TAM Builder
Define your target market with a deterministic filter and materialize a named target-account list the enrichment waterfall and awareness scorer work automatically.
Overview
TAM Builder turns a set of candidate accounts and a filter into a named target-account list. You paste candidates, set the filter (industry, region, headcount band), and build the list; each match is materialized as a target account that the enrichment waterfall and the awareness scorer then work on their own schedule. It is the front door to the gtmcron demand engine: define the market once, and the rest of the machine runs against it.
How the filter works
The membership is a deterministic filter, so the same candidates and the same filter always produce the same list, which is what makes a TAM defensible. An account must clear every filter you set: any-of industry, any-of region, and a headcount band. A dimension you leave blank is not applied. Headcount only excludes an account that actually has a numeric employee count, so an account with unknown headcount is never silently dropped by a band it cannot be evaluated against. Duplicate accounts (same domain) are collapsed, so a rebuild upserts rather than duplicates.
What "materialize" means
Each matching account is written as a target account keyed on its domain (or its name when there is no domain), tagged with the list name. That is the same record type the enrichment waterfall fills and the awareness scorer ranks, so building a TAM here immediately feeds the rest of gtmcron with nothing else to wire. Rebuilding the same list updates the existing records in place. An account with neither a domain nor a name cannot be keyed and is skipped rather than duplicated; the panel tells you how many were skipped.
Where candidates come from
Today you paste candidates as comma-separated rows (domain, name, industry, employee count, region), which is enough to define a TAM from a list export. The panel also shows the target accounts already materialized for you, so you can review the current list before adding to it. Pulling candidates directly from a data provider is a later step; the deterministic filter and the materialized list are the durable core.