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Audience Studio is the platform’s visual audience builder. It provides a guided workflow for selecting a data source, applying filters to segment your audience, choosing connector destinations, and delivering the resulting audience — all without writing NQL by hand.

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How Audience Studio works

Audience Studio builds audiences by combining three things:
  1. A source dataset — The data you want to segment. This can be your own first-party data (CRM records, transaction data, customer attributes) or third-party data accessed through access rules.
  2. Filters — Conditions that narrow the source data to the audience you want. Filters use your dataset’s Rosetta Stone attribute mappings to provide structured, type-aware controls.
  3. Connectors — Destinations where the audience will be delivered. Each connector handles format translation, identity matching, and API integration with the destination platform automatically.
The builder generates an NQL query behind the scenes, executes it to create an audience dataset, and sets up connector deliveries — turning what would be a multi-step manual process into a single workflow.

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Builder steps

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1. Source selection

Choose the dataset that contains your audience data. The dataset must have Rosetta Stone attribute mappings so Audience Studio can understand which fields are available for filtering and which identifiers are available for delivery. Only datasets on the currently selected data plane are shown.

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2. Connector selection

Choose one or more destination platforms to deliver your audience to. Available connectors include The Trade Desk, Meta, TikTok, Google DV360, Pinterest, Yahoo DSP, Magnite, PubMatic, and Amazon S3. Audience Studio checks connector eligibility automatically — it verifies that your source dataset contains the identifier types required by each connector’s collaboration policy. Ineligible connectors are flagged so you know before building the audience whether delivery will work.

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3. Filters

Apply conditions to narrow your source data. Filters are built from your dataset’s mapped attributes, so the available filter options reflect your actual data.

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Filter types

TypeControlsExample
Enum (low cardinality)Checkbox list of valuesGender: male, female
Enum (high cardinality)Searchable dropdownCountry: US, CA, GB
BooleanToggleOpted in: true / false
StringText input with multiple valuesEmail domain: gmail.com
TimestampCurated ranges, custom lookback, or date rangeLast 30 days, last 90 days
Numeric (long, double)Comparison operators with valuesAge greater than or equal to 25

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Logical operators

Filters support AND / OR logic. Multiple filters default to AND — all conditions must match. Group filters with OR to match any condition within a group.

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Frequency filters

Any filter supports an optional frequency constraint — for example, “purchased at least 3 times in the last 30 days.” Frequency filters use a QUALIFY clause in the generated NQL to count distinct occurrences of a field.

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Null handling

Filters include Is null and Is not null options that generate correct IS NULL / IS NOT NULL NQL predicates, allowing you to filter on the presence or absence of a value.

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4. Finalize

Configure the audience metadata and connector-specific settings:
  • Audience name (required) — Identifies this audience in the platform and in destination systems
  • Description — Optional context about the audience’s purpose
  • Tags — Optional labels for organization
  • Refresh schedule — How often the audience is rebuilt. Choose one-time for a static audience or set a recurring schedule (daily, weekly, etc.) to keep the audience current as source data changes
  • Connector quick settings — Each selected connector has platform-specific fields (advertiser selection, audience naming, historical data options). These are validated inline before creation.

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Forecasting

Before creating an audience, you can forecast its size. The forecast runs a preview query against your source data with the current filters applied and returns the expected record count. This helps you verify that your filters produce the right audience size before committing to creation. Suggested filter values show what percentage of your forecasted audience matches each value, helping you understand the impact of adding or adjusting filters.

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What Audience Studio creates

When you click Create Audience, Audience Studio:
  1. Generates and executes an NQL query based on your filters
  2. Materializes the results as a new dataset tagged as an audience
  3. Creates connector deliveries for each selected destination with your configured quick settings
  4. If a refresh schedule is set, configures incremental updates using NQL MERGE to keep the audience current
The resulting audience dataset appears under My Audiences in the navigation and can be managed, cloned, or delivered to additional connectors at any time.

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Cloning audiences

You can clone an existing audience by selecting Open in Audience Studio from the audience’s action menu. The builder pre-populates with the original audience’s source, filters, connectors, and settings, giving you a starting point for creating a similar but distinct audience.

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Related content

Building an Audience

Step-by-step guide to creating your first audience

Structuring Audiences

Strategies for organizing data for activation

Data Activation

How connectors deliver data to destination platforms

Connector Reference

Technical details for each destination connector