Why are all these data companies buying internal data?

Commenters discussed why data brokers and startups are buying internal business data, with many saying the primary driver is AI training and forecasting. DecoPerson framed the purchases as a quest for predictive signals that can beat market returns, while others pointed to specific use cases: chasebank relayed that home-health businesses are being offered large sums for their records, and ddarolfi noted firms like HUMXN Research Labs seeking trades, farming and manufacturing data. Lukeschlather and others emphasized practical applications - plumbers’ emails and QuickBooks entries reveal job types, prices and workflows useful for building domain-specific models or designing robots - and whatdowecallu argued internet scraping alone no longer suffices.

Opinion split over value and implications. Forshaper and toddmorey argued organic, operational data captures real edge cases that improve model accuracy where simulations fail, and altcognito listed concrete questions such data answers about customers and pricing. Skeptics like eeko_systems and rootsudo questioned how transaction logs actually make models better or whether public Medicare data already covers key signals. Totetsu and Delphiza raised broader concerns about AI’s all-consuming pull and the risk of underpaid employees selling internal data, highlighting ethical and market-maturity tensions beneath the commercial interest.