A multi-agent approach to audience intelligence

2026-04-06 · Source: Databricks · Field: Business & Management — Marketing, Branding & Advertising, Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Intermediate, medium

Summary

Databricks has introduced an AI-powered audience generation solution designed to bridge the gap between advertising campaign strategy and execution. This solution, built on the Databricks Data Intelligence Platform, addresses challenges such as strategy dilution, incomplete insights, and data blind spots that arise when business teams hand off campaign briefs to data teams. It enables advertisers and agencies to define audiences using natural language, discover previously unknown patterns within their extensive datasets, and activate more effective campaigns. The architecture involves ingesting first-party and partner data, curating it via Spark Declarative Pipelines into Unity Catalog, and then using an "Audience Genie Space" to translate natural language requests into audience segments. An Affinity Agent computes statistical patterns, while a Supervisor Agent orchestrates the multi-agent system, routing requests to Genie and Affinity sub-agents. The system leverages Databricks' agentic AI advancements, including Genie, custom tool-calling agents, and Agent Bricks, to surface insights and accelerate audience segmentation across hundreds of millions of consumers and thousands of attributes.

Key takeaway

For Product Managers overseeing advertising technology or campaign execution, this Databricks solution offers a significant opportunity to streamline audience creation. You can compress planning cycles from days to seconds and enable real-time responses to market shifts by allowing planners to define audiences in natural language. This approach embeds strategic intent directly into the audience generation process, leading to better targeting and campaign performance, while also strengthening governance through auditable natural language and generated SQL.

Key insights

AI-powered audience generation on Databricks bridges strategy-execution gaps by translating natural language into data-driven segments.

Principles

• Democratize data access for strategic users.
• Encode organizational data expertise into reusable layers.
• Automate discovery of non-obvious data patterns.

Method

The solution uses a multi-agent system, including Genie for natural language to SQL translation, an Affinity Agent for pattern discovery, and a Supervisor Agent for orchestration, all built on Databricks' Data Intelligence Platform.

In practice

• Use natural language to define target audiences.
• Automate SQL query generation for segmentation.
• Discover hidden behavioral affinities in customer data.

Topics

• Audience Intelligence
• Agentic AI
• Databricks Data Intelligence Platform
• Natural Language Audience Generation
• Campaign Performance Optimization

Best for: Product Manager, Marketing Professional, Data Scientist, AI Product Manager

Related on AIssential

• Introducing CustomerLake: The Agentic CDP embedded in Databricks — Databricks CustomerLake unifies CDP functions, AI, and governance within a lakehouse for autonomous, personalized customer engagement.
• Meet Ask Advisor, your new AI-powered collaborator — Google's Ask Advisor unifies disparate marketing AI agents into a single, proactive intelligence platform.
• From Data to Dialogue: A Best Practices Guide for Building High-Performing Genie Spaces — Effective natural language data querying requires robust data foundations, explicit configuration, and continuous validation.
• Marc Andreessen backs $10m raise for ‘synthetic audience’ startup Electric Twin — Synthetic audiences can predict human behavior and market responses by simulating real-world populations digitally.
• Snowflake’s CMO Runs Marketing for 700 People. She Starts Her Day By Talking to Her Data, Not a Dashboard. — CMOs are shifting from dashboards to AI agents for direct, conversational data interaction.
• The Virtual Roundtable: Multi-Agent Personas Simulating the Dynamics of Human Brainstorming — Multi-agent AI personas can simulate human brainstorming, deepening idea refinement through structured discussion but not expanding initial diversity.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.