Methodology

How Mainferret works — and what it can't tell you.

We built Mainferret on a simple conviction: the best acquisition decisions come from evidence, not anecdotes. Here's exactly where our data comes from, how we score it, and — just as important — its limits. We'd rather you trust us because we showed our work.

The data

• SBA 7(a) & 504 loan records (FOIA), 1991–2026 — ~2.17 million loans. Public records from the U.S. Small Business Administration: borrower name, mailing address, NAICS industry, loan amount, approval date, jobs supported, business stage, and final loan status (paid-in-full vs. charged-off).
• Google Places. Current operating status, website presence, review count and rating, and public contact info — our read on a business's digital footprint and demand.
• Open web & public records (for deep-dives): news, litigation, licensing, and registration signals.

The succession signal

The core insight: an owner's tenure is the strongest public predictor of seller-readiness. Someone who took an SBA loan 16–26 years ago is now, on average, at prime exit age — often having bought the business with that very loan. We compute tenure from loan vintage and rank owners by how likely they are to be ready for a conversation, long before they ever list with a broker.

Sell-readiness score

We combine the signals that, together, suggest an owner is ready to move on:

• Tenure (years since the SBA loan) — the dominant factor.
• Loan paid in full — a clean, debt-free, simpler sale.
• Digital neglect — no website, few reviews: an owner optimizing for the exit, not the next decade.
• Reputation drift — a slipping rating can signal a checked-out owner.
• Size fit — loan size and jobs as a proxy for cash-flow scale.

Each signal is weighted; the result is a 0–100 score. The weights are seeded by our judgment and continuously re-tuned against real outreach outcomes — when we learn which profiles actually convert, the model follows the evidence.

Risk & survival intelligence

Because we hold the final status of millions of loans, we can measure what actually survives. We report realized charge-off (default) rates by industry and owner profile — so you can tell a durable trade from a landmine before you spend a dollar. One finding we lead with: businesses acquired through a change of ownership default at 5.3%, versus 11.4% for startups. Buying beats building, in the data.

What this is not

• Not financial, legal, or tax advice. Mainferret is research tooling. Verify every figure with your CPA, attorney, and lender before acting.
• Not a valuation. Scores estimate seller-readiness and relative risk — not what a specific business is worth. That requires real diligence on real financials.
• Not perfect matching. Linking SBA records to a live business by name and location is probabilistic; we show provenance and confidence, and we expect you to confirm before outreach.
• Public data only. We surface what is already public record. We don't expose anything a seller hasn't already disclosed to the government.

Sources

U.S. SBA 7(a) & 504 FOIA datasets (data.sba.gov) · Google Places API · U.S. Census Business Dynamics Statistics · publicly available web and court records. Last data refresh and dataset versions are noted in-product.