What buyers usually want to understand before they deploy Trust ID.

Trust ID helps brands keep more of the customer journey connected before conversion. It can recognize qualifying return activity, understand live intent, preserve earlier source and journey context, and add approved identity or enrichment when more customer information is useful.

Yes. Recognition can begin as persistent journey state before a person's name or contact information is known. When an approved identity event occurs later, the earlier journey can connect to the known customer record instead of restarting at that moment.

Depending on implementation, Trust ID can use approved journey, traffic-quality, return, engagement, intent, permission, and activation signals before authentication. The exact signal set is defined for the customer journey being deployed.

No. Trust ID separates persistent recognition from identity resolution. A deployment can understand and reconnect a journey without turning every visitor into a named profile.

Yes. Identification can be limited to specific pages or journeys while behavioral analytics continues more broadly. This allows the deployment to use higher-cost identity or enrichment only where the added context is valuable.

Intent Intelligence turns live visitor behavior into a current view of engagement, intent, and likely next action while the visitor is still active.

Pageviews and clicks describe events that happened. Intent Intelligence adds approved behavior between those events — such as repeat evaluation, engagement rhythm, hesitation, return behavior, and journey progression — to understand the decision state with more context.

Not by default. Trust ID creates customer signal and makes it available to the systems already responsible for personalization, media, routing, lifecycle, analytics, sales, or service. Activation rules are defined with the implementation.

An implementation can expose engagement state, current intent, likely next action, connected journey context, and destination-ready customer state. Outputs are scoped to the workflow and receiving system.

Trust ID is designed to keep qualifying earlier activity connected so a later visit does not have to look like an entirely new customer journey.

Trust ID can preserve qualifying earlier campaign and journey context across later visits so the eventual outcome carries more of the path that created demand. The attribution model and qualifying rules are defined with the deployment.

No. Analytics and attribution tools can keep their existing reporting roles. Trust ID adds customer-level continuity and earlier context that those systems can use in analysis and measurement.

Across approved participating properties, Trust ID can make scoped recognition, permission, and customer context available without forcing each experience to start from zero. Participation and field rules are defined for each deployment.

Trust ID can add approved person, professional, company, contact, or first-party customer context when more information can improve a decision. Enrichment can be used live or in file/database workflows depending on the use case.

No. Enrichment is intended to be selective. A workflow can use recognition and intent broadly, then request richer context only for the customers or moments where the additional information is worth using.

Yes. A deployment can merge approved first-party customer, account, billing, product, support, preference, or eligibility context through server or data workflows, subject to the implementation and permissions.

The current platform model separates 66 signals that can be available earlier in the journey from up to 168 additional profile fields available through approved identity and enrichment, for up to 234 total customer-intelligence fields. Availability depends on the customer, data source, permission, and use case.

No. Trust ID is designed to sit upstream of and alongside the systems you already use. CRM, CDP, analytics, media, commerce, and personalization platforms keep their execution roles while Trust ID supplies stronger customer context earlier.

Delivery can use APIs, events, files, server/database workflows, or implementation-specific connectors. The correct connection method, permissions, and field scope are confirmed for the destination before deployment.

The starting deployment is designed to be lightweight, but the exact work depends on the journey, destinations, privacy requirements, and activation plan. A validation can begin with a focused implementation before broader rollout.

Credits measure usage across customer-intelligence actions. Recognition uses 0.5 Credit, intent and behavior use 1, enrichment uses 4, and enrich + bind uses 5 under the current pricing model. The same Credit pool can support the mix required by the workflow.

Implementations are scoped by purpose, permission, fields, destination, and workflow. Approved systems receive only the customer context defined for their use.

The current platform is designed to classify whether traffic is human, bot, or AI-agent activity. Agent-to-customer attribution is being developed as a separate private-beta capability for approved workflows.

AI Agent Attribution is the roadmap and private-beta capability for keeping trusted agent activity connected to the customer, authority, permission, and outcome it represents rather than treating the agent as anonymous traffic.