SQL Marketing & Customer Analytics
Use SQL to understand customers, measure campaigns, track conversions and turn marketing data into decisions.
3 course parts · 3 capstone projects · realistic marketing database · AI Tutor · Certificate issued by CiAI.
Self-paced online · Designed for learners who completed SQL Basics and SQL Beginner, or have equivalent foundational SQL skills.
Analyze the Customer Journey
Connect customers, campaigns, website sessions, engagement and purchases across the marketing funnel.
Measure Campaign Performance
Use SQL to analyze clicks, conversions, spend, revenue and ROI across campaigns and channels.
Understand Customer Value
Segment customers and analyze cohorts, CLV, retention, churn and repeat purchasing.
3 Applied Capstone Projects
Complete one marketing analytics capstone after each course part.
Use SQL to Turn HR Records into Workforce Insight
Marketing data is spread across employee records, jobs, departments, salary history, performance reviews, attendance, training and recruiting systems. This course teaches learners how to connect those records with SQL and answer practical workforce questions used in HR operations and people analytics.
Why take SQL Marketing after SQL Basics and SQL Beginner?
SQL Basics and SQL Beginner teach you how to retrieve, filter, group and combine data. SQL Marketing applies those skills to real HR questions: Who are our active employees? Which applicants are in the interview stage? How has compensation changed? Which departments have the highest turnover? How long have employees been with the organization? Who reports to whom?
What you will learn
- Retrieve and filter employee records for HR reporting
- Search applicants by recruiting stage
- Join employees to departments and jobs
- Extract new-hire, active-employee and terminated-employee cohorts
- Analyze salary history and compensation changes
- Review attendance, absence and overtime patterns
- Calculate turnover and departmental terminations
- Build headcount and average-salary summaries
- Use HAVING to filter grouped HR metrics
- Calculate tenure and hiring trends with date functions
- Map manager relationships with self-joins
- Rank employees within departments using window functions
Who this course is for
- Marketing professionals and HR administrators
- People analytics and workforce planning learners
- Recruiting and talent acquisition professionals
- Compensation, payroll and benefits professionals
- Managers who work with HR reporting and workforce metrics
- Non-technical professionals moving into people analytics
SQL Marketing & Customer Analytics Curriculum: 3 Applied Parts
The course progresses from understanding how marketing data is structured, to querying connected customer and campaign data, and finally to advanced marketing analytics and reporting.
Understand the tables, fields and systems behind modern marketing analytics before building reports.
- Understanding marketing analytics tables
- Customer-level vs. campaign-level vs. transaction-level data
- How CRM, marketing automation and ad platforms store data
- Key fields: acquisition_channel, campaign_id, conversion_flag, order_value
- The customer journey and marketing funnel data
- How customers, sessions, campaigns and purchases connect
- Capstone 1: Customer Journey Data Map & Acquisition Report
Apply SQL directly to customer, campaign, website and purchase data to answer common marketing questions.
- Retrieving customer and campaign data using SELECT
- Filtering marketing data with WHERE
- Joining customers, orders and campaign tables
- Analyzing campaign engagement and website sessions
- Aggregating marketing metrics using GROUP BY and HAVING
- Identifying high-value customers and repeat buyers
- Capstone 2: Campaign & Customer Performance Analysis
Turn connected marketing data into performance, customer-value and decision-ready reporting.
- Campaign performance analysis and ROI reporting
- Customer segmentation and cohort analysis
- Conversion funnel and attribution analysis
- Customer lifetime value and revenue analysis
- Retention, churn and repeat purchase analysis
- Building marketing performance dashboards with SQL
- Capstone 3: Marketing Performance & ROI Dashboard
Follow the Marketing Analytics Workflow End to End
Example: summarize advertising spend by campaign
Marketing teams need campaign-level metrics before they can compare performance or evaluate ROI.
The course builds from this foundation into conversions, revenue, segmentation, funnels, customer value and marketing dashboards.
3 Hands-On SQL Marketing Capstone Projects
The course includes exactly 3 capstone projects — one after each part — so learners apply SQL across the marketing data journey.
Customer Journey Data Map & Acquisition Report
Use customer, campaign, session and purchase data to show how marketing information connects across the customer journey and summarize acquisition channels.
Skills: marketing data structure, customer journey, acquisition analysis.
Campaign & Customer Performance Analysis
Query and join customer, campaign, order and engagement data to evaluate campaign activity, website behaviour and high-value customers.
Skills: SELECT, WHERE, JOIN, GROUP BY, HAVING.
Marketing Performance & ROI Dashboard
Build a decision-ready SQL analysis covering campaign performance, ROI, segments, funnels, attribution, CLV, revenue, retention and repeat purchases.
Skills: ROI, cohorts, attribution, CLV, retention, dashboard metrics.
Recommended SQL Learning Path After This Course
Assuming you completed SQL Basics and SQL Beginner, continue building deeper SQL capability after SQL Marketing with the following courses.
SQL Intermediate
Strengthen query logic with subqueries, CTEs, advanced filtering and data cleaning.
Explore SQL Intermediate →SQL Advance
Move into advanced set logic, window functions, performance and BI-ready SQL.
Explore SQL Advance →SQL AI-Assisted
Learn to generate, inspect, debug and verify SQL with AI while keeping human judgment in control.
Explore SQL AI-Assisted →SQL Data Analytics
Broaden into applied analytical SQL for BI, data engineering and machine-learning preparation.
Explore SQL Data Analytics →Course Details
Frequently Asked Questions
This course is designed for marketing professionals, digital marketers, CRM and lifecycle marketers, growth professionals, business analysts and learners who want practical SQL experience with customer and campaign data.
The course includes exactly 3 capstone projects: 1) Customer Journey Data Map & Acquisition Report, 2) Campaign & Customer Performance Analysis, and 3) Marketing Performance & ROI Dashboard.
The certificate of completion is issued by the Canadian Institute of Artificial Intelligence (CiAI).
Part 1 explains marketing analytics tables, customer-, campaign- and transaction-level data, CRM and marketing systems, key marketing fields, the customer journey and how marketing data connects.
Part 2 applies SELECT, WHERE, JOIN, GROUP BY and HAVING to customer, campaign, website, order and engagement data.
Part 3 covers campaign performance and ROI, customer segmentation and cohorts, conversion funnels, attribution, CLV, revenue, retention, churn, repeat purchases and marketing dashboards.
Yes. Learners use campaign, advertising and order data to summarize spend, conversions and revenue and support ROI reporting.
Yes. The course includes customer segmentation, cohort analysis, customer lifetime value and revenue analysis.
Yes. Learners analyze funnel stages and marketing touchpoints to understand conversion behaviour and channel contribution.
Assuming you completed SQL Basics and SQL Beginner, recommended next courses are SQL Intermediate, SQL Advance, SQL AI-Assisted and SQL Data Analytics.
For current subscription, cancellation and refund information, visit the DataSoSi FAQ page or Contact Us.
Meet the Creator of the Course
Learn from an educator and machine learning engineer working across analytics, AI, data science and applied business problems.
Dr. Mark Lokanan
Professor · Senior Machine Learning Engineer · Data Scientist · AI Specialist
Dr. Mark Lokanan is a professor at Royal Roads University and a Senior Machine Learning Engineer at Vedia. His work spans data science, machine learning, artificial intelligence, analytics, financial crime, and applied research. Drawing on both academic and industry experience, he designed SQL Marketing & Customer Analytics to help learners apply SQL to customer data, campaign performance, digital engagement, revenue, funnels, attribution and marketing decision-making.
