Create an Audience

Creating an audience begins with defining your use case, segmentation approach, and engagement strategy. To do this, consider the following questions:

• What is the business goal you are trying to accomplish?
• Which customer segments are important to achieving this business goal?
• Once you identify the relevant users, what is your strategy for engaging them?

Example Use Cases

Increase User Retention for a Mobile App

Retaining users is crucial for the sustained success of a mobile application. By identifying and re-engaging inactive users, you can boost overall engagement and reduce user drop-off.

Goal: Improve user retention by targeting users who have not opened the app in the last 7 days.
Segmentation Strategy: Identify users who have been inactive for a week but used the app actively within the previous month.
Engagement Strategy: Send personalized push notifications offering a discount or exclusive content to re-engage users.

Predictive Audience for Likely Purchasers

Leveraging predictive analytics allows businesses to anticipate user behavior and proactively engage those most likely to convert, thereby optimizing marketing efforts.

Goal: Increase conversion rates by targeting users predicted to make a purchase in the next 7 days.
Segmentation Strategy: Utilize Predictive Audiences to identify users with a high likelihood of purchasing based on machine learning models analyzing past behaviors and interactions.
Engagement Strategy: Deliver personalized email campaigns featuring product recommendations or special offers to these high-likelihood purchasers.

Optimize Engagement in a Subscription Service

Identifying subscribers at risk of cancelling enables proactive engagement strategies to maintain a stable subscriber base.

Goal: Reduce cancellations by identifying at-risk subscribers.
Segmentation Strategy: Identify users whose subscription renewal is within the next 30 days and who have decreased engagement (e.g., fewer logins or interactions).
Engagement Strategy: Offer these users tailored incentives such as a loyalty bonus or a discounted renewal rate to encourage continued subscription.

Create a New Audience

Once you have clearly defined your use case, it’s time to begin building your audience.

Navigate to the Audience Creation Page

1. From the mParticle Overview Map, select Segmentation.
   
2. On the Audiences landing page, click Create New.
   

Configure Your Audience Group

Individual audiences are contained within folders called Audience Groups. The first step in creating a new audience is to set the configurations for this folder:

1. Enter a name for your folder.
2. Select your Inputs (the platforms and feeds that will supply data to define the audiences within your folder).
3. Click Create.

Define Your Audience

After saving your audience group, you’ll enter the Editor. Here is where you can add, view, edit, and connect audiences.

Follow the steps below to create your first audience within this folder:

1. Click the Add criteria box to open the Audience Builder Modal.

2. In the audience builder modal, choose the environment (Production, Development, or both) from which the audience will receive data. (Note the audience environment considerations below.)
3. Click Add Criteria to begin adding criteria for your audience.
4. Select the type of data you would like to use for your first criteria (more on criteria types below).
5. Referring to the data types and matching rules below, use the criteria editor to further target the users who fit your use case. .
6. Once you have added your first criteria, click Done.

After you have added your first criteria, a number displays that represents the estimated audience size: . This estimate is based on a sample of data. As you continue to add criteria, you will see an estimated size for both individual criteria as well as for the whole audience.

4. Continue adding more criteria using And, Or, or Exclude logic to further refine your audience.

Audience Refresh Frequency

The Refresh Frequency setting determines how often mParticle updates audience membership. Choosing the right refresh frequency ensures your audience membership is as current as necessary for your business use case.

mParticle offers two types of refresh frequencies:

1. Real-time – Audience membership is automatically updated as users either meet or no longer meet the audience criteria.
2. One-time – Audience membership is calculated only a single time, and does not refresh.

One-time Audiences

Setting an audience’s Refresh Frequency to Once creates a one-time audience: an audience that calculates its membership a single time and does not refresh on a recurring basis. One-time audiences are a good fit for large audiences built on long-term, historical data, where real-time or repeated updates aren’t necessary.

A one-time audience expires 30 days after the scheduled start date. Before it expires, you can continue to connect it to new outputs, and mParticle sends its already-calculated membership to each new connection (see Connect an Audience).

After a one-time audience expires:

• Its size shows as 0.
• It can no longer be downloaded.
• You can’t add new connections or enable Match Boost.
• You can’t edit its environment, refresh frequency, or starting date.

An expired audience displays the Expired status (see Audience Statuses). Expiration does not remove membership that was already written to user profiles, so a real-time audience that references the one-time audience’s membership is unaffected when the one-time audience expires.

Key Limitations

• Refresh type is permanent – You cannot switch an audience from real-time to once after creation. Delta processing – Only changes (users who newly qualify or no longer qualify) for realtime audiences are forwarded to connected outputs. For one-time audiences there will be no delta processing, because one-time audiences are only calculated a single time.
• Historical data loads - Data from historical data replays will not be reflected in one-time audiences. You must clone the audience and re-activate it to have the data from the historical load be available for audience processing.
• Audience groups can’t combine realtime and one-time audiences — You can’t create both realtime and one-time audiences within the same audience group.
• One-time audiences can’t reference realtime audiences - You can’t add membership criteria to a one-time audience that refers to membership of a realtime audience. The reverse is allowed: a realtime audience can reference membership of a onetime audience.
• One-time audiences must be the root audience of a group - A one-time audience can only be the top-level (root) audience in its group. It can’t be nested as a child audience within an audience group.

Audience Preview

After defining your audience criteria, you can use the Preview tab to inspect a sample of users that match your current segmentation. Audience Preview helps validate audience composition before activation, reducing errors and improving targeting accuracy.

How to Use Audience Preview

1. Navigate to the Preview tab in the audience editor.
2. View a list of sample users that meet your audience criteria:

3. Each row in the preview includes:

   • mParticle ID – A unique identifier for each sampled user.
   • Last Seen – The most recent interaction timestamp.
4. Click on a user’s mParticle ID to open their User Profile for deeper insights.

Audience Preview enables quick validation of audience logic, ensuring that the right users are included before activation.

Audience Insights

The Insights tab in the audience builder helps you understand an audience both before and after activation. It provides visibility into how an audience’s membership changes over time, an audience’s potential reach, the distribution of attributes in an audience, and how much an audience overlaps with other audiences in your account. These insights can help improve the users you’re targeting to ensure your audience meets your business goals.

To view insights for an audience, navigate to Segmentation > Audiences, select an audience, and go to the Insights tab.

Analysis status

At the top of the Insights tab you can find an overview of when the audience insights were last updated, the sample size used to calculate the different metrics, and how much historical data is available.

• Insights last update (UTC): The timestamp of the most recent analysis run. Insights refresh on a schedule rather than in real time:

  • Active audiences: Recalculations happen automatically once per day.
  • Inactive audiences: Recalculations happen whenever you modify the audience.

• Analysis results: The precision of the metrics shown.

  • Until you activate an audience, insights are estimates based on a small sample of your audience data and are labeled Estimate.
  • Once you activate the audience, or save it without activating it, insights are regenerated using a larger sample size and are labeled Precise.
• Historic data: How many days of historical data are available for the charts in the Insights tab. Longer date ranges and the Audience Health forecast become more meaningful as more history accumulates.

Historical data accumulates from the last time you edited the audience definition: each change to the membership criteria in the audience definition resets the historical data. For example, if you activate an audience and leave it unchanged for 30 days, Historic data shows 30 days and the insights display a 30-day historical trend. If you edit the criteria on day 31, metrics are calculated from that point forward. Inactive audiences don’t accumulate historical data, but you can still view insights based on the current definition.

Audience Health

The Audience Health section allows you to examine how your audience membership changes over time: how large the audience is, how fast it’s growing or shrinking, and where it’s likely headed next.

You can refer to this section to answer questions such as:

• Is this audience growing, stable, or declining in size?
• How many users join and leave the audience in a typical week?
• At what rate is the audience losing members, and is this rate changing over time?
• What size should I expect this audience to be over the coming weeks?

Audience Size

The Audience Size chart plots your audience membership across the selected date range. Use the 3 controls above the chart to change what it displays:

• Show Forecast: A toggle that projects the audience’s expected future size. See Forecast.
• Date range: A dropdown that sets the time window shown on the chart. Options include Today, 7 days, 15 days, 4 weeks, 8 weeks, 12 weeks, or a custom date range.
• Trend / Flux: A toggle that switches the chart between the Trend and Flux views described below.

The 3 cards above the chart summarize the audience at a glance. Each card shows a headline value plus the change compared to the previous period of the same length (for example, vs last 15 days), with an up or down arrow indicating the direction of change. Each card includes a help icon with an inline definition.

• Current size: The number of users who currently qualify for the audience, based on the most recent analysis.
• Net Change: The number of users added to or removed from the audience during the selected period.
• Net Change Rate: The relative number of users added to or removed from the audience during the selected period, expressed as a percentage of the total audience size. A lower Net Change Rate generally indicates a more stable audience.

Trend view

The Trend view is the default view for the Audience Health section, and shows an area chart that plots total audience size at each point across the selected window. The vertical axis is audience size and the horizontal axis is time, with a tick for each interval in the selected date range. Use the trend view to read the audience’s overall trajectory: whether it’s growing, holding steady, or declining.

Flux view

The Flux view is a grouped bar chart that shows movement in and out of the audience for each interval, rather than the running total. Each interval displays paired bars, labeled Entries and Exits, representing the users added to and removed from the audience during that period. Use the flux view to spot turnover and volatility that a stable total size can hide, such as an audience whose size looks flat but is actually cycling many users in and out each week.

Forecast

Turn on Show Forecast to project the audience’s expected size into the near future. mParticle draws the forecast as a continuation of the trend line, labeled Forecasted size, accompanied by a shaded 95% confidence range that widens the further out it projects. The historical portion of the line is labeled Actual.

• The forecast view requires a date range of at least 4 weeks. Select the 4 weeks, 8 weeks, or 12 weeks date range to enable it. The forecast view projects 4 weeks into the future.
• The flux view is disabled while the forecast view is on. The forecast applies only to the trend view’s total size line. Turn Show Forecast off to return to the flux view.

Overlaps

The Overlaps section shows how much the current audience overlaps with other audiences you’ve already created. Use it to avoid targeting the same users across multiple campaigns, identify redundant audiences, and find closely related segments.

A legend at the top of the section distinguishes the parts of each comparison: This audience, Other audiences, and the Overlap between them.

Use the 2 controls above the table to choose and order the comparisons:

• Compare audience: Select which audiences to compare against the current audience. Selected audiences appear as removable chips. By default, the 8 audiences with the highest overlap are shown. If fewer than 8 other audiences exist, all of them are shown.
• Sort by: Set the order of the table, for example Overlap: High to low.

Each row in the table compares the current audience against another audience:

Column	Description
Name	The name of the other audience being compared.
Overlap	A visual indicator of how much the audiences intersect.
Shared Users	The number of users who belong to both audiences.
Trends	The change in the overlap, with an up or down arrow.
Overlap (%)	The overlap expressed as a percentage in both directions: the share of this audience that’s also in the other audience, and the share of the other audience that’s also in this one. The 2 values use the legend colors.
Date Created	When the other audience was created.

Reach

The Reach section helps you assess the potential reach of your campaign across different user identifiers.

• Track identified users per identifier, such as mParticle ID, Customer ID, or Email Address
• View coverage percentages for each identifier
• Compare reach across multiple identification methods

If you select a timeframe other than Last 1 day, the bar chart is replaced with a line chart to represent your data over time.

Composition

The Composition section shows the distribution of different values of an attribute across your audience to understand your audience demographics and characteristics. Hover your cursor over each section of the pie chart to:

• See percentage breakdowns for each attribute
• Compare relative sizes of different user segments

To view user distribution according to a different attribute, use the dropdown menu to select the attribute. The composition view only includes single-value, non-numeric, non-calculated user attributes. Calculated attributes, list-type (multi-value) attributes, and attributes whose values are numeric are not available for selection.

Additionally, the composition view does not support selecting attributes with high cardinality: attributes that have a high number of unrepeated values. This includes attributes such as:

• First name
• Last name
• Phone number
• Email address
• Physical address
• Date of birth

For example, a pie chart displaying the many unique values of “First name” would not be very useful in comparison to a chart displaying a breakdown of your audience by “favorite genre”.

If you select a timeframe other than Last 1 day, the pie chart is replaced with a line chart to represent your data over time.

View reach and composition metrics over time

For the Reach and Composition metrics, you can add additional filters to understand how these metrics change over time.

For either reach or composition, select a timeframe and averaging interval. If no historical data is available to calculate audience metrics over time, these filters are disabled. Audience metrics over time are not available for overlaps.

Select a timeframe

Use the first dropdown above each chart to select how far back you want to view data for. Options include:

• Last 1 day
• Last 7 days
• Last 15 days
• Last 30 days
• Last 60 days
• Last 90 days

This determines the time window displayed in the chart.

If no data is available for a given time period within your selection, the line chart will display a dotted line to indicate the gap:

Data may be unavailable for one of the following reasons:

• The audience was inactive during that period.
• The period is earlier than the oldest available historical data.
• The period is earlier than the release of Audience Insights.

Choose an averaging interval

If you select a timeframe greater than Last 1 day, a second dropdown appears allowing you to change the averaging interval. Options include:

• Daily (average)
• Weekly (average)
• Monthly (average)

This setting smooths out fluctuations and makes it easier to identify broader audience trends.

Precise vs. Estimated Audience Sizes

Throughout the Audience creation process, you will see both preliminary and precise audience sizes.

Preliminary Estimates

Preliminary estimates are displayed before the audience has been fully calculated, and are denoted with a ~ character throughout the Audiences feature. When an Audience is created or edited, for example, preliminary estimates are shown to give an approximate idea of audience size.

Precise Estimates

Once an audience definition has been defined, a precise estimate will be displayed for that audience, even if it has not been explicitly activated or connected. It can take up to 15 minutes for the precise estimate to finish calculating. Waiting for the precise estimate is a more efficient option than activating the audience just to get a sense of its size. Precise estimates will display a cross-hairs icon wherever they are displayed throughout the segmentation experience:

Activate an Audience Without Connecting

The Activate Without Connecting feature allows you to manually activate an audience so that it calculates audience membership and updates user profiles, even if no outputs are connected. Common use cases for activating an audience without connecting it include:

• API-Access – Membership in an activated audience appears in user profiles and is retrievable via the Profile API.
• Testing and Troubleshooting – Before sending an audience to a downstream integration (e.g., Facebook or Braze), you may want to verify its size, composition, and updates to ensure accuracy and confidence in segmentation.
• Separation of Activation and Connection – You do not have to delete an audience to disconnect it from an output. This makes audiences more flexible and versatile, as you can preserve their definitions and criteria through the process of connecting and disconnecting outputs.
• Deactivate without Deleting – If an audience is no longer needed but it may be in the future, you can manually Deactivate it in the UI without deleting it. This preserves the audience definition for future use while stopping membership calculation and preventing further billing.

Audience Statuses

Audiences can exist in four states:

• Inactive – The default state when an audience is first created.
• Active – A manually activated audience, either through this feature or by connecting to an output. An audience with this state is actively calculating/processing audience membership changes.
• Calculated – A state where an audience is automatically activated by mParticle because other audiences depend on it. An audience with this state is actively calculating/processing audience membership changes. Calculated audiences are not charged from a billing perspective.
• Expired – Applies only to one-time audiences. A one-time audience automatically expires 30 days after the scheduled start date. After it expires, its size shows as 0, it can no longer be downloaded or connected to new outputs, and you can’t enable Match Boost or edit its environment, refresh frequency, or starting date. For more information, see one-time audiences.

Activate an audience: To activate an audience after it has been created (but before any outputs have been connected), click the three vertical dots in the top right of the audience tile, then select Activate.

Deactivate an audience: To deactivate an audience once it is activated, click the three vertical dots in the top right of the audience tile, then select Deactivate.

Considerations when activating audiences

• Billing Impact: Once an audience is activated and has an Active status, billing begins regardless of whether it is connected to an output or used for any specific action.
• A/B Audience Billing: Only audiences with an Active status consume a real-time credit, and an A/B Test uses one credit total, no matter how many variations are active.
• Sibling cascade: If an audience in a branch moves to Active status, mParticle will automatically transition any dependent sibling and parent audiences into the Calculated state.

Activate an Audience in a Campaign

Once you have created an Audience that you want to forward to an external tool for use in a campaign, click the Connect Output button in the Audience tile, then follow the steps to connect that audience to any of your connected outputs.

Main Criteria Types

You can build criteria based on two main sources of data:

Events

Event criteria check for specific events and their properties, and their availability is subject to the data retention policy of your account. Within the new criteria option in the audience builder, the following options create event-based criteria:

• Events
• Ecommerce
• Crashes
• Installs
• Uninstalls
• Sessions
• Upgrades
• Screen views

User Profiles

These criteria check your active user profiles, and their availability is subject to the user profile retention policies of your account. Within the new criteria option in the audience builder, the following options create profile-based criteria:

• Users: Access user profile information such as user attributes, calculated attributes, current audience memberships, consent state, location, etc.
• User Predictions: Predictive Attributes that you have defined and generated for your users.
• Attribution: Access user install and uninstall information to build criteria based on the attributed campaign and publisher.

Data Types and Matching Rules

Audience criteria can be created with several different data types, each with its own matching rules.

Strings

When building audiences based on string attributes, several case-insensitive matching rules can be applied:

• Contains / Does Not Contain: Matches substrings. For example, "blue" matches both "blue" and "blue shirt".
• Exact Match / Does Not Match: Requires the entire string to match. For example, "blue" matches "blue", but not "blue shirt".
• Pattern: Allows wildcard matching. * represents any number of characters, and ? represents any single character. For example, "bl?e" or "b*e" would both match "blue".
• Includes / Does Not Include: Matches an exact value within a list. For example, specifying "Chicago" in a list of movies returns "Chicago (2002)" and "Chicago (1927)", but not "Chicago Cubs".
• Partial Match: The inverse of Includes. For example, specifying "Chicago" would return all movies with "Chicago" in the title.

Date-Based Criteria

Filters based on fixed calendar dates. For example, events occurring after 09/12/2018. Date-based criteria are defined in UTC and are not relative to when the audience is calculated:

• Before: Excludes the specified date. For example, “Before September 9, 2018” includes events up to 11:59 PM UTC on September 8.
• After: Includes the specified date. For example, “After September 9, 2018” includes events from 12:00 AM UTC on September 9.
• On Date: Covers events from 12:00 AM to 11:59 PM UTC on the specified date.
• Between Dates: Includes events from the start of the first date to the end of the second date.

Recency-Based Criteria

Defines a period relative to the current time. For example, users active within the last 7 days. Recency-based criteria select events occurring within a timeframe relative to ‘now’.

• For example, if calculated at 1:00 PM on September 9, 2018, a recency filter for the last 7 days includes events between 1:00 PM on September 3 and 1:00 PM on September 9.

Attribution

Attribution criteria segment users based on campaign interactions, such as app installs or re-engagements.

• Profile Criteria: Select Attribution, then choose Install or Uninstall to filter based on campaign and publisher fields from attribution events.
• Event Criteria: Select Events > Attribution to use install or engagement events, filtering by event attributes. This allows you to select any information included with the event as custom_attributes.

Note: All event criteria are subject to audience event retention limits.

Identity

Identity criteria segment users based on their stored identities. You can test for the existence of a specific identity or apply string-based logic. These criteria are scoped to the workspace in which the audience is created. For example, if your account has three workspaces, an audience in one workspace only includes users active in that workspace.

Location

Location criteria allow segmentation based on geographic information.

• Equals: Filter users in a specific city, state, zip code, or DMA (Designated Market Area), based on IP geolocation.
• Within: Filter users within a set distance of a global city using latitude and longitude coordinates.

Cart

For ecommerce events, you can target users who added items to their cart but did not complete a purchase.

• Cart Abandonment: Select New Criteria > Ecommerce > Shopping - Cart Level > Cart Abandonment to define this segment.
• Specify the time period to wait without a purchase before including users in this audience.

Attribute Key

Use Exists or Not Exists to check for the presence of an attribute.

• For example, User Attribute: Gender EXISTS evaluates as true for both Gender = "Female" and Gender = undefined.

Additional Audience Features

Hybrid Audiences

Hybrid Audiences allows you to combine a composable audience that runs in your warehouse with real-time criteria in the Audience Builder. At a high level, you start with a composable audience that has been enabled for Hybrid Audiences, then reference that audience as part of your real-time criteria.

When a composable audience is enabled for Hybrid Audiences, mParticle matches each warehouse user to their mParticle profile using the identities configured in the underlying data model (such as email or customer ID). For each user where a match is found, mParticle records that user as a member of the audience on their profile. This is what makes composable audience membership available as a criterion in the Audience Builder.

Before you begin, make sure that:

• Your composable audience is built on a user data model where Enable this Data Model for Hybrid Audiences is turned on. This tells mParticle which identities to use when looking up mParticle profiles for warehouse users.
• The composable audience has Audience Membership Settings set to Enable for Hybrid Audiences, and the audience has been activated so that membership is written to user profiles.

To create a hybrid audience in the Audience Builder:

1. Follow the steps above to create a real-time audience and open the Audience Builder.
2. Click Add criteria, then choose Users to add profile-based criteria.
3. In the criteria editor, select Audience Membership and choose the composable audience you want to reference. This limits your audience to users who are also members (or not) of that composable audience.
4. Add additional criteria as needed, such as recent events, recency windows, or user attributes, to refine your real-time logic.
5. Click Done when you have finished adding criteria, then continue configuring and activating the audience as you would for any other real-time audience.

Hybrid audiences you create this way are activated and connected to outputs in the same way as other real-time audiences. You can learn more about hybrid audiences in the Composable Audiences Overview.

Auto-complete

As you define your audience criteria, a list of suggested matching values will appear based on what you’ve entered.

This feature works both when building new audiences and fine-tuning existing ones, helping you save time, reduce manual effort, and improves accuracy. To use it, you must have one of the following standard Roles: User, Admin, Audiences-only, Support, or Admin+Compliance. Alternatively, you can create a Custom Role with any of the following tasks: audiences:draft, audiences:edit, catalog, or audiences.

Boolean operators

Once you have added criteria, you can use the Boolean operators And, Or, and Exclude to create logical relationships with subsequent criteria.

Audience Environment Considerations

Be mindful of your selected audience environment:

• Use Production for real customer data to prevent test data from overwriting profiles in partner systems.
• Ensure parent and child audiences share the same environment. If environments differ, child audiences will not inherit users from their parent.

Audiences in Development display a badge in the Audience Group Editor, while Production audiences do not.

By following these steps and best practices, you can build and activate audiences that align with your business objectives, enabling more targeted user engagement and monetization strategies.