Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
Accounts
Apps
Audiences
Calculated Attributes
Data Points
Feeds
Field Transformations
Services
Users
Workspaces
Warehouse Sync API Overview
Warehouse Sync API Tutorial
Warehouse Sync API Reference
Data Mapping
Warehouse Sync SQL Reference
Warehouse Sync Troubleshooting Guide
ComposeID
Warehouse Sync API v2 Migration
Bulk Profile Deletion API Reference
Calculated Attributes Seeding API
Data Planning API
Custom Access Roles API
Group Identity API Reference
Pixel Service
Profile API
Events API
mParticle JSON Schema Reference
IDSync
AMP SDK
Initialization
Configuration
Network Security Configuration
Event Tracking
User Attributes
IDSync
Screen Events
Commerce Events
Location Tracking
Media
Kits
Application State and Session Management
Data Privacy Controls
Error Tracking
Opt Out
Push Notifications
WebView Integration
Logger
Preventing Blocked HTTP Traffic with CNAME
Linting Data Plans
Troubleshooting the Android SDK
API Reference
Upgrade to Version 5
Cordova Plugin
Identity
Direct URL Routing FAQ
Web
Android
iOS
Initialization
Configuration
Event Tracking
User Attributes
IDSync
Screen Tracking
Commerce Events
Location Tracking
Media
Kits
Application State and Session Management
Data Privacy Controls
Error Tracking
Opt Out
Push Notifications
Webview Integration
Upload Frequency
App Extensions
Preventing Blocked HTTP Traffic with CNAME
Linting Data Plans
Troubleshooting iOS SDK
Social Networks
iOS 14 Guide
iOS 15 FAQ
iOS 16 FAQ
iOS 17 FAQ
iOS 18 FAQ
API Reference
Upgrade to Version 7
Getting Started
Identity
Upload Frequency
Getting Started
Opt Out
Initialize the SDK
Event Tracking
Commerce Tracking
Error Tracking
Screen Tracking
Identity
Location Tracking
Session Management
Initialization
Content Security Policy
Configuration
Event Tracking
User Attributes
IDSync
Page View Tracking
Commerce Events
Location Tracking
Media
Kits
Application State and Session Management
Data Privacy Controls
Error Tracking
Opt Out
Custom Logger
Persistence
Native Web Views
Self-Hosting
Multiple Instances
Web SDK via Google Tag Manager
Preventing Blocked HTTP Traffic with CNAME
Facebook Instant Articles
Troubleshooting the Web SDK
Browser Compatibility
Linting Data Plans
API Reference
Upgrade to Version 2 of the SDK
Getting Started
Identity
Web
Alexa
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Step 9. Test your local app
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Step 1. Create an input
Step 2. Create an output
Step 3. Verify output
Node SDK
Go SDK
Python SDK
Ruby SDK
Java SDK
Introduction
Outbound Integrations
Firehose Java SDK
Inbound Integrations
Compose ID
Glossary
Data Hosting Locations
Migrate from Segment to mParticle
Migrate from Segment to Client-side mParticle
Migrate from Segment to Server-side mParticle
Segment-to-mParticle Migration Reference
Rules Developer Guide
API Credential Management
The Developer's Guided Journey to mParticle
Create an Input
Start capturing data
Connect an Event Output
Create an Audience
Connect an Audience Output
Transform and Enhance Your Data
The new mParticle Experience
The Overview Map
Introduction
Data Retention
Connections
Activity
Live Stream
Data Filter
Rules
Tiered Events
mParticle Users and Roles
Analytics Free Trial
Troubleshooting mParticle
Usage metering for value-based pricing (VBP)
Introduction
Sync and Activate Analytics User Segments in mParticle
User Segment Activation
Welcome Page Announcements
Project Settings
Roles and Teammates
Organization Settings
Global Project Filters
Portfolio Analytics
Analytics Data Manager Overview
Events
Event Properties
User Properties
Revenue Mapping
Export Data
UTM Guide
Data Dictionary
Query Builder Overview
Modify Filters With And/Or Clauses
Query-time Sampling
Query Notes
Filter Where Clauses
Event vs. User Properties
Group By Clauses
Annotations
Cross-tool Compatibility
Apply All for Filter Where Clauses
Date Range and Time Settings Overview
Understanding the Screen View Event
Analyses Introduction
Getting Started
Visualization Options
For Clauses
Date Range and Time Settings
Calculator
Numerical Settings
Assisted Analysis
Properties Explorer
Frequency in Segmentation
Trends in Segmentation
Did [not] Perform Clauses
Cumulative vs. Non-Cumulative Analysis in Segmentation
Total Count of vs. Users Who Performed
Save Your Segmentation Analysis
Export Results in Segmentation
Explore Users from Segmentation
Getting Started with Funnels
Group By Settings
Conversion Window
Tracking Properties
Date Range and Time Settings
Visualization Options
Interpreting a Funnel Analysis
Group By
Filters
Conversion over Time
Conversion Order
Trends
Funnel Direction
Multi-path Funnels
Analyze as Cohort from Funnel
Save a Funnel Analysis
Explore Users from a Funnel
Export Results from a Funnel
Saved Analyses
Manage Analyses in Dashboards
Dashboards––Getting Started
Manage Dashboards
Dashboard Filters
Organize Dashboards
Scheduled Reports
Favorites
Time and Interval Settings in Dashboards
Query Notes in Dashboards
User Aliasing
The Demo Environment
Keyboard Shortcuts
Analytics for Marketers
Analytics for Product Managers
Compare Conversion Across Acquisition Sources
Analyze Product Feature Usage
Identify Points of User Friction
Time-based Subscription Analysis
Dashboard Tips and Tricks
Understand Product Stickiness
Optimize User Flow with A/B Testing
User Segments
IDSync Overview
Use Cases for IDSync
Components of IDSync
Store and Organize User Data
Identify Users
Default IDSync Configuration
Profile Conversion Strategy
Profile Link Strategy
Profile Isolation Strategy
Best Match Strategy
Aliasing
Overview
Create and Manage Group Definitions
Introduction
Catalog
Live Stream
Data Plans
Blocked Data Backfill Guide
Predictive Attributes Overview
Create Predictive Attributes
Assess and Troubleshoot Predictions
Use Predictive Attributes in Campaigns
Predictive Audiences Overview
Using Predictive Audiences
Introduction
Profiles
Warehouse Sync
Data Privacy Controls
Data Subject Requests
Default Service Limits
Feeds
Cross-Account Audience Sharing
Approved Sub-Processors
Import Data with CSV Files
CSV File Reference
Glossary
Video Index
Single Sign-On (SSO)
Setup Examples
Introduction
Introduction
Introduction
Rudderstack
Google Tag Manager
Segment
Advanced Data Warehouse Settings
AWS Kinesis (Snowplow)
AWS Redshift (Define Your Own Schema)
AWS S3 Integration (Define Your Own Schema)
AWS S3 (Snowplow Schema)
BigQuery (Snowplow Schema)
BigQuery Firebase Schema
BigQuery (Define Your Own Schema)
GCP BigQuery Export
Snowflake (Snowplow Schema)
Snowplow Schema Overview
Snowflake (Define Your Own Schema)
Aliasing
Although processing and forwarding event data is a core function of mParticle, we are not just an integration platform. Our goal is to help you develop a complete view of your users, across all of your data sources, and make that view available wherever it is needed. The user profile is central to this goal.
An mParticle user profile represents a complete picture of what you’ve learned about a given user over time, across all of your channels, continuously updated and maintained in real time as you capture new data.
Within mParticle, user profiles serve four core functions:
Use profiles in mParticle to understand users and create personalized experiences:
Inspect the profile for any user in the mParticle UI via the User Activity View. To find user profiles, you can search by any user identity type you capture, or by the mParticle ID. You can also navigate to the User Activity View for active users in your development environment by inspecting a batch in the Live Stream.
For more information, see User Activity.
Profile enrichment allows mParticle to make sure that each of your downstream systems has the most complete and up-to-date information about each of your users. For example, mParticle receives data as batches from native SDKs, our HTTP API and third-party data feeds. Each batch is a JSON object containing an array of events and contextual information about the user, such as identities, user attributes, and device information. mParticle processes the information in each batch and forwards it to downstream systems through event integrations. Before a batch from a particular source is forwarded, mParticle compares it to the matching user profile and adds additional information.
If you collect the same user attribute from multiple sources, for example an iOS app and a web app, mParticle accepts the most recent version. For example, if Bob sets his favorite drink to “Beer” in the web app, and then changes it to “Coke” in the iOS app the next day, Bob’s user profile will use the most recent value for enrichment.
Enrichment ensures that all of your downstream tools can receive complete and accurate information about your users. Remember that you can still use data filters to prevent downstream systems from receiving user attributes that they don’t need.
The mParticle user profile can be delivered in JSON format by the Profile API, in order to deliver personalized experiences based on user attributes or audience memberships. To request a profile from the API, supply either the corresponding MPID or a specially configured immutable ID (usually the Customer ID).
For more information, see Profile API.
Audiences allow you to define segments of users based on rule based criteria of their event behavior and profile data. mParticle builds and maintains these segments of users over time which can then be connected to hundreds of outputs for activation.
Audiences and Calculated attributes are built from all your profile data, including calculated attributes, and events that have been collected across all your data sources. For real-time audiences, these are within the audience look back window. Standard audiences utilize your extended Data Retention policy. For more information about data retention, see Data Retention.
For more information, see Audiences and Calculated Attributes.
Two main classes of data provide context about your users and the events they trigger.
User data
User data describes the attributes of individual user profiles. It includes information such as what identities they have, device types and IDs, and a number of custom attributes such as membership status and demographic information. An attribute can reflect either current or previous values, depending on its nature and how often it is updated. User data is stored in profiles.
Event data
Event data describes actions that your users take. They contain information current for the moment at which the event was triggered. For example, the event “Sign up” could have an event attribute of “membership tier”, which denotes the membership status at time of signing up. Event data is stored in events.
Each profile describes useful details about the user associated with the profile.
A user profile contains the following elements:
mParticle ID - a unique identifier for the user within mParticle
The most recently seen IP address associated with the user
X-Forwarded-For
header for client SDK batches or the ip
field for batches ingested from server-to-server connections. The IP address on a user profile is only forwarded to connected outputs if the Enrich IP Address
setting is available and enabled for the connection.For each workspace the user has been seen in:
For each device the user has been seen on:
More about the mParticle schema can be found here.
Most of the time, mParticle automatically keeps user profiles updated as you capture new data with any of the following methods:
setUserAttribute
SDK methodHowever, sometimes it is necessary to make direct updates to your user profiles in bulk. This happens most often when you’re loading large amounts of data from legacy systems.
To directly update a profile, you can make a standard request to our HTTP API, and leave out the events
node. For example:
{
"user_identities" : {
"email": "john.smith@example.com",
"customerid": "JohnSmith911"
},
"user_attributes" : {
"skill_level": 9,
},
"deleted_user_attributes" : [
"color_preference"
],
"environment": "production"
}
User attributes updated in this way will not be immediately updated in all downstream event integrations. Most event integrations in mParticle will not process a batch with no events. However, as long as you are sending some event data to each integration, the enrichment process will make sure that user attributes are updated the next time an event is sent for each user.
If it is important for profile updates to be reflected across all your systems immediately, add an event to the batch. For example:
{
"events": [
{
"data": {
"event_name": "Attributes Updated",
"custom_event_type": "other"
},
"event_type": "custom_event"
}
],
"user_identities" : {
"email": "john.smith@example.com",
"customerid": "JohnSmith911"
},
"user_attributes" : {
"skill_level": 9,
},
"deleted_user_attributes" : [
"color_preference"
],
"environment": "production"
}
For a given user, attributes are stored at the workspace level, not the device level.
User attributes are ingested according to the following priority:
Once ingested from a particular source type, subsequent source types for that same data won’t be ingested. For example, once you set a user attribute key value using the Web SDK, you won’t be able to set that same key value from a Custom CSV or partner data feed.
You can override the default behavior for input feeds, and specify whether data ingested from a feed creates new profiles or updates existing profiles. Choose from one of three input protection levels:
The default profile protection level for all input feeds is Create & Update.
Profile protection levels are specific to each input configuration, providing more granular control over multiple configurations even if they are contained in a single workspace.
When ingesting user data from an input, mParticle searches for an existing profile that corresponds with any of the user identifiers included with the data. The identity strategy configured for your account determines if a new profile is created when an existing profile can’t be found.
You can prevent unwanted changes by defining one or more input protections.
To set the protection level for an existing input:
When creating a new input feed, you are given the input protection dropdown menu, allowing you to set the protection level for that input from the start.
This setting removes all restrictions from an input’s access to a user profile, meaning that new user profiles can be created and modified as data is ingested.
For example, if mParticle receives data from the input that it can’t associate with an existing profile and your account uses the default identity strategy, then it creates a new profile for the user. If a matching profile was found, the data from the input enriches the found profile.
This setting ensures that only data from known, existing users in the workspace is ingested. If IDSync can’t find a matching profile (in other words, if the user is unknown) then the data is discarded. Only existing users within the workspace can be updated, and all other unknown users are ignored.
For example, if mParticle receives data from the input that it can’t associate with an existing profile and your account uses the default identity strategy, mParticle will not create a new profile for the user and the data will not be associated with an MPID. However, if a matching profile was found, then the user data from the input enriches the found profile.
If an event batch includes user data with an MPID or user identifiers that don’t resolve to an existing MPID in your mParticle workspace, mParticle will drop the data and it will not be forwarded to any outputs. However, this is still a billable event due to the processing needed when searching for a matching MPID in your workspace.
Imagine you have a business with a large customer base, but multiple storefronts or customer touch-points. These various touch-points are housed under separate brands and any one customer engages with many of them.
Furthermore, you have chosen to use a centralized data warehouse to help keep your customer data consolidated.
However, you want to ingest customer data into mParticle from your warehouse while maintaining a single user profile for each customer. To do this, you must prevent new profiles from being created. This is where the Only Update protection level is useful.
By setting your data warehouse input feed to Only Update, mParticle ensures that as new data for a known customer is ingested, that data is attributed to a single user profile. Without this protection, it would be possible for a separate user profile to be created for each of your brands a customer engages with. This would prevent you from maintaining a holistic perspective of your customers’ history.
Prevents all write access to profiles and IDSync. Event batches are ingested normally, but existing profiles can’t be modified and new profiles can’t be added to protect user profiles and IDsync records from undesired modifications from the input.
For example, if mParticle receives data from the input that it can’t associate with an existing profile and your account uses the default identity strategy, then it will not create a new profile for the user and the data will not be associated with an MPID. If a matching profile was found, mParticle will not associate the data with the found profile.
If an event batch includes user data with an MPID or user identifiers that don’t resolve to an existing MPID in your mParticle workspace, mParticle ingests and forwards the event batch to other outputs, but it will not create a new profile for the MPID.
Keeping your customer data clean and uncontaminated is critical. However, it’s also essential to be able to test new connections from your data warehouses to mParticle.
To configure and test a new input feed from a warehouse without allowing any ingested data to modify your existing customer profiles, you can set the initial protection level for the new feed to Only Read. This allows you to verify that data is ingested properly, without any of that data leading to the modification or creating of new user profiles.
After you’re confident in your new input configuration, you can change the protection level to allow data from that input to begin enriching profiles.
Profiles are available for different periods of time, depending on the data retention policy for your account.
The Professional Services team at mParticle provides the following guide for enriching your user profiles with UID2 for more effecive activation through The Trade Desk and others. If you have further questions while implementing the guide, please reach out to your Professional Services contact or account manager.
This guide references resources that can be found on GitHub. There you will find source code and supporting files for a serverless application that you can deploy with AWS’s serverless Application Model Command Line Interface (SAM CLI). It includes the following files and folders:
Was this page helpful?