Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
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Calculated Attributes
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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
Custom Access Roles API
Data Planning API
Group Identity API Reference
Pixel Service
Profile API
Events API
mParticle JSON Schema Reference
IDSync
AMP SDK
Initialization
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Network Security Configuration
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IDSync
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Opt Out
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Preventing Blocked HTTP Traffic with CNAME
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API Reference
Upgrade to Version 5
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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
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Opt Out
Push Notifications
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Preventing Blocked HTTP Traffic with CNAME
Linting Data Plans
Troubleshooting iOS SDK
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iOS 14 Guide
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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
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Initialization
Configuration
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Location Tracking
Media
Kits
Application State and Session Management
Data Privacy Controls
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Opt Out
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Preventing Blocked HTTP Traffic with CNAME
Facebook Instant Articles
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API Reference
Upgrade to Version 2 of the SDK
Getting Started
Identity
Web
Alexa
Node SDK
Go SDK
Python SDK
Ruby SDK
Java SDK
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
Step 1. Create an input
Step 2. Create an output
Step 3. Verify output
Introduction
Outbound Integrations
Firehose Java SDK
Inbound Integrations
Compose ID
Data Hosting Locations
Glossary
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
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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
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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 (Snowplow Schema)
AWS S3 Integration (Define Your Own 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
You can import bulk data, both user attribute and events, from your data warehouse or legacy system using comma separated values (CSV) files. You can use this technique in all regions and with all outputs.
Use the following process to load user attribute or event data from CSV files:
Prepare the CSV files for import. Files must follow the guidelines in this section.
Files must be sent in one of the following formats:
.csv
).zip
).csv.gz
)..gpg
appended, for example, .csv.gpg
or .csv.gz.gpg
). Only encrypted OR unencrypted files can be accepted, but not both. You must use PGP encryption with mParticle’s public key. See Encrypted files for additional instructions.File name requirements:
-custom_event.csv
-commerce_event.csv
-screen_view.csv
-eventless.csv
for eventless uploads of user identities and attributes Column names: specify fields according to our JSON Schema, using dot notation.
environment
set to development
or production
. If an environment
column is not included, data is ingested into the production environment.User and Device IDs: as with any data sent to mParticle, you must include a column with at least one user ID or device ID.
Device IDs
device_info.android_advertising_id
device_info.android_uuid
device_info.ios_advertising_id
device_info.att_authorization_status
device_info.ios_idfv
device_info.roku_advertising_id
device_info.roku_publisher_id
device_info.fire_advertising_id
device_info.microsoft_advertising_id
User IDs
mpid
user_identities.customerid
user_identities.email
user_identities.facebook
user_identities.microsoft
user_identities.twitter
user_identities.yahoo
user_identities.other
user_identities.other2
user_identities.other3
user_identities.other4
User attributes:
If you include user attributes, for each, include a column named as user_attributes.key
, where key is a user attribute key. For example:
user_attributes.$FirstName
user_attributes.communication_preference
user_attributes.Member Tier
Attribute names with spaces are allowed and do not require quotes. All the keys listed in the JSON Reference are supported.
Events:
events.data.timestamp_unixtime_ms
to set the event time.events.data.custom_attributes.key
, where key is an event attribute key, to set custom event attributes.events.data.screen_name
if you want to include the screen name.events.data.event_name
and events.data.custom_event_type
to include custom events.Commerce events: use columns with the following names for commerce events.
events.data.product_action.action
events.data.product_action.products.id
events.data.product_action.products.name
events.data.product_action.products.category
events.data.product_action.products.brand
events.data.product_action.products.variant
events.data.product_action.products.position
events.data.product_action.products.price
events.data.product_action.products.quantity
events.data.product_action.products.coupon_code
events.data.product_action.products.added_to_cart_time_ms
events.data.product_action.products.total_product_amount
events.data.product_action.products.custom_attributes
Only one product per event can be included for commerce events uploaded via CSV.
Data types:
All data in the CSV is converted to a string. The only exceptions to this are values that require a particular data type, such as MPID or IDFA.
mParticle maintains an SFTP server where you will drop your CSV files. Use the following instructions to securely retrieve your credentials and find the hostname and path to use when you drop your files on the SFTP server.
To get your SFTP username and password:
Configure the Custom CSV Feed as input. This step provides the hostname and folder path on the SFTP server where your CSV files must be dropped.
To configure the Custom CSV Feed:
Visit SETUP > Inputs > Feeds in the mParticle UI and click the Add Feed Input button, then select Custom CSV Feed from the list.
If you’ve already added the Custom CSV Feed, it won’t show up in the list. Scroll through the list of feeds until you see Custom CSV Feed, and then click the large plus sign in the gray bar to create a new feed. You need one feed for each different event type.
Enter the following values:
drop
folder. If you don’t see one, create a folder named drop
.drop
folder, and name it using the pathname provided in the mParticle UI as shown in the previous section. For example, based on the previous example, the folder path and name is sftp.mparticle.com:4422:drop/us1-123456789123456789/
. Hint: Verify that there are no trailing spaces in the name.Files on the SFTP location are added to the processing queue nearly immediately. Depending on file count and file size, a backlog may develop. You can observe how much data has been processed using Data Master and your outbound connections. There is no notification of processing progress or completion.
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