From 17,000 raw domains to 2,253 verified buyers for Zano

Zano is a privacy-focused cryptocurrency. To grow real-world usage, the project wanted to be accepted as a payment and deposit option on online gambling platforms, with the strongest fit among privacy-coin friendly and no-KYC operators. That audience is valuable and notoriously hard to reach. There is no clean list to buy.

Three things make this market resistant to normal prospecting. Coverage: operators are scattered across gambling-specific domain extensions but plenty of the best sit on plain .com, .io or .gg, so a single source misses most of them. Qualification: a gambling domain is not proof of an active site, and an active site is not proof it takes crypto, both have to be verified at the page level across thousands of sites. Contactability: even once confirmed, most operators block scrapers and publish no contact data. closed:in's brief was not to run a campaign, it was to engineer the targeting layer itself and hand it over for Zano to run.

closed:in does not buy a list and hope. For Zano, the entire targeting layer was built from public sources, in code, in five stages, and sized with a TAM analysis before any scraping began.

The headline is not a reply rate, it is an asset that did not exist before: 2,230 confirmed crypto-gambling operators and 2,253 verified decision-maker emails, distilled from a 17,213-domain universe. What makes it credible is that closed:in sized it first and then hit the number. The TAM run before any scraping predicted 980 to 2,350 priority crypto-accepting platforms, the build found 2,230, at the top of that range. The TAM predicted 70 to 80% email findability, the actual rate was 72%, dead centre. The deliverable was handed over as a structured, two-sheet file, segmented and ready to load straight into Clay and Instantly, with a recommended sequencing plan by crypto-confidence score.

Scope note: closed:in's engagement on Zano was the data engine and handover, not running the outreach. The figures above describe the targeting layer that was built and delivered. This case study exists to show the engineering, in a vertical where the data work is the hard part.