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Step 1. Create an input
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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
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What are predictive attributes?
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Aliasing
Predictive Attributes are special User Attributes that, as the name suggests, predict your users’ future behavior. Powered by AI and based on your customers’ behavioral and demographic information, Predictive Attributes eliminate the guesswork from campaign planning and execution, and allow you to engage with your users on a truly one-to-one level.
Traditionally, marketers and product managers look to user events like website visits, page views, and journey completions to build out customer segments. While manual segmentation can certainly be effective, it is subject to the limitations and inefficiencies of human decision making.
Predictive Attributes let you avoid the drawbacks of manual audience building. Once you define your desired conversion goal, Cortex’s Machine Learning models will analyze thousands of behavioral signals to determine which users are statistically most likely to convert, letting you accelerate decision making and execute campaigns with confidence.
Additionally, Predictive Attributes update automatically based on real-time customer behavior. Since your highest value customers are always changing, Cortex continuously recalculates Predictive Attributes to ensure that your campaigns stay focused on the users who most closely align with your campaign goals.
Predictive Attributes are stored on the User Profile, and you can use them in the same ways you would any other behavioral or demographic User Attributes (like audience building or querying via the Profile API). The difference is that unlike regular User Attributes, which are captured as soon as your users take specific actions, Predictive Attributes need to be defined and generated withing a workflow in mParticle. Once they exist on the User Profile, however, there is functionally no difference between Predictive and regular User Attributes in how you use them to achieve your business goals.
Predictive Attributes fall into two main categories based on the business outcomes they enable:
These predictions tell you how likely your individual customers are to take a specific action that matters to your business, like purchasing a new product or upgrading a subscription (to name just a few).
These predictions tell you which specific offer among a specified set is mostly likely to result in a customer taking a defined action.
The most fruitful use cases for Predictive Attributes tend to have the following characteristics:
Specific examples of use cases where Predictive Attributes are likely to improve campaign performance include:
Predictive Attributes created in mParticle have the following limitations:
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