Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
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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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Rules Developer Guide
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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
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Analyses Introduction
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For Clauses
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Manage Analyses in Dashboards
Dashboards––Getting Started
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Optimize User Flow with A/B Testing
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IDSync Overview
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Aliasing
Overview
Create and Manage Group Definitions
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Predictive Audiences Overview
Using Predictive Audiences
Introduction
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Data Subject Requests
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Import Data with CSV Files
CSV File Reference
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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
Audience A/B Testing allows you to split an audience into two or more variations and create connections for each variation independently, to help you to compare the performance of different targeting approaches. For example, if you have an audience of low engagement users that you want to reengage with your app, you might devise a test like this:
You can then compare the engagement outcomes for each group and apply the most successful strategy to the entire audience.
After saving your variations, you will see each variation in a new branch within the Journey Builder.
After defining your variations, you can connect each one, including the control group, to any output by clicking + Connect Output. There is also an option to connect the full audience to an output by clicking + Connect Output on the original audience card prior to the A/B split.
In the Audiences summary screen, audiences with an active A/B test will be marked with a % symbol.
Note that whenever the Audience Name is used in forwarding the audience to downstream partners, variant audiences will be named using the format [Audience External Name] - [Variant Name]
.
You can edit an audience definition without affecting the audience split, even after connecting to an output. When the audience is updated, the variants will still be balanced as defined when you created the test.
You cannot modify the percentages of an A/B test after creating the test.
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