Data licensing — acquisition strategy & pipeline design

Prepared Oct 13, 2026. Companion to the data-licensing leg plan. Purpose: how companies and deals get sourced, screened, and moved to a paid close.

The model in one line

Be the trusted front door between owners of licensable company data and the buyers (labs' brokers) who pay for it — monetized three ways: referral bounties, a negotiated channel percentage, and seller-side success fees.

The rails (register first — introductions only count if they run through them)

Priority order from the verified inventory (Oct 13, 2026): 1. micro1 — up to $50k per signed company, uncapped count; company must apply via Chad's referral link. Targets: 30+ employees, English data, US first. 2. Mercor — referral live, amount unpublished; Chad is already a data partner (warmest channel; also the channel-agreement ask). 3. Mode / BizBuyData — greater of $50k or 6% of deal; companies can receive $100k–$5M; thresholds: 20+ US office employees, 10+ for accounting firms, 6+ for law firms. No public signup link yet — direct inquiry. 4. Handshake AI — flat $10k at close; 20+ FTE, 3+ years operating. 5. Scale AI — program official, bonus unconfirmed (third-party reports say up to $50k); 40+ employees preferred. Every introduction gets logged in the pipeline the day it is made, with the buyer, program, and registration evidence — that log is the non-circumvention record until written channel agreements exist.

Who we source (target seller profile)

• 30–200 employees (program floors vary: 20–40+; accounting/law firms qualify much smaller via BizBuyData).
• 3–5+ years of English-language records across linked systems — Slack/email plus Jira/GitHub/tickets/CRM (linked systems are worth more than standalone documents).
• Verticals buyers pay premiums for: legal, finance, insurance, healthcare (with a de-identification path), professional services, manufacturing, real estate, logistics.
• An owner/CEO who can sign; best timing: steady operators curious about a windfall, companies just acquired, and companies winding down (data value dies at closure).
• Hard screens OUT: firms whose archives are mostly client-owned work (agencies/law/consultancies as sellers of client work — their own internal ops data can still qualify), no de-id path for health data, mostly non-English records.

Where sellers come from (sourcing channels, in expected-yield order)

1. Chad's CPA network — accounting firm owners are (a) sellers themselves at the 10-person BizBuyData threshold and (b) the first to know when a client is selling, closing, or sitting on years of records. One trusted accountant can surface many sellers.
2. His business network — Ambaum-era founders, e-commerce operators, and agency owners across the PNW; his own closed Mercor deal is the proof story that opens these conversations.
3. Wind-down channels — startup lawyers, ABC (assignment for benefit of creditors) firms, bankruptcy trustees (US Trustee Region 18 covers WA/OR/ID/MT/AK), and shutdown advisors. SimpleClosure already courts these; the wedge is Chad's screening quality and speed.
4. VC platform teams & accelerators — portfolio shutdowns and quiet wind-downs surface here first (Carta counted 966 US startup shutdowns in 2024).
5. Direct LinkedIn outreach — founders/CTOs of 30–200-person firms in the target verticals, led with the one-page seller explainer (payout bands, process, privacy handling).
6. Inbound via Leadsure — the pipeline page itself plus a short "what's your data worth" intake form; content from the physical-goods/deals audience overlaps heavily (server owners and data owners are the same people).

The screen (15 minutes, before any introduction)

1. Headcount, years operating, systems in use (Slack? Jira? GitHub? CRM?) and years of history in each.
2. Ownership: whose data is it — client work mixed in? Platform terms that restrict use (Shopify Partner §9.14–9.15 pattern)?
3. PII and secrets posture: employee/customer PII volume, credentials in repos/chats, de-id feasibility.
4. Decision-maker access and timing (operating, acquired, winding down). Output: qualified / nurture / reject, with the buyer match (which program's criteria it fits best) recorded in the pipeline.

Deal flow (pipeline stages — these become the page's columns)

Target identified → Contacted → Screening call → Qualified → Buyer matched → Introduction registered → Buyer diligence → Signed → Paid - Registration discipline: introduction is made in writing (referral link or email to the named partner contact) the same day it happens; screenshot/confirmation saved to the deal record. - One seller can be matched to multiple buyers only where program terms allow; exclusivity questions get asked before, not after. - Fees tracked per deal: program/buyer, expected fee (bounty / % / success fee), trigger event, expected date.

Activity math (what $20k/month requires from this leg)

$240k/year ÷ ~$40k average fee ≈ 6 closes/year. At a conservative 10% close rate on qualified introductions, that is ~60 qualified intros/year ≈ 5/month, fed by a working list of ~100 targets refreshed quarterly. Lumpy by nature: two $50k closes in one quarter cover five months of target — which is why this leg pairs with the physical-goods engine.

Assets to build (first 30 days)

1. Register: micro1, Mercor, Handshake, Scale; direct inquiry to BizBuyData (no public link yet).
2. Seller target list v1: 100 companies tagged by vertical, headcount, systems, channel source.
3. One-page seller explainer (payouts, process, client-data limits, privacy).
4. Finder-agreement template via a lawyer (percentage + floor, renewals, trigger, ≤30-day payment, 12-month tail, non-circumvention, audit rights).
5. Channel asks: Mercor partner team (existing contacts), SimpleClosure, Replay, Troveo, Halluminate.

Pipeline page (Leadsure) — spec

Public page shows: the strategy summary, live pipeline counts by stage, anonymized deal cards (vertical, headcount band, stage, buyer type, expected fee band — no company names until a deal closes and both sides consent), the intake form for sellers, and the current month's licensing revenue vs the $20k goal. The internal working list (names, contacts, notes) stays private in the goal workspace/Google Docs — the page is the showcase and the funnel, not the CRM.