This article provides a descriptions of various approaches you can use to define your strategy and goals before you begin creating and training models.
In this article:
The variety of approaches you can use to define your strategy and goals using Machine Learning is virtually endless. For example, you can augment existing use cases, create exploratory models, or create specific use cases for targeted findings.
If you have Tealium AudienceStream with data collection enabled, you have the ability to begin using Tealium Predict. There are no further requirements. For additional information, see Prerequisites.
As a general approach to get started, train one or more models and review the Included Attributes on the Training Details report.
The details in this report provide you with a source of new insights about which Tealium AudienceStream data points are the key drivers to an important user event. You can also use Tealium Predict as a tool for learning more about your data, your implementation, and as a source of information for new ideas.
The following proven best practices provide more robust results:
To help gather ideas to start your implementation or to implement proven use cases, review the following articles about popular and emerging machine learning use cases being implemented by Tealium customers.
For detailed information, see Tealium Predict ML: Top 5 Emerging Machine Learning Use Cases with Customer Data.