As a manager of frontline fundraisers, there’s one task I know I should be doing and almost never have enough time for: reading visit contact reports.
These are the reports fundraisers enter into the CRM after meeting with a prospect. They’re often detailed, multiple paragraphs long and there are a lot of them.
Reading every single one is time-intensive. But here’s the thing: visit contact reports are one of the best ways to see how a fundraiser is actually doing their job. You can see how they’re building relationships and how comfortable they are talking about money. And most importantly, you can spot exactly what needs to be discussed at their next 1:1.
That’s where AI became a huge help for me.
Instead of trying to read reports one by one, I now submit a single PDF that includes all of a fundraiser’s visit contact reports. I ask AI to read and analyze the entire set and give me a summary. Here’s what I get back:
- Executive coaching summary
- What This Fundraiser Is Doing Well
- Strategic Gaps and Missed Opportunities
- Asking & Money Conversations
- Donor Strategy & Momentum
- Patterns the Manager Should Address in 1:1 Meetings
- Suggested Coaching Questions for the Manager
- Prospect-Specific Snapshots (for immediate 1:1 action)
This is exactly the information I need for a 1:1 meeting. Instead of vague feedback like “You should be more strategic,” I can be specific:
- You’re doing a great job building rapport, but you’re consistently avoiding money conversations.
- You’re meeting often, but there’s very little evidence of a clear donor strategy.
- These three prospects are ready for a next step, and it hasn’t happened yet.
That changes the entire dynamic of the meeting. The conversation becomes more productive and more helpful for the fundraiser.
If you want to see the exact prompt I used to get this information, just email me at [email protected].
One important note: when you’re putting private information like fundraiser metrics or visit reports into an AI tool, make sure you’re using one that allows the information to remain private. Many AI platforms may store and potentially use content from conversations to improve their models.