Molly Singer – Expert Interview Guide (30 minutes)

Open (30–45 seconds)

• Quick context: “We’re building GrantFinder AI to help K-12 districts discover, qualify, and manage grants faster. We’re talking to experts who see many organizations to learn what actually works.”
• Ask consent to take notes/record.
• Goal: learn how prospecting/qualification really happens, especially for school districts vs. other sectors.

A) Role & Pattern Recognition (3–4 min)

1. Client mix & vantage point
   • “Which types of organizations do you most often support (districts, nonprofits, higher ed, city agencies) and where do you see the most repeatable patterns in grant prospecting/qualification?”
2. What “good” looks like
   • “Across your clients, what does a high-performing grants operation do differently in discovery and eligibility—what are the non-negotiables?”

B) Prospecting & Qualification: Cross-Sector vs. School Districts (6–7 min)

1. Prospecting workflow you recommend
   • “Walk me through your ideal prospecting workflow—from need definition → longlist → shortlist → go/no-go. Where do tools help vs. get in the way?”
2. School districts specifically
   • “Where do K-12 districts struggle most vs. other sectors—finding opportunities, interpreting eligibility, assembling data, approvals, or post-award?”
     • Assumption: Over programmed, how do i fit something new in here.
3. Signals of fit (go/no-go) up front
   • “What 3–5 criteria should a district check immediately to avoid wasting weeks on a misfit opportunity?”

Probe if helpful: seasonal timing (school calendar), match requirements, allowable costs, evaluation burden, reporting cadence.

C) Tools & Data: What Works, What Fails (6–7 min)

1. Prospecting tools
   • “Which prospecting tools/databases do you actually trust for relevance? Where do they fall short for K-12 (taxonomy, filtering, stale data, state-level nuance)?”
2. Eligibility clarity
   • “If you could redesign one step, how would a tool translate dense RFP language into a clear, district-profile-aware go/no-go with rationale?”
3. Data assembly & evidence
   • “For districts, what datasets (enrollment, FRPL, assessment, attendance, program outcomes, equity indicators) are always needed—and where does the data wrangling burn time?”