Add new data to a connection in Customer Journey Analytics

Welcome to the Add Past Data to an Existing Connection Training. There are many times when we want to add additional time based data to our analysis. If we were using standard Adobe analytics, we would use data sources to bring in this non website data. Let’s walk through a little scenario here. We’re on a team that’s been using AEP and CJA for months analyzing our customers web behavior. But we know that this isn’t the whole picture. Now someone comes in from IT and says, hey, we’ve just started tracking call center data last quarter could this be of any help to you guys? Our coworker says hey, can we add this data to our analysis even though it happened in the past ? To which you answer an emphatic well, yes. And then you also add hey, do you also have the brick and mortar point of sale data, we could use that too. So in a nutshell, we’re just trying to fold in or merge other channel data into the web data that we already have in AEP. Now the benefits of integrating this type of data is that AEP can accept data from virtually any source and attribution settings take into account all channel touch points, and more complete data leads to more advanced filtering. And lastly, all of these lead to a holistic view of our customers journey. So what’s needed to merge this added data, there are three key components. First, the data must be on boarded in any event type data set. Second, each event in the data set must have a timestamp of when the event happened. And third, we need an ID that links this data to an existing data set.

As we onboard our additional data, here are a few facts about AEP and CJA that we should understand. It doesn’t matter when the data is added to AEP and past data can be added to an existing or a new data set. A CJA data connection can have multiple AEP datasets.

And lastly, a CJA Data view can have only one connection.

Now because we added past data to our analysis, we have to be aware of the impact that this will have on our reporting. An example of this is session length. In a Data View the default session timeout is 30 minutes of inactivity. Now, this is across all of our data sources. If we only have our web data in CJA, the session would look like it was just the time we spent on our website. But what if the reality was that our customer was online looking at a product, and they pick up the phone and talk to our call center, and then our customer went to our outlet store two blocks away and bought that product. Once this additional data is on boarded, the holistic session length would expand to include the call center questions and the in store purchase. Because we now have more complete data in our reports, any static versions are inaccurate. This is why we recommend doing your analysis in the CJA workspace interface. This way, you will always have the most complete data regardless of the time period you are analyzing. Attribution is another feature that is highly impacted by this Data Merge. The added data brings a more accurate allocation of how all touchpoints influenced our conversions.

And filters are exponentially more effective with additional data points. Thanks for taking this training. -