Dstillery data & DS-1: how they fit together

See how consented panel data and website signals become targetable audiences.

Signals in. Audiences out.

Dstillery turns observed behavior into audiences built for activation.

It starts with two datasets working together. One teaches intent. The other identifies its scale.

1. Opted-in panel data teaches

About 2 million fully consented users, sourced through panel partners, reveal how decisions take shape.

Their journeys show the research, comparison, and consideration that precede an outcome.

This data trains the model. It never targets an individual directly.

2. Website visitation data reaches

Website visitation data spans web and mobile activity across about 400 million devices.

It is sourced from bidstream data via SSPs and exchanges. It also comes from web publishing tools, including ad, commenting, and sharing widgets.

Once the model learns a high-intent pattern from panel data, website visitation data finds devices showing that same pattern.

Audiences refresh every 24 hours and become available for targeting.

Opted-in panel data teaches. Website visitation data reaches.

For a travel campaign, panel data might show future bookers researching destinations.

They compare reviews and revisit flight options before converting.

Website visitation data finds devices showing that same pattern. It makes them targetable in the client's DSP.

From behavior to activation

1

Learn the journey

The model observes sequences, not isolated page visits.

2

Recognize similar intent

The model identifies devices showing comparable patterns.

3

Deliver a fresh audience

Audiences refresh every 24 hours. They are ready for activation in a DSP.

Where DS-1 comes in

These datasets are two of the four core signal types the multimodal AI model learns from.

The other signal types are LLM-derived insights and partner data.

See How our multimodal AI works for how the model connects all four.

For the full technical picture, including data partnerships and Dstillery's approach to data quality, see Our data sources.

DS-1 turns this intelligence into an audience on demand. Describe an objective, provide an input, or work from existing data.

DS-1 builds an audience with the control and visibility teams need.

The result: faster audience creation, clearer inputs, and targeting grounded in observed intent.