A pre-launch fintech built a 1,100-person ICP-qualified waitlist with Linkeddit + Claude in 14 days
Lumenpay: Seed-stage B2B fintech
Lumenpay needed a beta waitlist full of real SMB founders with multi-currency invoicing pain, not curious Twitter bookmarkers. Linkeddit surfaced the threads where those founders were already complaining. Claude + MCP turned each complaint into a tagged waitlist entry and a qualitative insight for product.
Background
Lumenpay's thesis is that Stripe holds funds too aggressively for international SMBs and Wise's platform-fee model is broken for agency ops. Their ICP is loud about this, in very specific subreddits. The founding team knew that the first 1,000 waitlist signups needed to be interview-grade, because they'd also be the first design partners.
The problem
Classic pre-launch trap: easy to get 10,000 'email me when you launch' signups that are worth nothing, hard to get 1,000 ICP-matched signups that are worth everything. The team had to build the waitlist and the qualitative research pipeline at the same time, with three people.
Pipeline configuration
Lumenpay runs 2 Linkeddit pipelines. Each one is scoped to a narrow set of subreddits and keyword patterns so the lead queue never turns into noise.
Stripe / Wise pain
wise blocking my accountstripe hold on fundsstripe rolling reserveinternational invoicing nightmaremulti-currency invoicingpaypal froze funds- •Contactability score ≥ 60
- •OP account age ≥ 180 days
- •Thread must contain a revenue or transaction figure
Agency ops pain
paying international contractorsinvoicing in USD and EURcontractor payout platformagency payment stack- •Contactability score ≥ 65
- •Thread score ≥ 5
AI Content Writer workflow
- 1.Empathy-first drafts: first 80 words are pure acknowledgment, no product mention.
- 2.Exactly one ask per reply: 'we're building something for this specific problem, want early access?'
- 3.Never link to the signup page; use a plain hand-typed URL so it looks like a recommendation, not a drop.
- 4.Follow-up DMs are hand-written after an OP opts in, never templated.
Linkeddit MCP + AI integration
Lumenpay's killer workflow is a nightly Claude job that pulls all new leads + waitlist signups, classifies them against the ICP, and writes a one-page voice-of-customer report for product.
search_leads: nightly sweepget_lead_insights: full profile + niche tagsfetch_post_comments: read entire threads for product insightsearch_reddit: discover adjacent complaint subreddits the team hasn't onboarded yet
- •Airtable MCP: stores waitlist entries with every qualitative tag
- •Linear MCP: auto-creates product tickets when ≥ 3 leads cite the same feature gap
- •Notion MCP: nightly VOC report lands in the product ops doc
- •Gmail MCP: drafts personalized follow-up emails (founders send manually)
Pull all waitlist signups from the last 7 days. For each, use get_lead_insights to analyze: company size proxy, industry, likely transaction volume, primary pain keyword. Cluster into 5 groups. For each group, extract 3 verbatim quotes and write a paragraph describing what they want from us. Create Linear tickets for any feature cited by ≥ 3 leads.
Want to run this workflow yourself? Set up the Linkeddit MCP server or connect via the Claude connector.
Daily rhythm
- Morning: Alex reviews overnight leads + waitlist entries in Airtable.
- Throughout the day: Replies posted from two founders' personal accounts.
- Evening: Nightly Claude VOC job runs; report lands in Notion by 11pm.
- Friday: Weekly product sync uses the VOC report as the primary input.
Thread breakdown
Subreddits monitored
Results
- •1,100 waitlist signups in 14 days, 62% matching the ICP on company size and industry.
- •One thread alone drove 220 signups and three inbound VC intros.
- •Voice-of-customer report informed 4 of 6 features in the beta release.
- •Now treats Reddit as the primary qualitative research feed in the company.
Lessons
- 1.The VOC job was the surprise killer feature. Waitlist size is vanity; tagged pain-point data is compounding value.
- 2.Don't link the signup URL in the reply. Let them ask how to sign up, or search and find it themselves. Signup rates were 1.6x higher without the link.
- 3.Auto-creating Linear tickets from recurring complaints eliminated the 'what do we build next?' debate.
“People think of a waitlist as a marketing asset. Ours is a product research instrument. Every person on it is a tagged data point with verbatim language, because Linkeddit's MCP turns every Reddit reply into a row in Airtable and a paragraph in a VOC report.”
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