Dotdigital Certification study plan

Map the full campaign automation workflow lifecycle (trigger, decision, delay, action, exit) and diagram a five-step program from memory

Configure a basic welcome program with at least three decision splits and two delay nodes in a sandbox account

Define how program entry rules, re-entry limits, and goal completion criteria interact, and document the logic in a one-page reference

Identify the five most common automation failure points (e.g., missing exit rules, overlapping triggers) and write a mitigation note for each

Build a three-stage abandoned-cart automation (browse abandonment, cart abandonment, post-purchase cross-sell) with dynamic content blocks

List every personalization token available in automation emails and test fallback values for missing data

Create a decision split based on purchase history and another based on engagement score, then compare their routing behavior

Draft a test plan covering time-zone sends, suppression lists, and program re-entry for the cart automation

Define at least six audience segments using behavioral, demographic, and transactional attributes, and document the rule logic for each

Configure dynamic content variants for three segments in a single email and verify rendering with preview/test sends

Implement a product-recommendation block based on browsing or purchase affinity and explain how the recommendation source is selected

Write a personalization governance note covering data freshness, consent, and fallback content for unknown profiles

Design an end-to-end lifecycle program that combines automation triggers with personalized content for onboarding, nurture, and re-engagement

Audit the program for conflicting sends, frequency caps, and suppression overlaps, and resolve at least three issues

Create a measurement plan with program-level KPIs (completion rate, goal conversion, revenue per send) and define how each is calculated

Run a peer-style walkthrough of the lifecycle design and incorporate feedback into a revised version

Design a tiered loyalty program structure (earn, redeem, expire) and map each tier to automation triggers

Build a win-back automation for lapsed customers with a three-step cadence and a clear exit on purchase

Define retention metrics (repeat purchase rate, churn risk score, loyalty tier migration) and calculate them from sample data

Create a referral or advocacy touchpoint and specify how its success is tracked back to the loyalty program

Compare email, SMS/MMS, WhatsApp, mobile app push, web personalization, and ads/retargeting on consent model, message limits, and best-fit use cases

Configure a cross-channel journey that uses at least three channels with channel-appropriate fallback logic

Set up a retargeting audience from a web personalization rule and document the data flow from site behavior to ad audience

Write a channel selection decision tree for a given campaign brief and justify each branch

Map the customer data model (contacts, consent, custom data fields, events) and explain how each feeds segmentation and reporting

Build a report or dashboard that tracks one automation program and one broadcast campaign, including open, click, conversion, and revenue metrics

Configure an AI agent or predictive feature (e.g., send-time optimization or product recommendations) and document its inputs and outputs

Create a data quality checklist covering consent capture, field validation, and duplicate management

Complete a timed 60-question practice exam covering all five domains and score at least 80%

Review every missed question, tag it to a domain, and write a one-sentence correction for each

Re-read the weakest two domain summaries and redo the associated hands-on exercise from weeks 1–7

Summarize the ten most testable distinctions (e.g., automation vs. campaign, segment vs. list, consent by channel) in a personal cheat sheet