Every Monday, I receive a spreadsheet with the metrics for all the fundraisers on our team. It’s filled with columns of goals, visits, asks, closes, and percentages.
But most fundraiser metrics reports don’t actually help managers manage.
You glance at the numbers, look for where fundraisers are behind on their goals, and then give feedback based on what’s low. It’s reactive and rarely gets to what really matters.
So I tried something different.
I put a very specific prompt into AI. One designed specifically for managers of frontline fundraisers. I fed it the same metrics we already track and asked the AI to act like an experienced nonprofit fundraising consultant and frontline manager advisor. I then asked the AI to analyze fundraiser performance in a way that would inform strategic coaching, morale, recognition, and early trend detection (the full prompt is much, much longer).
The output was amazing.
What came back wasn’t a prettier report. It gave me the things managers actually need:
- Early indicators of pipeline risk, before the numbers get bad
- The top one or two coaching focus areas for each fundraiser in their next 1:1
- Visibility into who’s truly strong versus who just looks busy
- Clear trends and early warning indicators
- Signals for who deserves recognition this week
- A short list of where my time actually matters most right now
The best way I can describe the results is this: it felt less like reading a report and more like having another experienced manager sitting next to me saying, “Here’s what actually deserves your attention this week.”
If you manage frontline fundraisers and feel like your metrics report isn’t telling you the full story of your team, this is the solution.
I’m happy to share the full AI prompt. Just email me at [email protected] to request it.
One important note: When putting private information, like fundraiser metrics, into an AI tool, make sure you’re using a platform that allows that information to remain private. Many AI systems may store and potentially use content shared in conversations to improve their models. As managers, we have a responsibility to protect our teams and our institutions, so it’s important to understand the data privacy settings of any AI tool before using it with internal or sensitive information.