Reonomy

Reonomy's pitch is narrower and more honest than most CRE data platforms: it is not a listing marketplace and it does not try to be. The product is a connected dataset — 53M+ commercial parcels, 68M+ transactions, 5.2M+ companies, 30M+ owner and contact records — with a machine-learning layer that matches each property detail and transaction back to a single property record and a single true owner. Public records are inconsistent, ownership entities are deliberately opaque, and the work of stitching five sources together is exactly the work Reonomy sells to you pre-done. Strengths start with owner resolution. Pierce an LLC or holding company and you get the human, plus verified phone, email and mailing contacts ranked by reliability. The ownership portfolio view then shows every property that owner controls and every entity in their corporate structure — which is how acquisition teams spot multi-parcel sellers before anyone else does. The likelihood-to-sell score, which weighs ownership tenure, debt position, transaction history and market signals, is the second pillar: it ranks the deals worth chasing rather than giving you a raw list. Rounding it out are property profiles (square footage, asset class, year built, lot size), full transaction history including sales, debt, liens and refinances, occupant data across every U.S. location of a tenant, and demographic and market data. The 200+ filters are the practical interface to all of it. Weaknesses are mostly commercial rather than technical. There is a real subscription floor — $400/mo billed annually, $500/mo month-to-month — and the annual rate only exists because you commit to a year. Exports are metered: the Annual tier includes 1k monthly exports and additional packs of 1,000 records per month are sold separately, so heavy list builders should price their actual volume before signing. Bulk Data Feeds and the API connection are quoted by sales, not self-serve, which means procurement overhead if you want Reonomy data inside your own warehouse. Coverage is U.S.-only, which is fine for the target buyer and a hard stop for anyone else. And the entire value proposition rests on the ownership and contact layer: if you only need comps, you are paying four figures a year for a dataset you don't use. Where it fits: brokerages running systematic cold outreach, acquisition and investment teams sourcing off-market, lenders and debt brokers hunting refinance and distressed opportunities, developers assembling site lists, and appraisers or research teams that need ownership and transaction records in one place. Where it doesn't: solo brokers on tight software budgets, non-U.S. markets, and anyone who wants public listing data rather than an owner-contact engine.