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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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
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Compose ID
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Migrate from Segment to mParticle
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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
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Introduction
Introduction
Introduction
Rudderstack
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BigQuery (Define Your Own Schema)
GCP BigQuery Export
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Snowplow Schema Overview
Snowflake (Define Your Own Schema)
Aliasing
Before you start this activity, you should have already:
Up until this point, you’ve been testing your account with a single development build of your app. This works well to establish basic data throughput.
The Audiences feature allows you to target segments of your users based on their activity or attributes. So to effectively use Audiences, even at the testing stage, your app needs multiple users!
If you’re not ready to enable the mParticle SDKs in your Production app yet, you can either spin up multiple development environments, or try using the Events API to supply some test data in bulk.
The mPTravel app lets users watch video content about travel destinations. This tutorial creates an audience to allow mPTravel to target users who view content about a paticular destination with deals for that destination.
There are three distinct aspects of an event criteria that you can define:
Attributes - you can refine your criteria further by setting attribute conditions. This example targets only instances of the Play Video event where the “category” attribute has a value of “Destination Intro” and the “destination” attribute has a value of “Paris”.
Note that this example creates an Exact Match condition, but there are other types of condition to explore. For example, if you set “destination” Contains “France”, then you could match events with a “destination” of both “Paris, France” and “Cannes, France”.
The types of condition available depend on what kind of data an attribute holds. For example, an attribute that records a number value will have Greater Than and Less Than conditions. mParticle automatically detects what type of data an attribute holds. However, you can manually set the data type by clicking the type symbol.
Don’t change the data type unless you really know what you’re doing. If you force the data type to be Number, and all your attribute values are strings, your condition will always fail! As long as you’re sending the same type of data consistently for each attribute, you shouldn’t have to worry about it.
You could save this audience right now and target all users who have watched mPTravel’s Paris content in the past three days. But, what if you have some extra special limited deals that you want to save for your premium members? You can’t just tell everyone! You need to add a second criteria. Whenever you have multiple criteria, you need to decide how to evaluate them together. There are three options:
To target users who watched Paris content, AND are premium members, choose And.
This is a good opportunity to look at the User criteria type, as it’s a little different. Where the other criteria match users who have triggered a particular event, the User criteria looks at all other information you might know about your users: the type of device they use, where they live, their custom user attributes, etc. This example targets users with a user attribute of “status”, with a value of “Premium”.
When you’ve added as many criteria as you need, click Save as Draft to come back to your definition later, or Activate to start calculating.
When you activate the audience, you’ll be asked if you want to set up an A/B Test. Select No for now, to go to the Connections Screen.
After you finish defining your audience you will be taken straight to the Audience Connection screen. Connecting an audience will be covered in the next section.
First, check that your audience definition is working as expected. Start by selecting Audiences from the left column to go to the main Audiences page. Audiences take time to calculate, so if you’ve only just activated it, you’ll probably see a Size of 0 for your audience. Mouseover the pie chart to see how far along the calculation process is.
After a while, as long as you have users that match your criteria, you should start to see the value of the Size column increase.
If the audience is 100% calculated, and your size is still zero, there may be an issue with your conditions.
In some cases, it might be enough just to know that your audience is matching users. However, if you know specific identities of users who should match your criteria, you can check that they matched by downloading your entire audience in CSV form. Follow the instructions here to download your audience.
For simple audiences, it’s a good idea to check your Live Stream to see if you can find an event that should match your criteria. Here, you can see a user who has triggered the correct event.
Some things to check:
Remember that recalculating an audience will take some time, so check your criteria thoroughly before you save your changes.
Congratulations on making your first audience in mParticle! You will have noticed that mParticle populates your options in the Audience Builder based on the data you have captured. This means that as you add new sources, and send more data, you will unlock new options for building audiences. Check in periodically to make sure that you’re getting the most out of your data. Some mParticle clients create hundreds of audiences, each with dozens of chained criteria to target hyper-specific user segments. You’re only limited by the data you can capture and your imagination.
A few things to read or think about:
favorite_color
in your Web implementation, and favoriteColor
in your Android implementation, it’s going to be much harder to build a cross-platform audience to capture your users who love green
. Check out some docs about the importance of names here.Next up, you will learn how to connect an audience to one of mParticle’s Audience partners.
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