Organizations can more effectively implement sales, marketing, and customer nurturing strategies when they have a complete understanding of who their customers are or what they're likely to do. This effectiveness comes from understanding customers based on your internal data and by obtaining a more complete profile with enriched data from external sources. When this information is combined with technologies, such as AI and machine learning, organizations can make informed predictions based on historical trends and then use the enriched data to better implement activities. Audience Insights helps your organization accomplish this task through data enrichment and intelligence.

This module discussed how Audience Insights can assist organizations by examining the different enrichment and prediction options that are available, including:

  • Providing an overview of the enrichment and prediction options that are available in Audience Insights.

  • Examining how enrichment can be used and what enrichment options are available.

  • Explaining the brand and interest capabilities and how to configure the functionality.

  • Examining additional enrichment options that are available by using partner services in the application.

  • Reviewing the prediction options that are available with Audience Insights and how to use them.

  • Examining the process of setting up and configuring the customer churn prediction model.

  • Explaining how custom machine learning models that are created in Microsoft Azure can be added into Audience Insights.

Your next steps would be to learn how to use the different Audience Insights features for different scenarios, such as using segments and customer profile data in other applications. It can also be helpful to learn how to extend Audience Insights with the different APIs that are available.