DemandVerified™ / Data Schema

From records to revenue context.

A useful record explains what is known, what is inferred, where it applies, and which action it may support.

Schema example / not a customer recordEXAMPLE-ENTITY-001

Example record structure · no real contact or market data
Data class	Field	Example value	Interpretation
Identity data	Entity identifier	EXAMPLE-ENTITY-001	Synthetic identifier; no person or business is represented.
Attribute data	Geography / market	Example service area A	Synthetic geography; granularity depends on the program.
Attribute data	Customer-fit attributes	Inside defined service area	An illustrative criteria label, not a verified customer profile.
Signal data	Relevant signal category	Category research	A potential category, not a specific person’s observed activity.
Signal data	Signal recency	Within the agreed observation window	No universal timeframe or real timestamp is implied.
Derived intelligence	Demand priority	Review under program criteria	A relative planning label; not a production score.
Derived intelligence	Territory	Example territory A	A planning boundary, not a household location.
Activation metadata	Activation status	Eligibility review required	A record is not automatically approved for every channel.
Signal data	Source category	Illustrative licensed-source category	Does not identify a vendor or confirm available coverage.
Activation metadata	Refresh date	To be set at actual processing	Refresh date differs from observation time.
Customer-provided data	Relationship / exclusions	Customer-supplied context, if authorized	Known facts, permissions, and suppression retain their provenance.

01 / Data Schema

Identity data

Contact or entity identifiers support a defined matching environment. Person, household, and business identifiers are not interchangeable. Unresolved identities should remain unresolved rather than being silently assumed.

02 / Data Schema

Attribute and signal data

Attributes describe available audience context, such as service area or customer-provided offer interest. Signals describe an observation or inferred category, its source category, and its timing. Keep observed facts separate from interpretation.

03 / Data Schema

Derived intelligence and customer-provided data

Priorities, clusters, and fit labels are derived from program criteria. CRM relationships, declared preferences, customer value, and permission records supplied by a customer should retain their own provenance and definitions.

04 / Data Schema

Activation metadata

Territory, eligible destination, review status, suppression, and refresh date explain how a record can be used. An activation identifier does not create channel permission. The schema must be agreed before transfer; every field shown here is illustrative.

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Data Delivery

Get demand intelligence where your team works.

Demand intelligence should not live in another isolated dashboard. Scope an audience or intelligence handoff for the advertising, CRM, sales, analytics, or operational workflow your team uses.

Explore Data Delivery →Identity Resolution

Signals become more useful when they can be responsibly connected to an audience.

Resolution connects appropriate identifiers and context within a defined audience unit and permitted purpose.

Explore Identity Resolution →Data Quality

More records aren’t better if they create more noise.

Optimize for usable intelligence—not database size. Quality means that the data can support the agreed commercial decision within its limits.

Explore Data Quality →

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Your market. An informed next move.

Define your offer, geography, available data, and intended channels. We’ll scope the intelligence and activation options for your program.

See What My Audience Could Include ↗

Signals indicate potential commercial relevance—not certainty that an individual will purchase. Coverage, permitted destinations, and refresh availability vary by program.