Page: 'Maya — Validation Interview Notes'\n\nInterview 1 — Sarah, Sugar Bloom Bakery (6 employees)\nDate: May 5, 2026\nWent really well. She immediately got it. Uses Google Sheets for custom cake orders, has a separate WhatsApp group for staff, and paper order slips at the counter. Said the nightmare scenario is when a big custom order comes in and she doesn't know if she has enough butter and eggs until the morning of. "I've had to call customers at 7am to tell them their wedding cake tier is smaller than planned. That's not okay." She mentioned she'd tried Square but gave up after a week. At the end she asked "when can I sign up?" I said I'd keep her posted. Should follow up.\n\nInterview 2 — David, Morning Light Café (3 employees)\nDate: May 6, 2026\nHe was friendly but I'm not sure he's the right customer. His café is mostly standard drinks and pastries, not custom orders. He said operational chaos isn't really his problem. He did mention he uses Homebase for scheduling and likes it. Not a strong signal. Probably not my early adopter.\n\nInterview 3 — Priya, Flour & Thread Bakery (4 employees)\nDate: May 8, 2026\nPriya was the most specific so far. She builds wedding and event cakes — almost entirely custom. Her current system: a Google Sheet with 47 columns that she built herself over 3 years, a separate tab for ingredient par levels, and a printed calendar on the wall. "I've put probably 200 hours into this spreadsheet. It works, but I'm the only person who understands it — if I get sick, the whole operation is at risk." She asked what I'd charge. I said probably $40-60/month. She said "I'd pay $80 if it actually worked." She said she'd be happy to be a beta tester. This is a strong one.\n\nInterview 4 — James, The Crumb Lab (8 employees)\nDate: May 10, 2026\nJames has been in the industry 12 years. Very skeptical of software. "I've tried everything, nothing works for a bakery specifically." He walked me through his exact workflow in detail — it took 35 minutes. He uses Toast, Homebase, a custom Airtable base, and a printed ingredient checklist. "I'm paying $340/month across these tools and they don't talk to each other. If someone built one thing that did all of this, I'd switch tomorrow." When I asked about price: "I'd pay up to $150/month if it actually reduced my morning prep time by 30 minutes." He asked me to email him when I have something to show.\n\nInterview 5 — Linda, Petite Patisserie (2 employees, solo owner)\nDate: May 12, 2026\nLinda is a one-woman operation with one part-time employee. She handles everything manually and doesn't seem stressed by it. Said she's "too small for software" and wouldn't pay more than $20/month for anything. Nice conversation but probably not the right segment for the initial product. Would revisit if we do a free or very cheap tier later.\n\nInterview 6 — Marcus, Provisions Café (5 employees)\nDate: May 14, 2026\nMarcus mentioned allergen tracking three times. He has a customer with a severe nut allergy and currently double-checks manually every time. "One mistake and I have a lawsuit." He uses nothing for inventory — just knows by feel when he's running low. He said he'd tried a few apps but none flagged cross-contamination risks at the ingredient level. "I'd pay whatever it costs if it handled allergens properly. That's not even a question." He asked if he could sign up now. I told him not yet. He said "let me know the second you're ready — I'll send you a deposit."\n\nNotes to self: Strong leads are Sarah (Sugar Bloom), Priya (Flour & Thread), James (The Crumb Lab), Marcus (Provisions). Priya mentioned $80 price ceiling. James mentioned $150. Marcus said "I'll send you a deposit." Need to follow up with all four this week. Also — allergen tracking keeps coming up (Marcus + one mention from Sarah). That might need to be a core feature, not an add-on.

Summary  
This chapter covers transforming unstructured interview notes into a structured five‐field data model by extracting key signals (name, problem phrasing, workaround, commitment level, next action) and organizing them into a tracker.

General domain of usage  
Customer validation interview tracking

Maya has spoken to eleven people. She has notes from six conversations, three follow-up promises she hasn't acted on, two people who asked to be kept posted, and one person who said "send me a contract when you're ready." She also can't remember which bakery owner mentioned the allergen tracking problem and which one complained about staff scheduling.

This is the validation data management problem. It hits every founder around interview eight.

## Why Tracking Matters

Validation interviews produce qualitative data – and qualitative data is slippery. You remember the most recent conversation most clearly, and the most dramatic quote most vividly. The quieter signals – the person who mentioned a specific workaround, the one who said "I'd pay up to $80 for this" – get buried.

A simple tracker solves this by forcing structure onto messy notes. It doesn't need to be a CRM. It needs five columns and a habit.

## The Five-Column Validation Tracker

| Column | What Goes Here |
|---|---|
| **Name + Business** | Who you talked to |
| **Problem signal** | The specific problem they described, in their words |
| **Workaround** | What they're using now to solve it (or not) |
| **Commitment level** | Which rung of the commitment ladder they're on (1–6) |
| **Next action** | What you said you'd do, and by when |

The "commitment level" column is the most important. At a glance, Maya should be able to see that she has 8 people at rung 2, 2 at rung 3, and 1 at rung 5 – and know exactly what she needs to do to move people up.

## Task

Ask Claude to read Maya's Notion notes from her validation interviews and organize them into a structured tracker. The notes are messy – that's the point. The task is to extract signal from noise.

### Prompt to Try
><b>Read my validation interview notes and organize them into a tracker with five columns: Name + Business, Problem Signal (in their words), Workaround, Commitment Level (1–6 based on the ladder), and Next Action. Flag anyone who mentioned pricing or said something that suggests strong buying intent.

Then ask for the analysis:
><b>Based on the tracker, who are my top 3 highest-priority people to follow up with this week, and what exactly should I say to each of them?

Master the skills needed to test a startup idea before building anything. You'll research markets, find early adopters, write cold outreach, analyze competitors, and run a two-week validation sprint — all with AI doing the heavy lifting on research and drafting.

Get hands-on experience turning a vague startup idea into a specific, testable hypothesis – backed by real market research and a clear picture of who your first customer actually is.

Discover how to find early adopters, write cold outreach that gets replies, and read competitor signals – all before writing a single line of code or spending a dollar on development.

Master the skills needed to move from promising conversations to real commitments – tracking your interviews, identifying your strongest leads, and building a sprint plan to close your first paying customer.