User-level vs. session-level vs. event-level vs. transaction-level data

In product analytics, data is organized at different levels depending on what you want to analyze. Understanding these levels is essential because each one answers a different type of business question. Rather than looking at all data the same way, analysts separate it into user-level, session-level, event-level, and transaction-level data.

User-level data focuses on the individual user. Each row represents one user and includes information such as signup date, country, device, and acquisition channel. This level is useful for understanding who the users are and how different groups behave.

Session-level data focuses on user visits. Each row represents a session, showing when a user entered the product, how long they stayed, and where they came from. This level helps analyze engagement and usage patterns.

Event-level data is the most detailed level. Each row represents a specific action taken by a user, such as logging in, clicking a button, or using a feature. This level is used to understand behavior inside the product.

Transaction-level data focuses on conversions. Each row represents a purchase or completed action that generates value for the business. This level is used to analyze revenue and product success.

For beginners, the goal is to:

• Understand the difference between each level of data
• Identify which table corresponds to each level
• Recognize how these levels support different types of analysis
• Learn how to retrieve data from each level

• User profiles and segmentation
• Session activity and engagement
• User actions and behavior
• Purchases and revenue

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The Basic Pattern

SELECT column_name
FROM table_name;
  

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Examples

Example 1 — View User-Level Data

Example 2 — View Session-Level Data

Example 3 — View Event-Level Data

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Practice Tasks (Your Turn!)

Task 1

View the user ID and country from the users table.

Task 2

View the session ID and session start time from the sessions table.

Task 3

View the order ID and total amount from the orders table.