SAP Emarsys Customer Engagement Implementation Consultant study plan

Map the full SAP Emarsys Customer Engagement implementation lifecycle from account provisioning and contact database setup through channel activation, and write a one-page process diagram in your own words

Define the core data objects (contacts, contact lists, segments, custom fields, relational data tables) and explain in writing how each one is created, populated, and consumed by campaigns

Install or access a test/sandbox account and complete the initial platform configuration steps: sender domains, reply addresses, and account-level settings

Build a glossary of at least 40 implementation-specific terms (e.g., API user, external event, Web Extend, predict, automation center) with a one-line definition each

Configure contact data ingestion: create custom fields, import a sample contact CSV, and document field-mapping decisions

Set up at least two contact lists and build segments using both rule-based and behavior-based criteria

Connect a test website or data source to Web Extend and verify that browse and purchase events flow into the platform

Write a short data-quality checklist covering deduplication, consent/opt-in handling, and field normalization

Implement the REST API: create an API user, authenticate, and execute contact creation, update, and query calls

Document the difference between the contact API and the event/trigger API and when an implementation would use each

Configure an external event and fire it programmatically to trigger a test automation

Set up SFTP or batch data import for a scheduled contact sync and verify a successful run

Build an email campaign end to end: template selection, personalization tokens, dynamic content blocks, and link tracking

Configure an Automation Center program with at least three nodes (trigger, wait/delay, send) and test it with a seed contact

Set up A/B testing on a campaign and interpret the result reporting

Document deliverability basics: SPF, DKIM, DMARC alignment, bounce handling, and sender reputation monitoring

Configure a second channel (SMS, mobile push, or in-app) and connect it to the same contact data model used for email

Implement a multi-channel automation that branches by channel preference or contact attribute

Review the reporting and analytics surfaces (campaign dashboards, revenue attribution, segment performance) and write a summary of what each metric means

Map out how Smart Insights and predictive features consume contact and event data

Practice integration scenarios: connect the platform to an external e-commerce or CRM system and document the sync direction, frequency, and error handling

Configure user roles, permissions, and team structures appropriate to a multi-team implementation

Write a troubleshooting runbook covering common implementation failures (failed imports, API auth errors, broken tracking, automation not firing)

Complete 40+ practice questions or scenario exercises and log every wrong answer with the correct concept

Revisit every weak area identified in the wrong-answer log and re-implement the related configuration in the sandbox

Do a full timed mock exam or a large scenario set and score it honestly

Explain out loud, without notes, the end-to-end flow from data ingestion to segmentation to automation to reporting

Review consent, GDPR-style data handling, and data retention settings as they apply to contact management

Re-run any previously failed practice scenarios until you pass them consistently

Review your glossary, runbook, and analytics sheet as a consolidated final reference

Confirm exam logistics: format, timing, question style, and any allowed resources

Do a final light review focused only on the highest-weight topics and your documented weak spots