Overview
This course is for the person everyone already turns to when a segment needs to get built — and it's built to make sure the answer is right, not just fast. Over four weeks, we move past basic list-pulls into the SQL patterns that let you answer real business questions directly inside Marketing Cloud: multi-table joins across a real data model, scoring and cohort logic, and datasets built to survive being handed to someone else. This is a hands-on, code-along course — expect to write SQL in every single session.
Prerequisites:
Comfortable writing basic SQL query activities in Marketing
Cloud — single-table filters, simple WHERE clauses.
Completed Segmentation & Data Extensions or
equivalent experience recommended.
What You'll Walk Away With
- Multi-table joins across complex data extension relationships
- Subqueries and CASE-based segmentation logic
- RFM-style scoring and cohort analysis queries
- Techniques for optimizing query performance on large data extensions
- Reporting-ready dataset design
Session-by-Session Agenda
Week 1 — Rebuilding the Foundation
01
Revisiting the data model
— relationships, keys, and where basic
segmentation starts to break down
02
Multi-table joins
— inner, left, and right joins across a real
marketing data model
Week 2 — Conditional & Cohort Logic
03
Subqueries & CASE logic
— building conditional segmentation that holds
up under edge cases
04
Cohort-based segments
— signup date, first purchase, and
lifecycle-stage groupings
Week 3 — Scoring & Identity
05
RFM-style scoring
— recency, frequency, and monetary-value
queries
06
Deduplication & identity resolution
— patterns for reconciling records at scale
Week 4 — Performance & Capstone
07
Query performance
— indexing behavior, avoiding timeouts, working
with large data extensions
08
Capstone project
— building one complete, reporting-ready
segmentation dataset from a messy, multi-table
scenario