Adobe Analytics - Business Practitioner Expert Certification

Exam details	Level: Expert (1-3 years’ experience) Passing Score: 31/50 Time: 120 mins Delivery: Online proctored (requires camera access) Available languages: English, Japanese Cost: $225 (global) / $150 (India) Exam ID: AD0-E208 (English), AD0-E208-J (Japanese)
Intended audience	Digital marketers Business analysts Business consultants Data analysts Web analysts Digital analysts Media/marketing analysts Product owners and managers UI analysts Conversion/optimization specialists
Minimum experience	You should have: 2 years’ experience in Digital Analytics with a marketing background An in-depth understanding of Digital Analytics metrics and dimensions An understanding of the business value of web technologies The ability to translate business requirements into metrics or KPIs The ability to build and interpret reports The ability to communicate results and can propose a course of action based on analysis of reports Helped clients understand how to extract/pull the information they want (for example, help them define their business questions) An understanding how the technology works and understands a client’s implementation (for example, where the data sits, how it can be collected, how it is tracked) from a functional standpoint At least one year of Adobe Analytics hands-on experience A basic understanding of how Digital Analytics is filtering/structuring data An awareness of the integration of Adobe Analytics with other Adobe solutions Additionally, you should be familiar with the following technologies and environments: FTP client Current Adobe Analytics Workspace features and other reporting options outside of Workspace (ex. schedule projects and schedule reports) Debugging tools relevant to Adobe Analytics (Packet monitor such as an Adobe Debugger, browser developer tools, Charles) Admin Console (Analytics Reports Suite Admin Console and Experience Cloud Admin Console) Adobe Launch fundamentals/basics Apps, SPA, basic website understanding Mobile services UI Adobe Help Center Data export options (ex. right click to export, .csv download, Data feeds, Data Warehouse extract)
Exam objectives and scope	This section provides information on the exam content. Section 1: Understanding Analytics in the Adobe Experience Cloud Ecosystem (10%) Demonstrate knowledge on utilizing the Adobe Experience Cloud ID Demonstrate understanding of Adobe Launch Demonstrate understanding of common integrations across the Adobe Experience Cloud Ecosystem Section 2: Reporting and dashboarding for projects (30%) Consider the advantages of using a reporting tool based on a given scenario Compare fallout and flow visualization and appropriate variable types for reporting Apply the process to schedule Projects and Data Warehouse Apply the process to share Projects and Reporting and Analytics dashboards for different users and/or groups Apply the process to set Alerts Apply the process to lookup the dimensions/components Apply the process to create a visualization Given a scenario, determine the appropriate item to use Apply the process to create, configure, and use mobile scorecards Section 3: Segmentation and calculated metrics (22%) Determine how to develop and configure segments Apply the process to share segments with others in the organization Compare segments Apply segments to Projects and Components Apply the process to generate calculated and/or segmented metrics Section 4: General tool knowledge and troubleshooting (12%) Analyze reports and identify data quality issues Define different types of dimensions and parameters existing in Adobe Analytics (eVars, props and events) Determine how to bring data in and out of Adobe Analytics Identify information from marketing URLs Section 5: Administration (10%) Apply the process to configure the Marketing Channel reports with Marketing Channel processing rules Apply the process to configure Classification Importer and Rule Builder Apply the process to configure a virtual report suite based upon an existing segment Use the Data Feed Manager Admin UI Understanding of data governance