Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
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ComposeID
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IDSync
AMP SDK
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Web
Android
iOS
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Identity
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Upgrade to Version 7
Getting Started
Identity
Upload Frequency
Getting Started
Opt Out
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Event Tracking
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Identity
Location Tracking
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Getting Started
Identity
Initialization
Configuration
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Location Tracking
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Kits
Application State and Session Management
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Preventing Blocked HTTP Traffic with CNAME
Facebook Instant Articles
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Browser Compatibility
Linting Data Plans
API Reference
Upgrade to Version 2 of the SDK
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
Go SDK
Python SDK
Ruby SDK
Java SDK
Introduction
Outbound Integrations
Firehose Java SDK
Inbound Integrations
Compose ID
Data Hosting Locations
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
User Segment Activation
Welcome Page Announcements
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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
Organize Dashboards
Dashboard Filters
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 Audiences Overview
Using Predictive Audiences
Predictive Attributes Overview
Create Predictive Attributes
Assess and Troubleshoot Predictions
Use Predictive Attributes in Campaigns
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
Snowplow Schema Overview
Snowflake (Snowplow Schema)
Snowflake (Define Your Own Schema)
Aliasing
Segmentation is Analytics’ most popular customer analytics tool. It offers a simplified query builder to generate fast, meaningful results and create informative visualizations. Ask, answer, and act on the most important questions about your customers and their behaviors.
Within the query builder, you’re able to construct a complex data search using a variety of field types. Every Segmentation query begins with an event. Start by setting whether you’d like to calculate the total count of events or the number of users who performed a particular event.
Additionally, you may categorize your results by using the Group By function or narrow your search by using a Filter Where function.
The Group By and Filter Where function are akin to SQL “group by” and “where” clauses. You can use event properties, user properties or user segments with any event you select in your segmentation.
Event properties are tied to a single instance of an event
User properties can be chosen on any event regardless if it came in with an event since it’s part of the user’s profile.
User Segments cross check user identities from their segment memberships.
Finally, you can create a combination of events by using additional For Clauses (+Did [Not] Perform).
You can also run a Frequency query to group users into different segments based on the number of times they performed a particular event.
All queries within Analytics are fully customizable using Settings such as the date range and interval. Event queries may display results on a per-interval basis or as a cumulative count. There are six different chart types to choose from:
Optional settings include Annotations, which mark milestone events, and Data Labels, which communicate the numerical values at each point in the chart.
For more advanced analysis, you may create queries with multiple rows, displaying and comparing information of distinct events within the same results. You may also create calculated queries to explore, for example, proportions or percentages using the Calculator. Finally, you may compare results to a previous interval by using the Trends function.
Certain analyses run in the past can change based on what user properties are set to since user properties can change over time. A common scenario where changes are seen when running analysis at different points in time, is a direct result of looking at users who were aliased since then.
Note on Aliasing: Aliasing runs once on a daily basis and links unknown users to known users. The count of unique users triggering an event seen before the aliasing process may decrease after aliasing finishes processing. You can read more by visiting our docs on user aliasing.
A few helpful tools are located to the right of the query builder:
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