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Leer Building Funnels with SQL | Funnel Analysis in SQL
SQL for Marketing Analytics

bookBuilding Funnels with SQL

Funnels are a foundational concept in marketing analytics, representing the journey users take through a predefined sequence of steps toward a desired action. Understanding funnels allows you to pinpoint where users drop off and where they convert, helping you optimize marketing strategies and improve conversion rates. Event-based data, which logs user actions as discrete events, is essential for funnel analysis because it enables you to track each user's progression through the funnel in detail.

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-- Example funnel_steps table defining the order of funnel events SELECT * FROM funnel_steps ORDER BY step_order;
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To analyze a funnel, you need to know how many users reach each step. SQL makes this possible by allowing you to count users at each funnel stage using event data. Typically, you group events by their type and count the number of distinct users who performed each event. This approach helps you visualize where users drop off and how many complete the funnel.

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-- SQL query to count distinct users at each funnel step SELECT e.event_type, COUNT(DISTINCT e.user_id) AS user_count FROM events e GROUP BY e.event_type ORDER BY MIN(e.event_timestamp);
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Write a SQL query that calculates how many distinct users reached each step in the funnel, using the events table. Your query should:

  • Group the results by event_type;
  • Count the number of distinct user_id values for each event_type;
  • Order the results so that the funnel steps appear in the order users would encounter them, using the earliest event_timestamp for each event_type (ascending).

Return two columns: event_type and user_count.

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Suggested prompts:

Can you explain how to interpret the funnel analysis results?

What are some common reasons for user drop-off at each funnel step?

How can I use this funnel data to improve my marketing strategy?

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bookBuilding Funnels with SQL

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Funnels are a foundational concept in marketing analytics, representing the journey users take through a predefined sequence of steps toward a desired action. Understanding funnels allows you to pinpoint where users drop off and where they convert, helping you optimize marketing strategies and improve conversion rates. Event-based data, which logs user actions as discrete events, is essential for funnel analysis because it enables you to track each user's progression through the funnel in detail.

1234
-- Example funnel_steps table defining the order of funnel events SELECT * FROM funnel_steps ORDER BY step_order;
copy

To analyze a funnel, you need to know how many users reach each step. SQL makes this possible by allowing you to count users at each funnel stage using event data. Typically, you group events by their type and count the number of distinct users who performed each event. This approach helps you visualize where users drop off and how many complete the funnel.

123456
-- SQL query to count distinct users at each funnel step SELECT e.event_type, COUNT(DISTINCT e.user_id) AS user_count FROM events e GROUP BY e.event_type ORDER BY MIN(e.event_timestamp);
copy
Taak

Swipe to start coding

Write a SQL query that calculates how many distinct users reached each step in the funnel, using the events table. Your query should:

  • Group the results by event_type;
  • Count the number of distinct user_id values for each event_type;
  • Order the results so that the funnel steps appear in the order users would encounter them, using the earliest event_timestamp for each event_type (ascending).

Return two columns: event_type and user_count.

Oplossing

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Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 2. Hoofdstuk 1
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