Start a B2B Data Aggregation Service

A B2B data aggregation service collects and cleans a scattered public dataset (business licenses, building permits, inspections) and sells access to it via API or subscription to companies that need it. It sounds technical, but the hard part is persistence, not code: valuable public data sits fragmented across thousands of government sites, and cleaning it into something a sales team can actually use is the moat. You pick a dataset with real buyers, validate demand before building, write scrapers and file records requests, clean and dedupe everything, and sell simple (CSV subscriptions) before adding an API. Startup runs $500 to $3,000, margins run 70 to 90 percent, and reliability is why B2B data subscriptions renew for years.

Valuable data (building permits, new business registrations) exists publicly but scattered across county and state sites in inconsistent formats, so companies that need it (contractors, lenders, insurers, sales teams) cannot easily use it and will pay for a clean, current version. The reframe most people miss: the moat is cleaning, not scraping, because anyone can scrape but a deduplicated, standardized dataset a sales team can import is what commands the price. You start from who pays, not what is easy, validate before building, and grow by poaching customers from worse providers. Because the work is persistence rather than novel technology, and the data refreshes, subscriptions are sticky and margins are high.

It sounds like a technical data-engineering project, so people assume it needs deep expertise, when the real work is the unglamorous persistence of collecting fragmented public records and cleaning them well. The overlooked reality is that valuable data sits free but unusable across government sites, and companies already pay for stale or overpriced versions. Because most people never start from who pays or do the cleaning work, the one who does can build a sticky, high-margin subscription.