Turning public data into products people pay for. Real files, real costs, real numbers — and the AI tools that make it possible.
Four campaigns, four audiences, 4,100 emails. Construction bounced at 9%. Wholesalers at 13%. Agents opened but never replied. Investors are the only signal still breathing. Here's the honest scorecard.
Read this →My entire data pipeline runs on a $699 computer under a desk. LaunchAgents, Python scrapers, Supabase, and a self-healin...
Read →39 pages, a lead pipeline, an admin dashboard, GA4, DNS migration, and three SEO posts — all from a WordPress site that ...
Read →Travis, Harris, Dallas, Bexar, Tarrant, Collin, Fort Bend, El Paso, Galveston, Nueces, Cameron — every parcel, every own...
Read →A foreclosure record with no address is worthless. But when you cross-reference it against a free county appraisal roll,...
Read →12 counties, 12 formats. Tilde delimiters, 9,716-character lines, values stored in cents, multi-file SQL joins, and one ...
Read →I sent 1,362 cold emails to real estate professionals about a data product. Open rate: 23%. Reply rate: 0.0%. Here's the...
Read →Every era's power belongs to whoever controls its key resource. Today that resource is data — and most of it is sitting ...
Read →Public records are public by law. So why does scraping and reselling them feel like a gray area? An operator's honest re...
Read →Most people pay list vendors hundreds a month for a worse version of what the county will hand you for the price of a co...
Read →A vendor promised 95%. The real number — names tied to a phone I could actually dial — was 64%. That gap is the most exp...
Read →Real files, real costs, real numbers — how to turn public data into products people pay for. Join and I’ll send you the Data Arbitrage Starter Pack to begin.