Capture what was said in a funder conversation — what they care about, what concerned them, and what to follow up on.
Who did you meet with and what was the stated purpose of the conversation?
Include the funder name, contact name, and whether this was an introductory call, check-in, report-out, or something else.
What did the funder say they care most about right now?
Their stated priorities, current focus areas, or the outcomes they mentioned unprompted.
What questions did they ask that stood out?
Questions reveal priorities. Include anything that felt probing, unexpected, or that they came back to.
Were there any concerns, hesitations, or red flags in the conversation?
Things they pushed back on, seemed skeptical about, or that felt unresolved at the end.
What did they respond most positively to?
Moments where they leaned in, asked for more detail, or expressed enthusiasm.
What is the next step, and who is responsible?
Include any follow-up materials they asked for, decisions expected, and the timeline.
What should the team know about this funder relationship going forward?
Context about their style, preferences, sensitivities, or what would strengthen the relationship.
After each completed session, Mayetik generates a structured AI summary. Here's an example of the output format — the actual content reflects each respondent's answers.
The respondent's answers highlighted three recurring themes — each supported by specific examples drawn from their experience. The summary captures what was said, not what was expected.
Two responses stood out as unusually detailed and pointed to an area worth following up on. The full text of each answer is preserved below the summary.
Based on the patterns in this session, the AI identified three concrete actions for the project team to consider. These are drawn directly from the respondent's own suggestions.
Generated from 7 questions · ~4 min session