Composable Audiences Overview

Composable Audiences is mParticle’s zero-copy solution for segmentation. With Composable Audiences, you can create dynamic user segments using data stored directly in your cloud data warehouse. This approach lets you take advantage of rich, custom attributes and events that already live in your own systems, without needing to copy data into mParticle. By querying your warehouse directly, audiences are always built on the most up-to-date and complete picture of your users.

When to use Composable Audiences

Composable Audiences are the right choice when you care about a customer’s accumulated history, attributes, or modeled data—things that live in your warehouse. These audiences are ideal for planned, lifecycle-driven campaigns where hours or days of latency are acceptable. For example:

• High-value or loyal customers: Segment users with a lifetime value above $1,000 and more than 5 purchases in the past 12 months.
• Dormant customers: Identify users who haven’t made a purchase in 300+ days but are still opted into marketing emails.
• At-risk subscribers: Target users with a churn risk score greater than 0.7, calculated by your data science team.

Because these audiences run on a scheduled basis against your warehouse, they are well-suited for strategic campaigns like loyalty promotions, cross-sell recommendations, or reactivation offers.

When to use Real-Time Audiences

Real-time audiences are best for reactive, intent-driven triggers where seconds or minutes matter. These audiences use streaming data ingested directly into mParticle and update in real time. For example:

• Cart abandonment: Reach out within 60 minutes of a user abandoning their cart.
• Flight delay notifications: Send travel alerts when an itinerary changes.
• Streaming engagement: Promote more content immediately after a subscriber finishes a show.

If the value of your engagement depends on acting while intent is fresh, real-time audiences are the right fit. See the Audiences Overview to get started with Real-Time Audiences.

Setting up Composable Audiences

Before you can start building audiences, there are two parts to the setup process:

1. Warehouse setup: This step is typically done by a data engineer or database administrator. It includes:

   • Connecting mParticle to your cloud data warehouse (Snowflake, BigQuery, Redshift, or Databricks).
   • Creating data models that define which warehouse tables and fields will be available in the Audience Builder.

2. Audience setup: Once the connection and models are in place, a marketer or analyst can:

   • Use the Audience Builder to define membership criteria based on the data models.
   • Connect the audience to downstream platforms like Google Ads, Facebook, or TikTok.

Together, these steps give you a zero-copy way to create audiences: your data stays in your warehouse, while mParticle queries it securely on your schedule to keep audience membership up to date.

To get started, go to the User Guide.

Hybrid Audiences

Hybrid Audiences allows you to include composable audience membership as a criteria when building a real-time audience. This is helpful when you have long-term customer data stored in your cloud warehouse, like account information, LTV, or churn risk, that you want to reference from a real-time audience built on in-the-moment behavioral data such as product views and cart activity. Hybrid audiences also enable you to optionally persist composable audience membership on user profiles in mParticle as well as optionally enrich outbound composable audience data with user profile data from mParticle.

To create a hybrid audience, you first create a user data model and configure it for hybrid usage. Then, a marketer can build a composable audience and enable it for hybrid usage so that mParticle records composable audience membership on user profiles stored in mParticle. You can then create a real-time audience that includes/excludes these users in the composable audience via the Audience Membership criterion in the Audience Builder. By including a composable audience membership criterion in your real-time audiences, you can combine rich warehouse data with in-the-moment activity in a single audience that powers more precise personalization, triggering, and suppression.

When to use Hybrid Audiences

Hybrid Audiences combines composable and real-time audiences so you can use long-term customer context stored in your warehouse with in-the-moment user behavior captured in mParticle in the same audience. Hybrid Audiences are most helpful when you want to:

• Target or reward high value customers in real time. For example, you can build a composable audience of high LTV or VIP customers as defined in your warehouse, then create a real-time audience that includes only those customers who are actively browsing, viewing key products, or adding items to their cart to be eligible for special offers or experiences.
• Engage at-risk customers based on live activity. For example, you can define a composable audience of customers with a high churn risk score as was calculated by your data science team and stored in your warehouse, then only trigger win-back campaigns through a hybrid audience when those customers return to your app, log in, or show renewed interest in pricing or plan pages.
• Control eligibility and suppression with account context plus behavior. For example, you can determine eligibility or suppression rules in your warehouse based on account status, plan, or loyalty tier, then create a real-time audience to only target eligible users who are actively engaged in the current session to receive specific messages, campaigns, or feature prompts.

Example hybrid audience: targeting high value customers who are actively browsing

For example, imagine that you want to reach customers who are both valuable over the long term (high LTV) and currently showing strong purchase intent. You could accomplish this with a hybrid audience built from:

• A composable audience built from cloud warehouse data that identifies high value shoppers based on metrics like predicted LTV or total spend.
• An in-platform, real-time audience that looks for in-session behavior, such as viewing a product detail page or adding an item to cart in the last 30 minutes.

How you would set this up

Step 1. Create the composable audience for high value shoppers

First, you must create a composable audience that can retrieve the user data needed from your warehouse.

1. Make sure your warehouse connection and data models are set up so you can query LTV and purchase history directly from your cloud data warehouse.
2. When you create the user data model that powers this audience, make sure to map your warehouse identifiers to your in-platform identifiers and confirm your identity settings. This makes the data model eligible for use in a hybrid audience, but the person creating the audience will also have to specify that they want their audience to be hybrid.
3. Create a new Composable Audience and add criteria, such as “High value shoppers (top 20% LTV)” that selects users whose predicted LTV or lifetime spend is above your chosen threshold. Check the box that says “Enable for Hybrid Audiences” to mark this audience as available for hybrid use cases.

Step 2. Create the real-time audience that references your LTV composable audience

Second, you create the real-time audience that will include members of your composable audience. This real-time audience is the “hybrid” audience.

1. Create a new in-platform real-time audience, for example “High value active browsers”.
2. Add behavioral criteria to capture in-session intent, such as users who have viewed a product detail page or added an item to cart within the last 30 minutes.
3. Add an Audience Membership criterion and select your composable audience “High value shoppers (top 20% LTV)” such that only users who are already in that audience can qualify.

Hybrid audiences are activated just like any other audience in mParticle. You connect them to your downstream destinations and use them for personalization, triggering, or suppression alongside your existing segments.

How is data from your warehouse processed?

When a composable audience initializes, mParticle translates your audience definition (the criteria that determine which users should be included in the audience) into a SQL query. This query is then executed directly within your data warehouse using your warehouse’s compute resources.

The SQL query returns a list of users and (optional) attributes that make up the audience at that particular point in time. This data is stored in a temporary table in your data warehouse that is provisioned for internal processing only. These datasets are not part of your production tables and are only used by mParticle to track audience membership over time. These additional datasets are automatically managed and cleaned up by mParticle.

mParticle pulls the users and any optional attribute data from your warehouse before forwarding them to your connected downstream integration.

When you create a composable audience, you specify the cadence at which it refreshes. Note that composable audiences can’t be refreshed in real-time.

Composable Audiences operates independently of mParticle’s identity resolution framework (IDSync). No user profile enrichment or merging takes place. Audience membership is based solely on the logic provided in the SQL query and the structure of the source data. This makes the feature highly transparent and deterministic, giving you full control over how your audiences are built and updated. It also means that the records in your data warehouse must include some form of user identifier (like a user ID or customer ID) that can be used when determining audience membership.

What data is stored in mParticle?

mParticle only stores the data needed to create and activate composable and hybrid audiences, including:

• Information needed to connect with, and authenticate to, your warehouse provider.
• Metadata about your warehouse database and tables, such as column names.
• If explicitly enabled, mParticle caches up to 1000 of the most frequent values from each column in your table for up to 7 days to power the autocomplete feature within the Audience Builder. You must enable autocomplete for each column included in your data model.
• If you create a composable audience and mark it as enabled for Hybrid use cases, mParticle stores audience membership on user profiles so that membership is visible in Customer 360, the User Activity View, via the Profile API, and in real-time audience criteria.

No other warehouse data is stored in mParticle beyond these items.

How are your user profiles modified?

By default, composable audiences do not modify user profiles in mParticle. Audience membership is calculated in your warehouse and forwarded to outputs without changing identities, profiles, attributes, or events in mParticle.

When you create a composable audience, mParticle will write audience membership to user profiles if the creator of the audience also marks their audience as “Enabled for Hybrid” during creation. This makes it possible to:

• View composable audience membership in Customer 360 , the User Activity View, and Profile API.
• Reference that membership from Real-Time Audiences via audience membership criteria.
• Enrich outbound Composable Audience data with additional data from user profiles in the CDP if a match can be found

Hybrid audiences do not write warehouse attributes, events, or identity changes back into user profiles in mParticle. Only audience membership state is reflected on the profile.

How are composable audiences refreshed?

To improve performance, mParticle only tracks changes in audience membership (specifically, the users who have been added to or removed from the audience) rather than recomputing the full list each time. The first time the audience is executed, the entire set of qualifying users is returned. For subsequent runs, mParticle compares the new audience snapshot with the previous one to determine which users have been added or dropped.

This “diff-ing” logic happens entirely within the data warehouse environment. Two snapshots of the audience (previous and current) are compared using SQL, and only the incremental changes are passed back into mParticle for forwarding to downstream integrations. This approach ensures both scalability and efficiency in audience refresh cycles.

Are composable audiences compatible with Real-Time mParticle Audiences?

Yes. Hybrid, composable, and real-time audiences can work together.

You create a user data model in your warehouse setup, making sure to map the identifiers from your warehouse to your in-platform identifiers and enabling them for use when matching users in your warehouse to in-platform profiles on the Identity Settings page of your user data model settings. You build a composable audience on top of that model and choose to make it enabled for hybrid use cases so that membership is written back to user profiles. You create a real-time audience that uses audience membership criteria to reference that composable audience.

This pattern lets you combine warehouse-modeled logic with in-session behavior without copying warehouse data into mParticle or rebuilding the same logic twice. Composable audiences still run on a scheduled cadence in your warehouse, and real-time audiences continue to update in real time.