Building Engagement Levels

Overview

KittyCarts is a fictional eCommerce company that sells monthly subscription boxes containing feline care products. In the accompanying KittyCarts app, subscribers can track and customize their monthly boxes, view their box history, and purchase specific products they liked from their boxes. In addition, non-subscribers have access to features such as KittyCam, which allows them to watch their cats through connected webcams.

KittyCarts wants to isolate the population of app users who are subscribers, and then bucket them by engagement level. They want to see:

  • Level 1:  Users who have opened the app 1-3 times a month
  • Level 2: Users who have opened the app 4-6 times a month
  • Level 3: Users who have opened the app 7 times or more a month

This information will allow them to create campaigns or promotions tied to a user’s engagement level.

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Task: Separate subscribers into three buckets based on engagement level.

 

Open the Segmentation Tool: Let’s click the Segmentation icon on the left side of the screen.

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Select Event: Since we are defining user engagement by app opens, the best event to begin our analysis with is “App Session”. Every time a user opens their app, a session begins.

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  • Let’s start by dragging “App Session” into the query builder.
  • Next, set it to “Users who performed” to give us the number of unique users who opened the app.

 

Create a Filter: Right now, we’re only interested in the engagement levels of app users who are also subscribers. We can modify our event with a “Where” clause to create a filter that shows us only subscribers.

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  • Let’s go into User Properties and select “Subscriber?”
  • Drag it into the “Where” dropzone and  set it to “Where users’ Subscriber? is equal to Yes”.

Using this filter, we should only see users who did App Session and who were also subscribers.

 

Use a “For” Clause: Now that we have a filter based on subscriber status, let’s finish expanding it to create our first engagement level: Users who have opened the app 1-3 times a month. We’ll be looking at subscribers who have opened the KittyCarts app 1-3 times in the past month. To do this, we will add a “For” clause  to our row.

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  • Let’s select the event “App Session” and drag it towards the “Where” dropzone
  • Once the event is picked up, the dropzone text will change to “For users who did/not”
  • Let’s drop in the event, then edit the clause.  The query row should read: “For users who also did App Session greater than or equal to 1 time within the prior 30 days”.

Our analysis now shows us subscribers who had an app session, who also had 1 or more app sessions within the prior 30 days.

 

Add a Second “For” Clause: We’re almost done creating our first engagement level. So far, we’ve narrowed it down to subscribers who had an app session, who also had 1 or more sessions within the prior 30 days.

Now, let’s limit this group to users who had 1-3 sessions in the past month. This can be done by adding a second “For” clause to our query row.

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  • Select the event “App Session” and drag it towards a “Where” dropzone.
  • Once the event is recognized, the dropzone text changes to “For users who did/not”. After the event is dropped, our new “And” Clause is added.
  • The query row should read: “And did App Session less than or equal to 3 times within the prior 30 days”.

Our query row has now limited our results to to subscribers who had an app session, who also had 1 to 3 sessions within the prior 30 days

  

Label the Row: Let’s label our first engagement level query row. In the bottom right corner of the query row, type in “Level 1”.

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Duplicate the Row: Now, let’s create a second engagement level for those with 4-6 app sessions per month using the same framework that we used to create our first engagement level. However, instead of recreating it from scratch, we can simply duplicate the row we’ve already created and then modify the duplicated version.

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  • Let’s open the query row menu and click “Duplicate Row”.

 

Modify the Duplicated Row: Let’s modify our duplicated row.

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  • Change the “For” clause to “greater than or equal to 4 times”
  • Change the “And” clause to “less than or equal to 6 times”
  • Label the row as “Level 2”

 

Duplicate the Row: Now, let’s create a third engagement level for those with greater than 7 app sessions per month. We can duplicate a previous row to get started. Let’s duplicate our row “Level 2”

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Modify the Duplicated Row: Let’s modify our duplicated row. This one will be a little different from our previous rows, since we do not have a maximum number of app sessions for this bracket.

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  • Change the “For” clause to “greater than or equal to 7 times”
  • Delete the second “For” clause
  • Label the row as “Level 3”

 

The three query rows should read:

  1. Users who performed App Session Where users’ Subscriber? is equal to Yes  
    1. For users who also did App Session greater than or equal to 1 time within the prior 30 days
    2. And did App Session less than or equal to 3 times within the prior 30 days

 

  1. Users who performed App Session Where users’ Subscriber? is equal to Yes
    1. For users who also did App Session greater than or equal to 4 times within the prior 30 days
    2. And did App Session less than or equal to 6 times within the prior 30 days

 

  1. Users who performed App Session Where users’ Subscriber? is equal to Yes  
    1. For users who also did App Session greater than or equal to 7 times within the prior 30 days

 

View Results: We now have our finished engagement level analysis.

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Observation

  • Level 1 (1-3 sessions per month) represents the majority of the user base.
  • Level 2 (4-6 sessions per month) while not the majority, represents a sizeable number of users.
  • Level 3 (7+ sessions per month) represents a negligibly low number of users.

 With this information, KittyCarts should create engagement strategies for each of these buckets of users. They should also create targeted promotions and upsells for their more dedicated users in Levels 2 and 3.

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