Marketing Data Analyst — SQL for Marketing

Retrieving Marketing Data - Description: Learn the essential SELECT statement in SQL. This is the cornerstone of retrieving data from databases. Explore the basic syntax, SELECT *, selecting specific columns, and using FROM to specify tables. Practice retrieving data from a sample dataset. Focus on common marketing-related fields. - Specific Resources or Activities: - Resource: Follow a beginner-friendly SQL tutorial focusing on SELECT statements (e.g., Codecademy's SQL course, DataCamp's SQL Fundamentals). - Activity: Practice writing SELECT statements against a simple online SQL database (e.g., using a website like SQLZoo or db-fiddle.com) with a sample marketing dataset (e.g., customer data, campaign data). Try selecting all columns, then specific columns like customer_id, email, and campaign_name. - Expected Outcomes: Be able to write basic SELECT statements to retrieve data from a database, understand the purpose of SELECT, FROM, and the asterisk (*), and select specific columns relevant to marketing.

• Description: Learn how to filter data using the WHERE clause. This allows you to retrieve only the specific data you need. Explore comparison operators (=, !=, <, >), and logical operators (AND, OR, NOT). Practice filtering data based on criteria relevant to marketing campaigns and customer segments. - Specific Resources or Activities: - Resource: Continue with your chosen SQL tutorial, focusing on the WHERE clause and operators. - Activity: Practice filtering data using WHERE. Example: Select customers registered after a certain date, or customers who clicked on a specific ad. Use your online SQL database and sample marketing dataset. Experiment with different operators. - Expected Outcomes: Understand how to use the WHERE clause to filter data, use comparison and logical operators effectively, and apply these skills to filter marketing data based on specific criteria.

• Description: Learn to sort data using the ORDER BY clause (ascending and descending order) and limit the number of results returned using the LIMIT clause. These techniques are essential for analyzing trends and focusing on relevant data. - Specific Resources or Activities: - Resource: Review the ORDER BY and LIMIT sections of your SQL tutorial. - Activity: Practice sorting data. Example: Order customers by registration date, or order campaigns by their click-through rate. Use LIMIT to see the top 10 campaigns. Continue using your online SQL database and sample marketing dataset. - Expected Outcomes: Know how to sort data using ORDER BY, understand the difference between ascending and descending order, and use LIMIT to restrict the number of results. Apply these skills to analyze marketing data.

Calculating Marketing Metrics - Description: Introduce aggregate functions, the tools that let you calculate key marketing metrics such as totals, averages, minimums, maximums, and counts. Learn COUNT(), SUM(), AVG(), MIN(), and MAX(). Apply them to analyze campaign performance and customer behavior. - Specific Resources or Activities: - Resource: Learn about aggregate functions in your SQL tutorial. - Activity: Practice using aggregate functions. Example: Calculate the total number of customers, the average order value, the maximum and minimum conversion rates for a campaign, and the number of clicks on a particular ad. Use your online SQL database and sample marketing dataset. - Expected Outcomes: Understand the purpose of aggregate functions and be able to use COUNT(), SUM(), AVG(), MIN(), and MAX() to calculate key marketing metrics.

Segmentation and Analysis - Description: Learn to group data using the GROUP BY clause. Combine it with aggregate functions to analyze data at a more granular level. Explore using HAVING to filter results based on aggregated values. Apply these concepts to customer segmentation and campaign analysis. - Specific Resources or Activities: - Resource: Study the GROUP BY and HAVING sections of your SQL tutorial. - Activity: Practice grouping and filtering data. Example: Group customers by their geographic location and calculate their total purchase value. Filter out any segment that has fewer than 100 customers. Use your online SQL database and sample marketing dataset. - Expected Outcomes: Understand the function of GROUP BY and HAVING and be able to use them with aggregate functions for data analysis, focusing on customer segmentation and campaign analysis.

Combining Marketing Data - Description: Introduce JOIN operations, allowing you to combine data from multiple tables. Learn about INNER JOIN, the most common type of join, and understand how to relate tables based on shared keys (e.g., customer ID, campaign ID). This is vital for connecting marketing data from different sources. - Specific Resources or Activities: - Resource: Review a tutorial that explains different types of JOINs, focusing on INNER JOIN. - Activity: Practice joining tables. Example: Join the customers table with the orders table to analyze customer purchase history, or join campaigns and clicks tables to analyze campaign performance metrics. Use your online SQL database and sample marketing dataset and work through joining example queries. - Expected Outcomes: Understand how to use INNER JOIN to combine data from multiple tables and apply joins to analyze relationships between marketing data from different sources.