Analytics for Target (A4T) Panel in Analysis Workspace

Last update: 2021-08-30
  • Created for:
  • Intermediate

The Analytics for Target (A4T) panel lets you analyze your Adobe Target activities and experiences, with lift and confidence, in Analysis Workspace.


Hi, this is Jen Lasser with Adobe Analytics product management. In this video, I’m going to give you an overview of the Analytics for Target panel in Analysis Workspace. For those that aren’t familiar with Analytics for Target or A4T for short, it’s an integration between Adobe Target and Adobe Analytics. It enables Adobe Target to use Analytics data as its data source. And it enables Target users to analyze their Target activities and experiences, in Adobe Analytics. This unlocks deep Analytics capabilities, available through Analysis Workspace, such as freeform analysis, deep segmentation, journey visualizations, and much more. So, let’s take a look at what this Analytics for Target panel does for you. It’s available in the left rail under panels, and you simply drag it over to the middle. The first thing you want to do when you bring over the A4T panel, is select the activity you want to analyze. You can choose from a list of activities, and the list will be populated by the last six months of activities. Or you can drag over one from the left rail, just like you normally would. So, we’re going to select the AAC landing page activity. And notice, it happened really fast, but we retrieved a bit of information for you. We brought in all the experiences that relate to this activity, and we’ve selected one as the control. You can always change that through this drop down. We also updated the calendar date range, to reflect the active date range for this activity. This is passed over from Adobe Target. And, if you deactivate your activity in Target, there will be an end date applied here as well. You can select your normalizing metric. Visitors is typically the default, but Visits and Impressions are also an option. Normalizing metric is used as the denominator in the Lift calculation. The last thing you need to do is choose success metrics. And these can be any standard success metric, in Adobe Analytics. You can choose up to three success metrics and these will all have Lift and Confidence, calculated for them. You can search through the drop down, or you can type in what you’re looking for. So, I’m going to go ahead and add three different metrics here so you can see how this renders in the panel. Just like with the other drop downs in this building experience, you can also drag and drop over metrics from the left rail. The advantage of picking them from the drop down list, however, is that we’ve pre-populated the list with all of the acceptable or supported metrics, in this panel. So, we’ll go ahead and click Build. Like with many of our other panels, there is a progress bar up at the top, which will give you an indication of how long the panel is going to take to build. So, let’s take a look at what the panel built for us. First of all, at the top, there’s a summary line that shows you all the settings that you selected. Now, for each metric that you chose in the building state, we will output one table, and one trended conversion rate graph for you. Starting with the table, experiences will be down the rows, with the control experience in bold. In the columns, the first column will be the normalizing metric you selected. The second column will be the success metric you selected. And then, conversion rate is the division of those two. Lift and Confidence are now added to the table and they work off of the conversion rate column. Lift Mid is what you traditionally saw on Reports and Analytics. It’s a midpoint of the Lift range. Lift Lower and Upper are the lower and upper bounds of that range. If at any point, you want to understand the definition of these metrics, you can always hover the eye here, to get a better understanding of what they mean. Confidence is the final metric in this table. And, it also has a definition. And it’s based on a student’s T-test model, just like it was in Reports and Analytics. We’ve also applied a static or custom conditional formatting range to the Confidence column. And it has thresholds of 75,85, and 95%. So, the red, yellow, green coloring will change, as it approaches those different midpoints. To analyze this table, you want to focus on the Control row. Notice that Lift and Confidence with the Control will be zeroed out because that’s what all the variance experiences are compared against. And then, you want to look at the variance compared to that. What is their Lift and Confidence of that lift, compared to the control? Now, down below the table, we also have a conversion rate chart, for the metrics you selected. Now, this is demo data, so it’s not producing that great of a chart. But you can see here that we have each experience, and we have its trended conversion rate. At any point, if you want to change the granularity of this chart, you can go ahead and click the gear, and then, change this to any other granularity you’d like. The second and third metrics that you selected, when you built the panel, will be repeated in the same format further down. So, we selected activity impressions, which will have its own table and visualization. And then, our third metric was page URL instances. And we output a table and a visualization for that as well. Now at any point, if you want to make any edits to your panel, you can simply click the Edit pencil, and change your inputs and then rebuild. And, if you have any questions, you can click the question mark up here at the top and it will explain all the builder parameters. And link out to more rich documentation if you need assistance. This has been an overview of the Analytics for Target panel in Analysis Workspace. We hope that both Target users and analysts alike, get a lot of value out of being able to deeply analyze their Target activities and experiences, with Lift and Confidence in Analysis Workspace. -

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