The Connections screen is the core of mParticle’s functionality. It controls how event data from your inputs (iOS, Android, Web, Feeds, etc) is forwarded to your Output platforms. You must set up a separate connection for each input/output. For each connection, you have a number of opportunities to cleanse and filter your data, to ensure that each output receives the data you want it to receive, in the correct format.
Each of mParticle’s Output services has it’s own requirements, so the process for setting up each connection will be a little different, but all connections require these basic steps:
1. Select an input
Select the input you want to configure. When you first load the connections screen, you will see a list of available inputs. If the list is empty, go to Setup > Inputs to create inputs.
2. Apply ‘All Outputs’ transformations
Once you have an input selected, you can setup transformations that will be applied to all Output services connected to that Input. Click All Outputs to see options. There are two transformations that can be applied here:
3. Select an Output
Once you have selected an Input, you will see a list of available Output services that can receive data from your selected Input. If this list is empty, go to Setup > Outputs to create some outputs.
4. Complete Connection Settings
Complete any settings that apply to the connection. These will be different for every Output but can include:
5. Apply ‘Specific Output’ transformations
The second set of transformations apply only to your selected Output. Click Specific Output to see options. Specific Output transformations include
6. Set Status to ‘Sending’
When you have completed the required settings and set up any transformations, open Settings, check that the Status slider is set to Sending and click Save.
See Rules for more information on Rules.
The User Splits feature gives you the ability to test two or more different output services against each other by sending a specific group of users to each service.
mParticle has implemented User Splits via user ranges. The mParticle platform assigns each user a random number between 1 and 100, ensuring an even distribution of your users across this range. This implementation allows you to create up to 5 overlapping or mutually exclusive groups of users for your User Split test.
Simply set the sliders for each integration to determine which users to send to each platform. For example, you might create a group to send 0-50% to Output Service A and 50-100% to Output Service B.
mParticle lets you customize the data that you send to each output. There are many reasons to do this, including:
Unlike other tranformations, the Data Filter exists on its own page, separate from the Connections screen. The Data Filter allows you to decide which events/attributes you want to send to each Output. By default, all events/attributes are enabled when you first enable a connection. From the Event Filter you can:
See The Data Filter for more information.
Like the Event Filter, Forwarding Rules let you filter out events from being sent to an Output. But where the Event Filter is based on Event and Attribute names, Forwarding Rules look at values, which lets you build some more complex conditions. There are several types of forwarding rules.
Attribute: Attribute rules take an event attribute name and a value. You can choose to either not forward events that match the rule, or to only forward events that match the rule, excluding all others. Greater than / less than comparisons are not possible. Matching is case sensitive and exact.
Attribution: Attribution rules filter events according to Publisher information. You can choose to exclude events attributed to a specific publisher, or forward only events attributed to that publisher.
Consent: Consent rules allow you to filter events based on whether a user has given consent to a particular data collection purpose. See our Consent Management guide for more information about consent.
ID Sync: ID Sync rules allow you to only forward data from logged-in users. A logged in user is one with at least one Login ID, as defined by your Identity Strategy.
Not to be confused with user splits, which is designed to help you test output services against one another, User Sampling is applied to a single output and sends only a subset, or sample of your data to a service. The main reason to do this is to control costs on services that charge by volume of data. Data is sampled on a user level, not an event level - if you select a 50% sample, mParticle will forward all data received from half your users, not half of each user’s data.
See Rules for more information on Rules.
Some services allow your incoming events to be translated into events specific to the service. For example, if you have a custom event named “NextLevel”, typically this event would be forwarded as a custom event to a service. With custom mappings, you can specify that this event be forwarded to a service using their specific event name. For example:
|Integration||Integration Description||Integration Event Name|
|Criteo||User Level Finished||UserLevel|
For partners that support custom mappings, the Output Service’s events are listed on the left side of the Custom Mappings tab. For each event, you can then select an mParticle event and associated attributes to map to the Partner’s event.
The following integrations support custom mappings:
If an event has a Custom Mapping for a particular connection, it will be displayed with an icon in the Event Filter
If you turn off forwarding of an event with a Custom Mapping, the mapping information will be deleted.
The final and most crucial transformation step is the mParticle Forwarder Module itself.
After all your other transformations have been completed the forwarder module turns your data into messages to the Output service in its preferred format.
Each integration has its own Forwarding Module. Settings for the forwarder are derived from three places:
Based on these settings, mParticle transforms your data into a format accepted by the Output service. This can involve extensively reformatting the data. For example, Mixpanel’s API accepts events, with attributes given as a flat set of key-value pairs. To fit this structure, a single mParticle eCommerce event with four products will be transformed into 4 Mixpanel Events - one for each product - with common attributes, such as user and device info, repeated for each event.
The documentation for each integration will tell you what you need to know about how data is transformed to be accepted by the Output service.
As you can see, mParticle gives you plenty of opportunities to transform and enrich your data. It is often possible to perform the same transformation in more than one place. For example, if you wanted to drop all Application State Transition events for a given output, you could use the Event Filter, or you could write a condition in an Output Rule. There are advantages to each choice. The Event Filter can be used by anyone with the appropriate access to your organization in the mParticle Dashboard, so it is easy to update and maintain. Writing a Rule will give you much finer control over your data, but it will be hard for non-developers to understand or alter.
As a general rule, it is best to make the necessary transformations to your data in as few steps as possible. The fewer times you alter your data, the easier your integration will be to troubleshoot and maintain.
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