The 100k Database Playbook, Applied to My Situation
This is a brutally honest, self-directed application of Fraser's 100k Database playbook to my specific context: software engineer, northern France, currently unemployed, 15,243 LinkedIn connections, chronic focus problems, past startup failure (Valyent), and a desperate need to make money before having to take a job.
1. The Diagnosis: Why I Haven't Made Money Yet
Fraser made $1,182 in his first 2 weeks with a Google Sheet. I've been vibecoding PHP runtimes in Rust for fun. Here's the gap:
| Fraser | Me |
|---|---|
| Started with a pain point he personally experienced | Start with whatever sounds intellectually interesting |
| Built a Google Sheet (0 code) | Build entire platforms before having a single user |
| Cold emailed the leads IN his own database | Have 15,243 LinkedIn connections and message nobody |
| Got revenue, THEN built the web app | Build the app, never get revenue, kill the project |
| 0 subscribers from 14k Twitter followers | I also get nothing from X. But I don't use LinkedIn either. |
| Delegated outreach within 6 months | Do everything myself, burn out, move to next idea |
| Tested pricing ($197 → $297 → $247) | Never charge anyone for anything |
The Valyent lesson I keep citing but never applying: "We spent a year engineering instead of looking for customers." I'm doing it again. Every single time. Palmframe, Hypercode, Wikistral, Hypercafe, PHP.rs — all engineering, zero customers.
2. My Unfair Advantages (That I'm Not Using)
- 15,243 LinkedIn connections. Fraser had zero audience when he started. I have 15,000 people, 2,400+ of whom are founders/CEOs, 1,000+ CTOs/tech leads, 6,000+ engineers. This is a gold mine I've never touched.
- Deep French tech network. Scaleway (76), OVHcloud (68), Mistral AI (67), Qonto (25), Decathlon Digital (19), lemlist (14), Ledger (16), BeReal (11). These aren't randos — these are real companies where I know real people.
- I can build things fast. Fraser paid $150 for his web app. I can vibecode an entire platform in a weekend. This is an advantage ONLY if I first validate that people will pay.
- I'm in France. The French tech market is underserved by English-language DaaS products. Language barrier = moat.
- I understand vibecoding. Jonathan Serra is already working with vibecoders. This is a real, emerging market I know personally.
- I already have AI market research infrastructure. My /ai section has 30+ deep analyses. I understand markets better than most founders.
3. The 3 Most Realistic DaaS Ideas for Me
Applying Fraser's criteria: (1) B2B, (2) I have domain knowledge, (3) I can populate it, (4) I can reach buyers through my existing network.
Idea 1: French Tech Startup Database
A curated, enriched database of every French tech startup: founder contacts, funding stage, tech stack, team size, hiring status. Updated monthly.
- Who buys it?
-
- Dev agencies & freelancers (479 in my network) — they need to prospect startups that will hire them
- SaaS companies selling to startups (devtools, infra, fintech) — Datadog, Supabase, lemlist-type companies
- Recruiters — who's hiring, who's the CTO, what's the email
- VCs & accelerators (68 in my network: OSS Ventures, Hexa, etc.) — deal flow
- Why me?
- I already have 11,000+ unique companies in my LinkedIn. I can scrape Station F directories, French Tech listings, Crunchbase France, LinkedIn company pages. I'm French, I know the ecosystem. No one is doing this well in French.
- MVP data points
- Company name, founder name(s), founder email, founder LinkedIn, company URL, tech stack (if detectable), funding stage, number of employees, city, industry vertical.
- Price
- €149/mo (cheaper than ZoomInfo, more niche, in French). One-time download: €297.
- First 10 customers
- The 479 freelancers in my LinkedIn. They need leads. I have leads. It's that simple.
Idea 2: Vibecoder Service Provider Database
A curated database of vibecoders, their tech stacks, portfolios, pricing, and availability. Plus: a directory of vibecoded apps with what stack was used and who built them.
- Who buys it?
-
- Non-technical founders who need to find vibecoders to build their MVP
- Agencies looking to subcontract to vibecoders
- Jonathan Serra-type consultants who help vibecoders consolidate — they need to find vibecoders to sell to
- Tool companies (Cursor, Lovable, Bolt, Replit) wanting to understand their user base
- Why me?
- I'm literally vibecoding right now. I know the tools, the stacks, the community. This market is brand new — nobody has organized it yet. First mover advantage.
- Risk
- Market may be too nascent. Could be hard to monetize at $150+/mo. Better as a lead magnet / community play initially.
Idea 3: French Tech Conference Attendee Database (Fraser's Exact Model)
Database of attendees from French tech conferences: VivaTech, Web2Day, DevFest, France Digitale Day, etc. Enriched with direct contact info.
- Who buys it?
-
- Sponsors & exhibitors who paid €5K-50K for a booth and want to reach people they didn't meet
- SaaS companies who couldn't attend but want the contacts
- Recruiters hunting for talent at these events
- Why me?
- I attend some of these events. I can access event apps (Fraser's pro tip: you don't need to attend, just pay for the event app). French conferences are under-exploited compared to US ones.
- Risk
- Legal risk in France (GDPR is stricter than in Fraser's case). C&D from conference organizers. Needs careful positioning — "likely attendees" rather than "verified attendees."
4. My Recommendation to Myself: Idea 1
The French Tech Startup Database wins because:
- I already have the seed data (11,000+ companies in my LinkedIn export)
- I have the buyers in my network (479 freelancers, 68 VCs, hundreds of SaaS company employees)
- I have the technical ability to enrich data fast (scraping, APIs, AI)
- Nobody does this well for France specifically
- It's B2B — low chargeback, high stickiness
- I can use it myself (to find customers for whatever I build next)
- It doesn't require me to attend conferences or buy event app access
5. The Execution Plan: 14 Days to First Revenue
Days 1-3: Build the Google Sheet
DO NOT WRITE ANY CODE. NOT ONE LINE.
Create a Google Sheet with columns: Startup Name | Founder(s) | Founder Email | Founder LinkedIn | Company URL | City | Industry | Funding Stage | Team Size | Tech Stack | Last Updated
Populate it from my OWN LinkedIn export:
- Filter connections by "Founder" / "Co-Founder" / "CEO" titles
- That's ~2,400 people with companies
- I already have their LinkedIn URLs
- Start with the top 500 (most recent connections first)
Enrich the first 200 leads:
- Use Apollo.io free tier (250 credits/mo) for emails
- Use company websites for tech stack (or BuiltWith free)
- Use LinkedIn company pages for team size + funding
Quality check: verify 20 random entries manually
OUTPUT: Google Sheet with 200-500 enriched French tech startups
Days 4-5: Validate with My Network (Fraser's "Accidental Share" Method)
1. Share the Google Sheet (view-only, no download) with 30-50 freelancers from my LinkedIn connections.Message (LinkedIn DM, not email): "Hey [NAME] — I put together a database of French tech startups with founder contacts. Thought it might be useful for prospecting. Here's the link: [GOOGLE SHEET URL] Let me know what you think!"
Track who views the sheet (Google Sheets shows active viewers)
When they stop viewing, follow up: "Hey, did you find the list useful? Anything missing that would make it more valuable for you?"
Listen to feedback. Do NOT sell yet.
- What data points do they want?
- What industries are they looking for?
- Would they pay for this if it was updated monthly?
If 5+ people say "yes I'd pay for this": Create a Stripe link at €149/mo and share it.
"Cool — I'm thinking of keeping it updated monthly with new startups, verified emails, tech stack data. €149/month if you want ongoing access. Here's the link: [STRIPE]"
Days 6-10: Cold Outreach to My Own Network
1. Segment my LinkedIn connections:SEGMENT A (highest priority): Freelancers (479 connections) → They need clients. My database IS their client list. → Message angle: "I compiled a prospecting list of French startups with founder emails"
SEGMENT B: Founders of devtools/SaaS (selling to startups) → They need to reach startup founders. I have them. → Message angle: "I have a database of 500+ French startup founders with direct emails. Thought it could help with your outreach"
SEGMENT C: VCs / Accelerators (OSS Ventures, Hexa, etc.) → They need deal flow. I have emerging startups listed. → Message angle: "I'm building a French startup database. Would this be useful for deal sourcing?"
SEGMENT D: Recruiters and HR → They need to reach founders/CTOs at startups → Message angle: "Database of French tech startups with CTO/founder contacts"
Send 20-30 LinkedIn DMs per day (not automated, personal)
Use Fraser's golden rule: do NOT sell in the first message. Get a reply first. The sale happens in the conversation.
Days 11-14: Iterate Based on Feedback
IF 5+ subscribers:
→ Keep going. Add 100 new startups per week.
→ Start enriching with Clay or Findymail for better data.
→ Consider building a simple search web app (I can
vibecode this in 2 hours, but ONLY after 10+ subscribers).
IF 0 subscribers but positive feedback:
→ Adjust pricing (try €99/mo or €49/mo)
→ Try one-time download at €197
→ Add more data points people asked for
→ Keep sharing the free sheet to build demand
IF 0 subscribers and no interest:
→ Pivot to Idea 2 or 3
→ Do NOT spend more than 2 weeks on a dead idea
→ The whole point of the Google Sheet MVP is that
it costs nothing to fail
6. The Anti-Alexis Patterns (Rules to Follow)
- NO CODE for 14 days. Google Sheet only. If I catch myself opening VS Code to "just build a quick prototype," I stop. Fraser made $87k ARR from a Google Sheet. I can survive 2 weeks without touching code.
- NO new project ideas for 14 days. No Hypercafe. No PHP.rs. No observability prototypes. No pentesting tools. One idea, 14 days, full commitment.
- 20 LinkedIn DMs per day, every day. This is the work. Not coding. Not research. Not reading books about startups. Sending messages to real people.
- NO building in public on Twitter. Fraser got 0 subscribers from 14k Twitter followers. I will too. LinkedIn is where my buyers are.
- Charge money on day 5. Not day 30. Not "when it's ready." Day 5. The Stripe link goes out on day 5, period.
- Track revenue, not vanity metrics. I don't care about views, likes, followers, GitHub stars. The only number that matters: € in Stripe.
- If it doesn't work in 14 days, pivot immediately. Don't romanticize the idea. Don't "give it more time." Fraser moved fast. So should I.
7. The Math: What €149/mo Looks Like
| Subscribers | MRR | ARR | Net profit (est.) |
|---|---|---|---|
| 5 | €745 | €8,940 | ~€700/mo (enrichment costs minimal) |
| 10 | €1,490 | €17,880 | ~€1,300/mo |
| 20 | €2,980 | €35,760 | ~€2,500/mo |
| 30 | €4,470 | €53,640 | ~€3,800/mo (hire VA for enrichment) |
| 50 | €7,450 | €89,400 | ~€5,500/mo (Fraser territory) |
Fraser's costs: $500/mo for outreach team + $0.15/lead enrichment. My costs would be even lower because I can automate enrichment with my own scripts. 30 subscribers would already be more than enough to live on in northern France.
8. The Upsell Ladder (After Validation)
From Fraser's playbook, applied to my context:
- Base product: French startup database — €149/mo
- One-time download: For people who won't subscribe — €297
- Custom list building: "Give me startups in [specific vertical] with [specific criteria]" — €500-1,000 one-time
- Outreach-as-a-service: I'll email the startups FOR you using my data — €1,500/mo
- Spin-off databases: French AI startups only, French fintech only, French devtools only — each €99/mo
- The web app (later): Searchable, filterable, with saved searches and alerts — €199/mo premium tier
9. Why This Is Different From Everything Else I've Done
| What I usually do | What I'm doing this time |
|---|---|
| Build first, find customers never | Find customers first, build only what they'll pay for |
| Work alone in silence | Send 20 DMs per day |
| Change projects every 3 days | 14-day hard commitment, no switching |
| Free and open source | Paid from day 5 |
| Complex technical projects | A Google Sheet with a Stripe link |
| Inspired by Linus Torvalds | Inspired by a guy who made $87k from a spreadsheet |
10. Start: Tomorrow Morning
07:00 — Create the Google Sheet. Set up columns. 08:00 — Export my LinkedIn connections CSV to a working format. 09:00 — Filter for founders/co-founders/CEOs. That's ~2,400 rows. 10:00 — Take the first 300. Add to the sheet. 11:00 — Start enriching with Apollo free tier (emails). 14:00 — Enrich company data (URL, team size, city, industry). 16:00 — Quality check 30 random entries. 17:00 — Sheet is live. Share with 10 freelancers from my network. 17:30 — Go for a walk. Let them look at it. 20:00 — Check who viewed it. Follow up with anyone who did.Day 1 output: 300 enriched leads in a Google Sheet, shared with 10 real potential customers.
No code. No Rust. No PHP. No blog post about it. Just a spreadsheet and a Stripe link.
11. Appendix A: Generated Data Files
Two CSV files were extracted from my LinkedIn export (Connections.csv, 15,243 connections) on February 27, 2026:
startup-database-seed.csv— 3,491 rows- All connections with founder/CEO/CTO titles, deduplicated by company. Columns: Company Name, Founder First Name, Founder Last Name, Founder LinkedIn URL, Founder Email, Position, Company URL, City, Industry, Funding Stage, Team Size, Tech Stack, Last Updated. Ready for Google Sheets import. Some noise (non-startups) to clean manually.
buyer-prospects.csv— 1,077 rows- All freelancers, consultants, and independents from my network — the potential buyers. Includes outreach tracking columns: DM Sent?, Viewed Sheet?, Replied?, Reply Summary, Interested in Paying?. Sorted by most recent connection first.
12. Appendix B: French Tech Slack Communities to Target
Tier 1: High-Value (founders + freelancers = buyers AND data)
| Community | Members | Why |
|---|---|---|
| FrenchStartupsIO | 708 | French startups community. Founders sharing, beta testing. Both a data source and a buyer pool. |
| Freelance France | 1,310 | #1 buyer segment. Freelancers who need startup leads for prospecting. |
| CFO Connect (by Spendesk) | 5,000 | Finance leaders at startups. High-value contacts for the database. |
| French CPO | 154 | CPOs from French startups. Small but every member is a potential database entry. |
| Tribes Invest | 120 | Business angels investing €10k-100k seed. Data source (portfolio companies) and potential buyers (deal flow). |
Tier 2: Regional Tech Hubs (startup ecosystem data)
| Community | Members | Why |
|---|---|---|
| lyontechhub | 1,580 | Lyon startup ecosystem. CTOs, founders, devs. |
| Communautés Montpellier | 4,204 | Huge local tech community. Dev + meetup culture = startup people. |
| Startup Lyon | — | Explicitly for founders, freelancers, students in Lyon startups. |
| Dijon Tech | 142 | Small but tight regional community. |
| MetzTechHub | 171 | Northeastern France tech. Close to my area. |
| franchecomté-tech | 141 | Regional community. |
Tier 3: Specialized (enrichment data + potential buyers)
| Community | Members | Why |
|---|---|---|
| French Designers Club | 6,489 | Largest French Slack. Designers at startups = company data. |
| Business Operations Network | 2,000 | Ops people at startups know company details. |
| Sales Tribes | 120 | SDRs/BDRs — they understand the value of a lead database. Potential buyers. |
| Heaven Sales | 110 | VP Sales at B2B tech. Buyers for sure, but invite-only. |
| Modern Data Network | 650 | Data professionals. Overlap with enrichment needs. |
| Les Agilistes | 990+ | Francophone agile community. Lots of startup CTOs. |
How to Use These Communities
- Join FrenchStartupsIO + Freelance France first. Open communities, 2 minutes each.
- Browse #introductions channels. People post company, role, and what they do — free database entries.
- Browse #jobs and #freelance channels. Startups posting jobs = active companies with hiring budget = valuable entries.
- Don't sell anything yet. Lurk, note active startups, add them to the Google Sheet.
- After Day 5, share the sheet as a “resource I built” — not a sales pitch. Freelancers will self-select as buyers.
The Slack communities aren't for scraping at scale — they're for manual enrichment (finding companies you'd miss) and distribution (sharing the sheet where buyers hang out). The CSV + Apollo.io enrichment is the bulk data engine.
13. Appendix C: Scraping Playbook — Platforms, Events, Directories
Beyond the LinkedIn CSV and Slack communities, here's every scrapable data source for populating the French Tech Startup Database, organized by difficulty and value.
1. French Startup Directories (Free, High-Volume)
These are the bulk data sources. Most have public listings you can scrape with Instant Data Scraper (free Chrome extension) or simple Python scripts.
| Source | What You Get | How to Scrape | Volume |
|---|---|---|---|
| Station F Startups | 1,000+ startups with name, description, sector, program | Instant Data Scraper on the public directory page. Paginate through results. | ~1,000 |
| La French Tech Ecosystem Map (powered by Dealroom) | Official French government startup map. Company, sector, funding, city, team size. | Browse and extract via Instant Data Scraper. Limited by Dealroom's paywall for deep data. | 1,000+ |
| Les Pépites Tech | Curated collections of French Tech startups by category | Instant Data Scraper on each collection page. Each collection = 20-100 startups. | 500+ |
| Wellfound (ex-AngelList) France | Startup name, description, team size, funding, tech stack, founder profiles | Instant Data Scraper. Paginate through listings. Free tier shows basic data. | 2,000+ |
| GrowthList France | 1,380+ startups with verified CEO contacts and funding data | Paid access ($49-199 for list downloads). Worth it for verified emails. | 1,380+ |
| Seedtable France | Curated list with funding, team size, description | Instant Data Scraper on the public listing page. | 69+ |
| Failory France | Top 100 startups with description, funding, founders | Instant Data Scraper. | 100 |
2. Event & Conference Platforms (Medium Effort, High-Quality Contacts)
Fraser's core insight: event attendees are warm leads because they self-selected into a topic. Here's how to extract them.
Luma (lu.ma)
The go-to platform for French tech meetups, especially AI/crypto/startup events.
- What you get: Event title, organizer, attendee names + profiles (if public), speaker names
- How: Use the Apify Lu.ma Scraper (free tier: 48 scraper runs/month). Or open DevTools on any Luma event page, click “Guests,” and look for the guest list API request — it returns JSON you can copy.
- Tip: Search lu.ma for “French Tech,” “Paris startup,” “AI France” to find relevant events.
- Limitation: Full attendee list often requires authentication. Hosts, speakers, and featured guests are always public.
Meetup.com
Still big for dev meetups in France (FranceJS, Paris.rb, GDG Paris, Docker Paris, etc.).
- What you get: Member names, bios, event RSVPs
- How: Meetup has a GraphQL API. Query events by location (Paris, Lyon, Lille) and topic (technology, startups). RSVP data includes member name and profile link.
- Tip: Focus on organizers and speakers, not all attendees. Organizers run companies or are senior devs — higher-value database entries.
- Key groups: Search Meetup for tech groups in Paris, Lyon, Lille, Nantes, Bordeaux, Toulouse. Filter by “Tech” category.
Eventbrite
Used by bigger French tech events and corporate-organized meetups.
- What you get: Event name, organizer, description. Attendee lists are private.
- How: Scrape the organizer pages for event history. Cross-reference organizer names with LinkedIn.
- Value: Lower than Luma/Meetup for individual contacts. Better for discovering which companies are hosting events (= active, funded, worth adding to DB).
LinkedIn Events
The most valuable and most overlooked source.
- What you get: Attendee name, headline, company, LinkedIn profile URL
- How:
- Phantombuster LinkedIn Event Guests Export — automated extraction of all event attendees
- Evaboot — tutorial on exporting LinkedIn event attendees to CSV
- Manual: open any LinkedIn event → click “Attendees” → use Instant Data Scraper on the attendee list
- Tip: Search LinkedIn Events for “startup,” “French Tech,” “IA,” “SaaS” in France. RSVP to events to see full attendee lists.
- Risk: LinkedIn may restrict your account if you scrape too aggressively. Use slowly, manually, or with a secondary account.
3. Major French Tech Conferences (Seasonal, Premium Contacts)
These are the big events where the highest-value contacts are. Speaker and exhibitor lists are public; attendee lists require more work.
| Conference | When | Data Available | How to Get It |
|---|---|---|---|
| VivaTech | June (Paris) | 450+ speakers, 3,500+ exhibitors, 13,500+ startups, 3,200+ investors | Speaker list is public on vivatech.com/speakers. Exhibitor list scrapable. Full attendee list via Visitorslist or Vendelux (paid). |
| Web2Day | June (Nantes) | Speakers, sponsors, startup competition finalists | Speaker list on event website. Instant Data Scraper on the speakers page. |
| France Digitale Day | September (Paris) | Startup demos, investor list, speaker list | Check france digitale website for startup portfolio and member directory. |
| DevFest (GDG France) | Various cities | Speakers, sponsors, organizers | Speaker lists on each DevFest city website. Cross-reference with LinkedIn. |
| Devoxx France | April (Paris) | Speaker bios with company + role | Full speaker list on cfp.devoxx.fr. Instant Data Scraper. |
| dotConferences | Various (Paris) | Speaker list with company affiliations | Public on dotconferences.com. |
4. Tools for Scraping & Enrichment
| Tool | Cost | What It Does |
|---|---|---|
| Instant Data Scraper | Free | Chrome extension. Point at any web page with a list/table, it auto-detects the pattern and exports to CSV. Works on 80% of directory pages. |
| Apify | Free tier (48 runs/mo) | Pre-built scrapers for Luma, LinkedIn, Eventbrite, Meetup. Run in the cloud, export to CSV/JSON. |
| Apollo.io | Free tier (250 credits/mo) | Email finder + company data enrichment. Paste a list of company names or LinkedIn URLs, get emails back. |
| Phantombuster | Free trial, then $56/mo | LinkedIn automation: export event attendees, group members, company employees to CSV. |
| Evaboot | $29/mo | LinkedIn Sales Navigator scraper. Exports search results to clean CSV with verified emails. |
| Python + BeautifulSoup/Playwright | Free | Write your own scrapers for directories without anti-bot protection (Station F, Les Pépites Tech, conference speaker pages). |
5. Scraping Priority Order (This Weekend)
- Your LinkedIn CSV is already done. 3,491 founders extracted. Start enriching in Google Sheets.
- Station F directory — open Instant Data Scraper, scrape the /startups page. 15 minutes for ~1,000 startups.
- Les Pépites Tech collections — same method. Pick 5-10 relevant collections. 30 minutes.
- Wellfound France — paginate through the France startup listings. 30 minutes for 200+ companies.
- Luma French tech events — search for recent Paris/Lyon tech meetups, scrape speaker + organizer info. 1 hour.
- Apollo.io for emails — take your top 200-300 companies, run them through Apollo free tier. 1-2 hours.
Everything after step 4 can wait until Week 2. The LinkedIn CSV + Station F + Les Pépites Tech gives you 4,000+ companies before touching any paid tool. That's more than enough to validate whether anyone will pay for this database.
Self-directed analysis based on The 100k Database by Fraser (@iamfra5er) and my own LinkedIn network analysis.