Contact databases and intent data tools mostly miss these moments. Intent data measures reading, and no plant reads its way into a new owner. Which ERP runs a plant's back office almost never appears on its public website either, so tools that scan for installed technology only ever see the marketing site.
Clean researches manufacturing accounts plant by plant: the account is the site where jobs get routed and costed, not only the parent's head office. More than 4,000 early signs sit in Clean's database, catalogued across 14 buying moments in a plant's life, and about 190 of them matter to ERP sellers. For each plant, those signs are laid out on a dated timeline, and a temporal graph network weighs their order and spacing. A change of owners, then a new head of finance, then a second site says more about an ERP decision than any one of the three alone, and Clean maps more than 140 typical chains like that one.
Each plant Clean puts in front of an ERP team carries a dated reason to reach out. Attached to it: the evidence, any other explanation that could fit, and the fact that would prove the reason wrong. Unconfirmed facts stay marked unknown; Clean doesn't guess at them. Repair shops, contractors and one-person operations never reach your list; they are filtered out first. Clean works out who to reach and why, often before the plant has said anything publicly, and your team does the reaching out.
Clean's September 2026 research on the seller side covered more than 500 companies whose software, AI and automation products go into US plants. The mechanics are in how Clean works. Book a demo and you'll leave the call with a live list of plants built for your ERP.