11.4 Data Preparation in Customer Journey Analytics
Customer Journey Analytics - Data preparation in Analysis Workspace
Last updated
Customer Journey Analytics - Data preparation in Analysis Workspace
Last updated
Understand the Analysis Workspace UI in CJA
Understand the concepts of data preparation in Analysis Workspace
Learn how to do data calculations
Analysis Workspace removes all of the typical limitations of a single Analytics report. It provides a robust, flexible canvas for building custom analysis projects. Drag-and-drop any number of data tables, visualizations, and components (dimensions, Metrics, segments, and time granularities) to a project. Instantly create breakdowns and segments, create cohorts for analysis, create alerts, compare segments, do flow and fallout analysis, and curate and schedule reports for sharing with anyone in your business.
Customer Journey Analytics brings this solution on top of Platform data. We highly recommend watching this four-minute overview video:
If you haven't used Analysis Workspace before, we highly recommend watching this video:
Now it's time to create your first CJA project. Go to the projects tab inside of CJA. Click Create new.
You'll then see this. Select Blank project and then click Create.
You'll then see an empty project.
First, make sure to select the correct Data View in the upper right corner of your screen. In this example, the Data View to select is vangeluwe - Omnichannel Data View.
Next, you'll save your project and give it a name. You can use the following command to save:
| OS | Short cut |
|---|---|
Windows | Control + S |
Mac | Command + S |
You'll see this popup:
Please use this naming convention:
| Name | Description |
|---|---|
|
|
Next, click Save.
Although we have organized all the components in the Data View, you still need to adapt some of them, so that business users are ready to start their analysis. Also, during any analysis you can create calculated metric to go deeper on the insights finding.
As an example we will create a calculated Conversion Rate using the Purchases metric/event we defined on the Data View.
Let's start opening the calculated metric builder. Click on the + to create your first Calculated Metric in Analysis Workspace.
The Calculated Metric Builder will show up:
Find the Purchases in the list of Metrics in the left side menu. Under Metrics click Show all
Now drag an drop the Purchases metric in to the calculated metric definition.
Typically, conversion rate means Conversions / Sessions. So let's do the same calculation in the calculated Metric definition canvas. Find the Sessions metric and drag and drop it into the definition builder, under the Purchases event.
Notice that the division operator is automatically selected.
The conversion rate is commonly represented in percentage. So, let's change the format to be percentage and also select 2 decimals.
Finally, Change the name and description of the calculated metric:
| Title | Description |
|---|---|
Conversion Rate | Conversion Rate |
You will have something like this on your screen:
Don't forget to Save the Calculated Metric.
Calculations are not meant to be only for Metrics. Before starting any analysis it's also interesting to create some Calculated Dimensions. This basically meant segments back in Adobe Analytics. In Customer Journey Analytics, these segments are called Filters.
Creating filters will help business users to start the analysis with some valuable calculated dimensions. This will automate some tasks as well as helping on the adoption part. Here are some examples:
Own Media, Paid Media,
New vs Returning visits
Customers with Abandoned Cart
These filters can be created before or during the analysis part (which you'll do in the next exercise).
Time Dimensions are another type of calculated dimensions. Some are already create, but you also have the ability to create your own custom Time Dimensions at the data preparation phase.
These Calculated Time Dimensions we will help analysts and business users to remember important dates and use them to filter and change the reporting time. Typical questions and doubts that come to our minds when we do analysis:
When was Black Friday last year? 21th-29th?
When did we run that TV campaign in December?
From when to when did we do the 2018 Summer Sales? I want to compare it against 2019. By the way, do you know the exact days in 2019?
You've now finished the data preparation exercise using CJA Analysis Workspace.
