SELECT DISTINCT app _idįunnel_Step_1 ON app _id = Funnel_Step_1.user_id Next, we use the 'Funnel_Step_1' view to construct the view for the second step in the funnel: CREATE VIEW Funnel_Step_2 AS ( This view, which we name 'Funnel_Step_1', captures the users who opened the product during March 1st and 2nd. WHERE DATE(event_time) BETWEEN ' ' AND ' ' Query Objective: Obtain a List of Users for Each Step of a Funnel CREATE VIEW Funnel_Step_1 AS ( NOTE: Tracking the number of users who make it (and do not make it) to each stage in a funnel is crucial, as it identifies which parts of your product's user experience flow are smooth and which parts are bottlenecks that need improvement.
The values in red are what you will need to replace with your own. To do this, we will create each step in the funnel as a SQL "View" - essentially a saved query that we can use without retyping the query.
In this section, we will demonstrate how to do funnel analysis in Redshift by using the three-stage texting app funnel described above as an example. This article is maintained as a courtesy.įor example, for a messaging app, the key initial funnel might have three steps: NOTE: For most customers, the Help Center article on exporting Amplitude data to Redshift will be more useful. For almost any product, there are key sequences of events that users should progress through in order to successfully begin or continue using the product this sequence is commonly called a "funnel".