Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
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Apps
Audiences
Calculated Attributes
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Users
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Warehouse Sync API Overview
Warehouse Sync API Tutorial
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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
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Events API
mParticle JSON Schema Reference
IDSync
AMP SDK
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Kits
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Upgrade to Version 7
Getting Started
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Getting Started
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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
Step 1. Create an input
Step 2. Create an output
Step 3. Verify output
Node SDK
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Python SDK
Ruby SDK
Java SDK
Introduction
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Compose ID
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Glossary
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
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Events
Event Properties
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UTM Guide
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Apply All for Filter Where Clauses
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Understanding the Screen View Event
Analyses Introduction
Getting Started
Visualization Options
For Clauses
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Calculator
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Frequency in Segmentation
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Save Your Segmentation Analysis
Export Results in Segmentation
Explore Users from Segmentation
Getting Started with Funnels
Group By Settings
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Interpreting a Funnel Analysis
Group By
Filters
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Manage Analyses in Dashboards
Dashboards––Getting Started
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Query Notes in Dashboards
User Aliasing
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Compare Conversion Across Acquisition Sources
Analyze Product Feature Usage
Identify Points of User Friction
Time-based Subscription Analysis
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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
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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
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Feeds
Cross-Account Audience Sharing
Approved Sub-Processors
Import Data with CSV Files
CSV File Reference
Glossary
Video Index
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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
mParticle collects data from all of your platforms and data connections and uses it to resolve customer identities and stitch together customer profiles. It also makes this data available to be forwarded to downstream systems, and retains it in long-term data stores that allow you to run data replays with help from mParticle Support.
By default, mParticle makes all data available for evaluation. However, many events and the data related to them may not be needed for running data replays or evaluations depending on how you use Audiences or Calculated Attributes. With Tiered Events, you can choose to collect data but not store it, or to collect and store data but not evaluate it.
These configurations help improve performance for all customers, and may provide cost savings for value-based pricing customers.
mParticle provides three event tiers. All three tiers support ingestion and forwarding of data, but provide different levels of support for storage and evaluation:
The following table can help you decide which tier to apply to data:
Feature |
Personalize | Preserve | Connect |
---|---|---|---|
Event data | ✓ | ✓ | ✓ |
Profile enrichment | ✓ | ✓ | ✓ |
Ingest | ✓ | ✓ | ✓ |
Forward | ✓ | ✓ | ✓ |
Store for data replays and backfills | ✓ | ✓ | |
Evaluate for calculated attributes | ✓ | ||
Evaluate for real-time audience | ✓ |
If your account uses value-based pricing, you can change the default event tier for ingested events.
There are two ways to modify your event tiers:
Before you modify your event tiers using either method, ensure the following prerequisites are met:
Verify that the consequences of changing tiers are acceptable in your environment:
To change the event tier using the UI:
You can make bulk modifications to your event tiers by downloading a copy of your Event Volume Report, entering your new tiers in the New Event Tier column in the downloaded file, and then re-uploading your new report to commit your changes in mParticle.
To make bulk changes to your event tiers:
Under Select Event Volume Data Range, use the date picker to select one of the date range presets or enter a specific date range to include in your Event Volume Report.
Open the Event Volume Report downloaded to your computer. Find the row for each event type you want to change the tier for, and enter the tier in the New Event Tier column. Make sure to save your changes.
Connect
, Preserve
and Personalize
.By default, mParticle assigns all event types to the Personalize tier. However, you can change the default assignment to Preserve or Connect if your account uses value-based pricing.
Changing the default tier is helpful. For example, if you create a data plan with many new event types and most of them won’t be needed for real-time evaluations, you could assign them to the Preserve or Connect tier by default.
To change the default event tier for a workspace:
After you set a default tier, all new events of all types seen in mParticle are assigned the new default tier. You can override the default tier assignment of an event type in Data Master > Catalog. For example, you could change the default tier to Connect in the workspace setting and also set the tier for event type MyEvent to Personalize. Then, all new and existing events of type MyEvent are assigned the Personalize tier, while all other new events are given the new default, Connect.
The event volume report, accessible from Data Master > Catalog, is a CSV file that lists all the events used in calculated attributes and audiences. It also shows data volumes for the time range you specify.
The Event Volume Report displays an approximate count of each event type ingested from your inputs within a certain date range. You can use these metrics to identify event types to change to a different event tier, or event types to exclude from calculated attributes and audience definitions.
There are differences between the Event Volume Report and your Monthly Credit Usage Report, which is a record of the billable items you are charged for. To learn how billable items are calculated, see Usage metering for value-based pricing (VBP).
The two reports present different views of your data ingestion:
Following is a list of differences between the Event Volume Report and Monthly Credit Usage Report:
The Event Volume Report displays event tier assignments at the time the report is generated, but the Credit Usage Report displays event tier assignments for events at the time they were ingested and processed. For example, imagine the following scenario:
Screen View
event type in the Connect
event tier.Screen View
from Connect
to Preserve
and you ingest another one million events.Screen View
events in the Preserve
event tier. However, your Credit Usage Report will show one million events in the Connect
tier and one million events in the Preserve
tier.batch.SystemNotifications
, which could include events like ConsentGranted
and ConsentDenied
. However, automatically generated events are not included in the Monthly Credit Report, because they are not billable items.Events timestamped 72 hours prior to when they are ingested are not be reflected in the Event Volume Report.
February 21, 2022 at 10:00 UTC
. An Event Volume Report report created on February 21st will not reflect that event. However, it will be reflected in your Monthly Credit Report.Was this page helpful?