iCustomer offers two products: Decision OS and Audience Loop. Decision OS is a warehouse-native decision intelligence platform for enterprises that need to unify signals, orchestrate AI agents, and measure marketing impact across their stack. Audience Loop is a self-serve AI audience workspace for marketers who want to build, enrich, and activate campaign-ready audiences without engineering support.

Both products focus on turning customer data into better marketing outcomes, but they serve different teams and use cases.

Decision OS is an enterprise platform that sits between your data warehouse and activation tools, enabling composable decision intelligence with AI agents, attribution, and learning loops. Audience Loop is a self-serve spreadsheet-style workspace where AI agents enrich and grade contacts for paid media activation.

The key difference is scope and complexity: Decision OS orchestrates your entire GTM stack with warehouse-native infrastructure, while Audience Loop focuses specifically on getting cleaner, higher-matching audiences into ad platforms like Meta, Google, and LinkedIn in minutes.

iCustomer is not a traditional CDP or standalone enrichment tool. Decision OS is a composable decision intelligence platform that works with your existing data warehouse rather than creating another data silo. Audience Loop is an AI-powered audience workspace focused specifically on paid media activation, not general-purpose data management.

Unlike CDPs that require you to copy data into their system, Decision OS uses zero-copy architecture so data stays in your environment. Unlike enrichment tools built for sales prospecting, Audience Loop is purpose-built for marketing use cases like match rate optimization, suppression, and multi-channel audience sync.

Use Audience Loop if you need to quickly build and activate audiences for paid media campaigns without engineering resources. Use Decision OS if you need enterprise-grade decision intelligence with warehouse-native architecture, AI agent orchestration, attribution, and cross-channel measurement.

A good rule of thumb: if your primary goal is faster, better-matching audiences for ads and you want to start in under 5 minutes, choose Audience Loop. If you need to orchestrate signals, agents, and decisions across your entire marketing stack with data warehouse integration, choose Decision OS.

Audience Loop is built for growth marketers, performance marketers, and agencies who manage paid media campaigns across channels like Meta, Google, LinkedIn, and TikTok. It is ideal for teams that spend time manually cleaning lists, struggle with low match rates in ad platforms, or want AI to handle contact enrichment without building complex data pipelines.

The product works well for D2C brands running reactivation campaigns, B2B teams activating CRM segments, and agencies managing audiences across multiple clients.

Decision OS is designed for enterprise marketing, data, and GTM operations teams that need warehouse-native infrastructure to unify signals, deploy AI agents, and measure incremental impact across channels. It is ideal for organizations with existing data warehouses like Snowflake, BigQuery, or Databricks that want to activate that data without copying it into another system.

Decision OS fits teams that require policy-driven decision automation, cross-channel attribution, and composable architecture that integrates with their existing CRM, MAP, and ad platforms.

Yes. Audience Loop is designed as an entry point to iCustomer's platform for teams that need fast, self-serve audience activation without enterprise infrastructure. As organizations grow and require warehouse-native architecture, unified audience intelligence, and stricter data governance, Decision OS becomes the natural next step.

Decision OS includes all the audience capabilities of Audience Loop plus signal orchestration, AI agent deployment, attribution, and learning loops built directly on your data warehouse. Enterprise teams that need their data to stay within controlled environments typically move to Decision OS, where zero-copy architecture keeps data in Snowflake, BigQuery, or Databricks rather than flowing through an external application.