This document provides a descriptions of various approaches you can use to define your strategy and goals before you begin creating and training models.
In this document:
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 AudienceStream, you have the ability to begin using Predict Machine Learning. 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 can provide you with a source of new insights about which AudienceStream data points are the key drivers to an important user event. You can also use Predict as a tool for learning more about your data, your implementation, and as a source of information for new ideas.
The following general best practices can provide more robust results:
To help jump start your implementation, you can review popular and emerging machine learning use cases being implemented by Tealium customers. From here you can gather ideas or implement proven use cases, such as:
For detailed information, see Tealium Predict ML: Top 5 Emerging Machine Learning Use Cases with Customer Data.