Adobe Analytics Training

Adobe Analytics is a sophisticated analytics tool with the ability to deliver powerful insights. In this one-day, onsite training session, we’ll customize a solution to meet your team’s needs. A customized training guide will be provided for your team’s future reference.

Gain valuable knowledge from our Adobe Analytics Experts

  • Understand customer behavior to optimize the customer journey
  • Measure and monetize marketing channel performance
  • Have a clear understanding of the terms and metrics in Adobe Analytics
  • Create and modify reports in the UI & Analysis Workspace
  • Create and apply segmentation
  • Create and manage dashboards
  • Create conversion funnels to measure online purchases, leads or other funnel behavior

This intensive training will cover the following topics:

 Adobe Analytics Interface

We’ll begin with a comprehensive introduction to Adobe Analytics, covering:

  • User interface walk-through, familiarizing your team with how to use the tool
  • Tips for easier navigation and shortcuts

Custom Variables

Adobe Analytics’ customization’s feature is perfect to fit the specific demands of your business. We’ll perform a discovery and data validation process to cater the training to your organization’s needs.

Segmentation

We’ll show you how to build, manage, share, and apply audience segments to your reporting. This will include container hierarchy logic, rules, and operators.

Analysis Workspace
With this powerful new tool within the Adobe Analytics reporting suite, you can perform more in-depth analyses of the data available to you. We’ll go over how to create breakdowns and segments and curate reports for sharing within your organization.

Report Builder

Build customized reports that import your analytics data with this Microsoft Excel add-in. We’ll show you how to use the tool and provide best practices for creating reports using Report Builder.

Data Validation

During this part of the training, we’ll explain the importance of data validation for the following reasons:

  • To better understand how data is captured, helping users interpret data in the reporting.
  • To identify when something isn’t tagged that should be or identify a sudden drop in a data point, giving your team a method for finding the underlying issue.