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Our data sources

Explore the consented, scaled, and specialized signals behind Dstillery audiences.

Dstillery combines consented behavioral data with website activity at scale.

How the data works together

Learn from consented journeys

Opted-in panel data

About 2 million fully consented users reveal the journeys behind decisions.

Panel partners provide this data. It trains the model. It never targets people directly.

Recognize patterns at scale

Website visitation data

Web and mobile activity across about 400 million devices makes learned patterns actionable.

This data comes from bidstream partners and web publishing tools.

For the full story, see Dstillery data & DS-1: how they fit together.

Data sources

Opted-in panel data

Panel partners provide fully consented data from participants. Their browsing journeys show the research and comparison patterns that lead to an outcome.

The model learns sequences, not isolated clicks. It recognizes the difference between casual interest and meaningful consideration.

Website visitation data

Website visitation data provides the reach layer. It is sourced through SSPs, exchanges, and web publishing tools, including ad, commenting, and sharing widgets.

This dataset captures billions of daily behavioral events. It shows where comparable intent appears across the open web.

Specialized partner data

Specialized partners add depth for distinct campaign needs:

  • NielsenIQ/GfK supports CPG and auto use cases.

  • PurpleLab supports healthcare use cases.

  • ScreenEngine supports media and entertainment use cases.

  • Resonate supports consumer insights.

  • Emporia supports B2B use cases.

Partner signals complement the core datasets. They help the model understand specialized contexts.

This is the detail behind the “partner data” signal type in How our multimodal AI works.

Custom audience seed signals

DS-1 can begin with the signal you already have:

  • First-party data

  • A domain

  • Search terms or keywords

  • Behavioral signals

  • Retail purchase intent

These inputs help seed a custom audience. The model identifies related patterns for scalable activation.

How audiences refresh

  1. The model identifies behavior patterns associated with an outcome.

  2. Website visitation data identifies devices showing similar behavior.

  3. Audiences refresh every 24 hours and are ready for delivery.

How Dstillery thinks about data

Just for your brand. Every campaign runs on a custom model tuned specifically to that brand, not a shared, generic model.

Fresher data is better data. Custom audiences refresh every 24 hours, so targeting reflects current behavior rather than a stale snapshot.

Balance performance and scale. Every audience is scored and ranked against Dstillery's entire universe of devices, tuned to the right balance for each campaign's goals.

Responsible data use

Dstillery uses data to model intent, not to target a known individual.

Learn more about Dstillery's Privacy and data.

Learn more

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