Visitor type
The Visitor type condition can be used in your goal setup to limit which users are counted as conversions.
However, in most cases, you do not need to use this condition in goals to compare performance between new and returning visitors.
Built-in segmentation in results
Lyftio already provides Visitor type as a filter in the results view.
This means you can compare performance between the two segments without creating separate goals for this.
When you should NOT use it in goals
If your goal is simply to compare how new vs returning visitors perform, you should:
- Create a standard goal (without this condition)
- Use the results filter to segment the data
This keeps your setup simpler and avoids unnecessary duplication of goals.
When to use it in goals
You should only use the Visitor type condition in a goal when you explicitly want to restrict which users can trigger that goal.
For example:
- Tracking a conversion that only makes sense for new users
- Measuring a KPI that should exclude returning visitors entirely
- Creating goals tied to specific stages in the user lifecycle
Example
You want to track how many first-time visitors complete a signup.
- Goal: Signup completed
- Condition: New visitors
Result:
- Only new visitors will be counted as conversions
- Returning visitors will not contribute to this goal
This is only eligable if your experiment targets both new and returning visitors. In most cases you would rather set the visitor type as an Audience condition instead to only track interactions of a specific visitor type.
Best practice
- Use results filters for comparison
- Use goal conditions only when you need to restrict tracking
This ensures:
- Cleaner goal setup
- More flexible analysis
- Less duplication
Summary
The Visitor type condition in goals allows you to limit which users are counted as conversions.
However:
- You usually don’t need it for comparison
- Lyftio already provides this segmentation in results
- It should only be used when you want to explicitly filter who can trigger a goal
This approach keeps your experiments simpler while still giving you full analytical flexibility.