Add components to the freeform panel

In this video, we’ll look at how to work with Freeform Panels in Customer Journey Analytics. Freeform Panels let you explore, compare and correlate your customer experience data through a flexible drag-and-drop interface. They’re the default panel type when you create a new project and are a great starting point for exploring data. If you’ve previously worked with Analysis Workspace in Adobe Analytics, the interface in Customer Journey Analytics will feel similar. The main difference is that we’re dealing with Adobe Experience Platform data instead of the props and eVars you’d find in Analytics. Let’s jump into a new project and see how this works. When we first open the project, a Freeform panel is already set up for us by default. So, we can start adding our metrics and dimensions right away. Before building, though, check the selected data view in the top right corner. The data view controls which components like dimensions and metrics are available to be used and how they’re named. Next, let’s set our date range. The default is “This month”, but I’ll switch it to the “Last 90 days” for a more consistent view over time. Now, let’s add some components. In the left rail, select the abacus icon to open the Components tab. This is where we’ll find all the metrics, dimensions, segments, and other components we can include in our analysis. We can see our selected data view on the top as a reminder of what set of available options we’re working with. For this example, we’ll build a table showing the top ten most purchased products for Luma over the past 90 days. We’ll start by adding the Product Name dimension. Customer Journey Analytics can incorporate data from many sources, so we need to be careful to choose the right field from the list. When I search “Product Name”, multiple options appear. The one that we want is tied to the cart at purchase time. Since Customer Journey Analytics can pull from multiple channels, it’s not uncommon to see overlapping or conflicting component names in a data view. If anything is unclear, be sure to reach out to your data view admin. They can rename components for clarity in a future update without affecting the functionality of your table. All right, so we know we’ve got the right dimension here. So we’ll drop it onto the table. You’ll see a list of product names appear. And “Events” is set as the default metric. In our case, we’re specifically interested in purchases though. So we’ll search for the “Purchases” metric instead. Note that when we’re dragging components over the table, helpful tooltips appear, showing us that if we drop it in the center of the column, it will replace the current metric, while dropping it on the edge will add it as a new one instead. In this case, we’ll drop it on the center to replace events with purchases. The table automatically resorts, and now the products are ranked by purchase count. To limit this to the top ten, I’ll adjust the rows setting.

And while I’m here, I’ll also add a second metric: “Price Total”. Just so we can show actual revenue alongside purchase volume. Nice. We now have a functioning freeform table that’ll dynamically give us the top ten most purchased products in the last 90 days. Let’s quickly rename the table to “Top Selling Products” to make our report easier to read. Now, let’s get to the fun part and add some visualizations. When working with a freeform table, you can right click on any row or column and select Visualize to get a list of options. There are many visualization types–too many to cover here-- so we’ll just show a couple examples. First, we’ll double click the Purchases metric to highlight its respective column. And then we’ll go to Visualize.

And then we’ll select “Bar” to produce the classic bar chart. Once the chart appears, we’ll click the gear icon, go to Data Source and then lock the selection so the chart doesn’t change display if the user selects a different part of the table. We’ll repeat the process for Price Total, this time choosing a donut chart.

Again, will lock the selection to ensure that it stays in sync with the table. And that’s it. Two charts built from the same table, giving us a clearer picture of what products are selling best and how they compare in terms of total revenue. You can resize or rearrange these elements however you like and give them clear names for presentation.

So that was a brief overview of working with Freeform Panels in Customer Journey Analytics. We only scratched the surface when it comes to the kinds of insights and visualizations you can build with these panels, so we strongly encourage you to experiment with different setups and to check out the documentation for more information on the other visualization types.

Thanks for watching.