How to create custom reports in Google Analytics

The goal of creating a custom swivl report in Google Analytics is to compare the behavior of swivl users to non-swivl users, focusing on specific metrics like rental submissions, contact form submissions, and/or revenue. This will help you understand how swivl impacts user engagement and retention.

Creating the different Segments

1. Navigate to Explore: Click "Blank" to create a new exploration.
2. Name the Exploration: Give it a meaningful name like "swivl events"
3. Create the swivl User Segments:
   1. Add a Segment: Click "Add a Segment" and select "User Segment"
   2. Name the Segment: Call it "swivl Users"
   3. Add a Condition: Search for "swivl Chat User" and select it.
   4. Set the Filter: Choose "is one of" and enter "New" and "Return" on separate lines. This will include new and returning swivl chat users.
   5. Save and Apply: Click "Save and Apply" to save the segment.
4. Create a Non-swivl Users Segment:
   1. Add a Segment: Click "Add Segment" and select "User Segment".
   2. Name the Segment: Call it "Non-swivl Users".
   3. Add a Condition: Search for "swivl Chat User" and select it.
   4. Set the Filter: Choose "Is not one of" and enter "New" and "Return" on separate lines.
   5. Save and Apply: Click "Save and Apply" to save the Segment.

Building the Report

1. Add Dimensions:
   1. Event: Select "Event Name" and "Key Event".
2. Add Metrics:
   1. Event: Select "Event Count".
   2. User: Select "Total Users".
3. Rows and Values:
   1. Drag "Event Name" to the Rows section and set "Show Rows" to 100.
   2. Drag "Event Count" and "Total Users" to the Values section.

Filtering for Key Events (optional)

1. Add Filter: Drag "Is key event" to the Filters section.
2. Set Condition: Choose "Exactly matches".
3. Enter Expression: Type "TRUE".
4. Click "Apply" to filter for key events.

Interpreting the Results

1. Event Frequency:

   1. Compare Event Counts: Examine the "Event Count" for each event to see how often swivl users and non-swivl users are triggering these events.
   2. Identify Differences: Look for significant differences in event frequency between the two groups. This can highlight areas where swivl may be having a positive impact.

2. User Engagement:

   1. Total Users: Analyze the "Total Users" metric to understand how many unique users are engaging with each event.
   2. Engagement Patterns: Compare the engagement patterns of swivl users and non-swivl users. Are swivl users more or less likely to engage with specific events?

3. Key Event Performance:

   1. Filter for Key Events: If you've filtered the report for key events, analyze their performance. Are swivl users more or less likely to trigger key events compared to non-swivl users?
   2. Conversion Rates: Calculate conversion rates for key events to measure how effectively swivl is driving desired actions.