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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
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The Developer's Guided Journey to mParticle
Create an Input
Start capturing data
Connect an Event Output
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Connect an Audience Output
Transform and Enhance Your Data
The new mParticle Experience
The Overview Map
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Introduction
Introduction
Rudderstack
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BigQuery (Snowplow Schema)
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BigQuery (Define Your Own Schema)
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Snowflake (Snowplow Schema)
Snowflake (Define Your Own Schema)
Aliasing
Analytics supports several aliasing use cases. This topic describes the use cases and provides best practices for managing user aliasing.
Identity Reconciliation
Users interact with digital environments in many different ways. When a new user accesses your website or app, they are unknown, so a unique Anonymous ID is assigned to track their online behavior. Users may remain anonymous for the duration of their visit or they might create an account, log in, or otherwise share identifiable information. Once the user becomes known, it’s important to reconcile the known identity with any previously anonymous user identities, and to combine the activity timelines of each ID. This creates a unified user activity timeline and enables a complete analysis of the full customer journey. Without user reconciliation, an individual user may be assigned multiple user IDs, which can cause duplication of user counts and fragmentation of user activity in your data. The process of reconciling known and unknown user identities is called aliasing. Aliasing is also known as identity reconciliation, stitching, or merging.
Cross-Device Identification
Users can access your website or app from a variety of devices and locations. Maybe a user creates a profile on your website using their laptop, then downloads your app onto their smartphone and also onto their tablet. Maybe they log in on a friend’s phone to place an order. In addition to reconciling known and unknown user identities, aliasing combines the activity timelines of each device, platform, and geographic location. This again creates a unified activity timeline to provide a complete analysis of the full customer journey.
Cross-Domain Tracking
Aliasing can also help with cross-domain tracking. To achieve this, pass the Anonymous ID from the second domain as an aliasing parameter. Then contact your Customer Success Manager for more information on how to enable cross-domain tracking with aliasing.
Depending on your integration type, aliasing is achieved in different ways. For example, if you send events to Analytics in real-time by using Segment, Amazon Kinesis, or via the Analytics API, the process is different than if you send events to Analytics daily through a data warehouse integration. The following documentation describes our process for aliasing user identities in real-time integrations.
An aliasing API call consists of three components:
After receiving an aliasing call, Analytics reconciles the anonymous ID and the user ID, and handles all incoming events from both IDs as the same user. In short, they’re “stitched” together. Multiple anonymous IDs may be aliased to a single user ID, however you may not alias multiple user IDs to a single anonymous ID, nor may you alias a user ID to another user ID. Alias calls are processed once per day, so please allow up to 24 hours for best results.
JavaScript (SDK) Alias Calls
Indicative.sendAlias()
The Analytics client automatically generates a universally unique identifier (UUID) to apply to all events until “Indicative.setUniqueID(id)” is called. “Indicative.sendAlias()” can be called to alias the UUID to the ID parameter defined within “Indicative.setUniqueID(id)”
Indicative.setUniqueID(id, true)
After setting the new unique ID, then this will automatically call “Indicative.sendAlias()”. If you perform “callIndicative.setUniqueID(id)” without ‘true’, then the alias call will not be sent.
It is recommended that an alias call be made once, at the first instance of the user identifying themselves, such as upon registration or profile creation. We also recommend caution, as improper use of aliasing can cause unforeseen issues with data accuracy. To mitigate this risk, Analytics enforces the following strict aliasing rules:
Rule |
---|
Anonymous ID and User ID must be different |
Anonymous ID may be aliased to only one User ID |
Multiple Anonymous IDs may be aliased to one User ID |
Anonymous ID may not be aliased to another Anonymous ID |
User ID may not be aliased to another User ID |
If an ID has already been defined as a User ID, then it cannot be reclassified as a Anonymous ID |
You may not “chain” alias calls (i.e. Anonymous ID > User ID1 > User ID2) |
Alias calls only impact future data received. |
Aliasing is stateful, which means we build an accumulated view of your aliasing calls over time. |
When user profiles and events are sent from the mParticle CDP to Analytics, Analytics will inherit all aliasing functionality that was performed using IDSync. This means that Analytics automatically has access to the same unified view of user profiles and events established within mParticle.
For customers on the Enterprise plan, alias calls can be performed retroactively to combine two activity timelines that have already been processed. Retroactive aliasing is useful when events performed anonymously before an aliasing API call is received need to be reconciled with a known user profile. Retroactive aliasing takes place once every 24 hours.
For example, consider the events below, all performed by the same customer:
In this sequence, only event 3 would need to be retroactively reconciled with the known user ID, while events 1, 2, 4, 5, and 6 would be immediately associated with the unified profile following the aliasing API call. Once daily retroactive aliasing is complete, the event in step 3 becomes associated with the same user profile as the rest of the events.
This diagram further illustrates retroactive aliasing:
Custom aliasing rules may be supported for Enterprise customers only. This can be requested by contacting Support or your Customer Success Manager.
Aliasing calls from a third party are not supported. Analytics rejects these calls because they are considered “chained” alias calls (i.e. Anonymous ID > Third Party User ID > Indicative User ID). If you are concerned that your method of integration is causing aliasing issues, please contact Support or your Customer Success Manager.
Under GDPR privacy regulations, users have the option to opt into or out of session tracking. If a user does not consent to tracking, then all personally identifiable information (PII) must not be collected and existing PII must be deleted. The only data that is tracked by the Analytics client is the Anonymous ID, a random string ID used to unify a single user session. This ID does not persist across multiple user sessions. It is not possible to alias the IDs of users who opt out of session tracking.
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