Use segments as dimensions in Analysis Workspace projects
Last update: April 23, 2025
- Topics:
- Workspace Basics
CREATED FOR:
- Beginner
- User
Learn how to compare and visualize segments when used as dimensions in Analysis Workspace projects. For more information, visit the documentation.
“Filters” have been renamed “segments” in the Customer Journey Analytics interface.

Transcript
In this video, I’ll show you how to use filters as dimensions in Analysis Workspace for Customer Journey Analytics. Now, while filters and dimensions each have their own primary function, filters can be used like dimensions in certain scenarios, and that’s the focus of what I’ll be showing you. Now normally, you would take a filter and drag and drop it into the drop zone here. This filter contains all events that occurred in 11 through 20 days from the current date. I’ve added this to my first panel in my project, and you can see that these metrics are updated based on this filter and relative to the date range that I’m using. Usually, this is how you would use filters. I’ll add the same filter to my top 10 pages panel. This one contains a table, among other visualizations. The page title is a dimension that was added from the dimensions panel in the left. This shows me the breakdown of sessions for each page title displayed based on the filter I applied at the top. So, what am I talking about when I say you can use filters as dimensions? One of the things you can do, and I have this empty freeform table right above, is put those segments into the table just like you would with dimensions. For example, I’ll use that 11 through 20 days filter and drag and drop it to the dimensions drop zone in the left of this table here. As you can see, it’s treated like a dimension. It even uses the correct container metric associated with the filter, which is events. Notice it even uses the label filters up here. Now I’ll add in a couple of others. When you do this, make sure the action is add and not breakdown though, before you release your mouse button. Okay, so now I have 1 through 5, 6 through 10, and 11 through 20 days. I can finish off my table the way I want to show it, so maybe I’ll sort by the filter name by clicking this arrow next to the filters heading right here. There’s a comparison I’ll show you now. I’d like to add a couple of metrics to this table. First, I’ll add sessions to the left of events and price total to the right of events. Now price total is reflected as revenue in the summary panel above. Okay, so why did I do this? Well, I wanted to show you that the metrics for the row with 11 through 20 days match up with the metrics in the first panel, which contains summary numbers for these metrics and have the 11 through 20 days filter applied at the panel level. So there’s 144.3k sessions, which is abbreviated in the summary section, and the full number is displayed in the table, which is 144,258. Now you might ask, is it better to apply the filter on the panel with the summary numbers, or is it better to use a table with each filter in a row and the metrics added to it in columns? First, if you want to look at a lot of different visualizations in the same panel, then drop the filter in the drop zone at the top. I’m using a lot of different panels in my project, so I’d have to drop this to each panel. It’s really just a design consideration. It is possible to drop all of those segments to the top of a panel, which is really helpful. Let me show you how that’s done. I’ll simply select all the filters I want. On a Mac, I’ll hold down the Command key while I select each of the filters, and if I was using a Windows machine, I would hold down the Control key. Then, as I hover over the filter’s drop zone, it tells me to hold down the Shift key as I release. Now I could select each filter separately and see how the metrics change as I do this. If you want a quick glance at multiple filters to see how they compare, then using the filters as dimensions in a table is really useful. You can even add a visualization to it like this. I’m adding a donut visualization. Now there’s another way we can treat a filter like a dimension. I’ll come down to my Top 10 Pages Visited table, and I’ll drag and drop one of my filters to one of the dimensions in the table to do a breakdown by that filter. I’ve broken down the Category 5 page by the Demographic Group 35 through 44 filter. This is something typically done with dimensions, but I’ve just shown you how to do it with a filter. And that’s a wrap! I’ve shown you how filters can be used as dimensions and explained why you would want to do this. Have a great day!
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Customer Journey Analytics
- Customer Journey Analytics overview
- Customer Journey Analytics basics
- Architecture
- Data prep and planning
- Connections
- Visitor identification
- Data views
- Overview of configuring data views for CJA
- Basic configuration for data views
- Configure component settings in data views
- Component type settings in data views
- Create summary-level data sources
- Create derived fields
- Use the Math function in derived fields
- Use the Next or Previous function in derived fields
- Formatting metrics in data views
- Configure substring component settings
- Include or exclude metric values in data views
- Creating value buckets in data views for analysis
- Include or exclude dimension values in data views
- Binding Dimensions in data views
- Configure no value options in data views
- Attribution settings in data views
- Currency conversion
- Analysis Workspace
- Workspace projects
- Panels
- Visualizations
- Create cross-channel visualizations
- Cross-channel attribution
- Create intelligent captions
- Add area visualizations
- Add bar visualizations
- Add bullet graph visualizations
- Add donut visualizations
- Add line visualizations
- Use summary visualizations
- Add text visualizations
- Use the scatterplot visualization
- Add the tree map visualization
- Create fully stacked visualizations
- Add forecasting to your visualization
- Annotations
- Curate and share
- Tips and tricks
- Adobe Product Analytics
- Guided analysis
- Components
- Content Analytics
- Dashboards (scorecards)
- Exporting
- Experience Platform Integration
- Use cases
- Blueprints