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Audience Intelligence
1.3M government decision-makers. Precision targeting. Measurable outcomes.
Target government decision-makers by state, agency function, job role, and government branch. DataOS profiles every contact captured across all engagements — giving you precision audience segments no third-party data provider can match.
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States Covered
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Job Functions
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Government Branches
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Natural-Language Audience Builder
Beta
Describe the audience you want to reach in plain English. The builder composes six signals — topic engagement, agency-function presence, BI text match, semantic similarity, government procurement match, and sponsorship history — and returns a ranked list with cited evidence per account.
Gap Analysis — Find accounts missing a key role
Beta
Describe a role and the engine returns accounts that lack it, ranked by revenue. Hand off any row to ZoomInfo with the target role pre-filled — or run an inline quick search. The Ideal Team Coverage chips are derived from your won deals (stored in indexes/contact_ideal_roles.parquet).
Campaign List — Pipeline + scored prospects
Beta
Describe any outreach list in plain English. The engine interprets event start-date windows, opportunity stages, scored prospects (event_prospect_matches and product_synthesis), and flags accounts whose best contact spans multiple product families. Use “no other open pipeline” to keep prospect-only accounts that lack additional CRM opps.
Decision Maker Matrix — who has to be in the room
Beta
For each product line, which buyer archetypes were present on the deals we won versus the ones we lost. Only closed, pre-decision (OpportunityContactRole) records count — contract and delivery roles exist only on deals that already closed, so including them would score the outcome against itself.
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Account coverage — who we have, what is vacant
Measure one account against a product line's blueprint. A filled seat names the contacts we already have (ranked by deal influence, then recency); a vacant seat hands back the titles to search for.
Contact Behaviour — every person we have ever observed
Beta
One row per human across 15 behaviour domains — events, webinars, badge scans, papers, newsletter, marketing email, website, subscription usage, surveys, polls, replies, forms, speaking, deals and qualified interest — rolled into four dimensions and stacked month by month back to 2010. Scores are read against what we could actually observe about each person, so somebody we hold no channel for reads as unobserved rather than disengaged.
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Sector
Behaviour band
Trajectory
Behaviours
Distribution
Grouped
Behaviours in this cohort measured of observable
Accounts
People observed per account within the current filter
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