SAS Marketing Automation: Defining the Data and Structure for Campaigns

This course provides an understanding of how to build, extend, and maintain the information map required in a SAS Marketing Automation 6.6 environment.

The self-study e-learning includes:

• Annotatable course notes in PDF format.
• Virtual lab time to practice.

Learn how to

• Create simple and complex information maps for use in SAS Marketing Automation 6.
• Use the information map to generate metadata tables for SAS Marketing Automation 6.
• Create a business context and the necessary definitions to support the creation of marketing campaigns.

Who should attend

Data modelers, IT administrators, and marketing analysts who want to understand how to set up data for SAS Marketing Automation

Formats available	Standard Duration (duration can vary, see event schedule for details)
Classroom:	1.5 days
Live Web Classroom:	3 half-day session(s)	System Requirements
e-Learning:	10.5 hours/180 day license

Before attending this course, you should have taken the SAS Marketing Automation: Designing and Executing Outbound Marketing Campaigns course or be familiar with SAS Customer Intelligence Studio functionality at the level of that course. Prior experience with SAS Information Map Studio is beneficial but not required.

This course addresses SAS Customer Intelligence Tools, SAS Marketing Automation software.

Introduction

• Course overview.
• Overview of SAS Marketing Automation (self-study).

Creating a Basic Information Map

• Overview.
• Specifying source tables.
• Adding data items and folders.
• Defining subjects.
• Assigning subjects.
• Setting up metadata tables.

Business Contexts: Generating Metadata

• Creating metadata tables.
• Updating metadata.

Creating a Complex Information Map

• Working with multiple source tables.
• Defining and assigning multiple subjects.
• Validating the information map.

Business Contexts: Enabling Campaigns

• Introduction.
• Creating campaign definitions.
• Creating export and communication definitions.
• Using the common data model (self-study).

Other Data Items

• Using measures.
• Calculated data items.