and funneling those donors into appropriate pipelines will ensure the impact of Giving Tuesday lasts far beyond a single calendar day.

Building Better Prospect Profiles

Today we’re excited to announce that we’ve upgraded the way CharityCAN builds our Prospect Profiles – the profiles on individual Canadian donors in our database that are algorithmically created by mixing and matching data from all of the various datasets that CharityCAN has to offer.

This upgrade brings improvements in a few different areas. Read on to learn more!

More Data Means More Profiles

The goal of our profile upgrade was to primarily bring in some of the new datasets that CharityCAN has launched over the last year: the Federal Corporation Registry, Federal Marine Craft Registry, Federal Aviation Registry and the Canadian Deceased List.

By adding these datasets, we added profiles for almost 2 million Canadian donors, bringing our Prospect Profile total to well over 4 million records.

More Profiles Mean More Relationships

Adding this new data to our Profiles also means we now have relationship data between not just individuals on registered charity and public company boards, but between individuals on federal corporation boards too.

Now you can find connections your organization has to local business leaders via local chambers of commerce, or see donor relationships through boards of private companies registered at the federal level.

A New Algorithm To Match Them All

Using all this new data to generate these profiles meant we needed a new way to match different datasets against each other, and figure out what pieces of the profile puzzle fit together.

We overhauled our prospect matching algorithm to better use name frequency and geographic location when de-duplicating donor name data, which we hope has led to cleaner Prospect Profiles.

The best part about our new algorithm is that it is easier to tweak going forwards, so if you see anything that looks amiss, please let us know and we can use your input to fine tune our profile building process in the future.