Overview

Composable Audience Studio (CAS) is a deployment mode of Treasure AI's CDP that enables you to build and manage audience segments directly on your Google BigQuery data warehouse without copying data into Treasure AI. Using Zero-Copy / Federated Query architecture, CAS queries your BigQuery tables in place, keeping data under your existing governance and access controls.

This guide walks through the end-to-end process of setting up a Composable Parent Segment on BigQuery, from GCP service account configuration to segment creation.

1. GCP service account and JSON key authentication for secure BigQuery access
2. BigQuery authentication configuration to connect Treasure AI to your BigQuery project
3. Zero-Copy catalog configuration for federated queries
4. Parent Segment configuration file defining your customer and behavior tables
5. API upload of the configuration to create the Parent Segment in CAS

Before you begin, ensure you have:

• A Treasure AI account with admin-level permissions
• A Google Cloud Platform account with:
  • A BigQuery project, dataset, and tables containing your customer and event data
  • Permission to create service accounts and manage IAM roles
• A Treasure AI API key (Master API key recommended)

Data never leaves your BigQuery environment. Treasure AI sends federated queries and receives results at query time.

A Composable Parent Segment is composed of a single Customers table and multiple Behaviors tables.

The Customers table stores unified profile data and attributes, with each record representing a single profile. A unique identifier column is required for each profile.

• Contains all customer attributes (e.g., email, name, city, membership tier, LTV)
• Each row = one unique customer profile
• Unique identifier column serves as the primary key

Behaviors tables contain activity records for specific actions taken by profiles (e.g., website visits, orders). Each Behaviors table must include a unique ID column that links the activity record to the corresponding customer profile via the Unique identifier.

• Each table represents a distinct type of activity (page views, purchases, etc.)
• Multiple behavior records can exist per customer
• Must include a time column for temporal queries

The relationship between Customers and each Behaviors table is 1-to-many: one customer profile can have many behavior records.