Cross-Channel Attribution in Customer Journey Analytics

In this video, we will show how you can use visualizations to show attribution (give credit) across channels in Customer Journey Analytics.

Transcript
Hey everybody, this is Doug. In this video, I want to talk about Cross-Channel Attribution in Customer Journey Analytics, or really how we show cross-channel attribution individualization in Customer Journey Analytics. So, we’re going to add a visualization, and we’re going to make it really easy with a freeform table. And we’re going to drop that in, and we’re going to scroll down a little bit. Now, when we’re going to attribute something, we need something to attribute, we need something to attribute it to, or give it credit for. So we’re going to start off with call duration, minutes, okay, so we want to understand more about what is causing people to call in to our call center. So this is call center data, this is a metric coming from our call center data, and certainly we could put other call center data here like the call reason, and that would be good, that’d be good to know, you know how many minutes for this reason or that reason, but it really gets super interesting when we can actually cross our data sources and attribute these minutes to some other kind of data. So in this case, we are going to go to our Point of Sale data and look for store location. And now when we drag this store location data over and replace this day right there, we can see the number of call duration minutes, again, from our call center data, and how that attributes back to our point of sale, our retail data, in the different store locations. And this is only possible because we are using the same person ID between these two data sets. So it really treats these two datasets like one data set, and you can see the store locations that tied to the most call duration minutes. And number one is Salt Lake City here, and so you can see how many minutes were attributed to that. And if we wanted to, we can even take it down deeper and say, "Well, why were they calling then, “what is the call reason?” And we drag that over to Salt Lake and break it down.
And Yikes, we see it’s refunds and customer complaints, not a lot of people calling in for website help, or forgot password, or apparently nobody calling in to buy stuff, but rather people are calling in to get refunds and to complain. So we need to talk to everybody at Salt Lake and see what’s going on. And before I let you go, I just want to talk about attribution for a minute. Remember that the attribution models can be set in the Data View. So I’m going to click on this tab which has a Data View up, you can see that for store location, it has Last Touch as the model and expiration is person based on the reporting window. So in other words, all the visits for that person within the reporting timeframe. And so that is the attribution model that is using Last Touch. Now, our call duration minutes was the metric and that actually has higher precedence. So if I look at call duration, you can see here as I click on it, that it has no attribution settings. So because this has no attribution settings, then it goes to the store location which we saw had last touch, and so by default, this combination of store location and call duration is using the Last Touch attribution model from Attribution IQ. And if you are familiar with Attribution IQ from Analysis Workspace in general, then you know that you can change that by going to the gears, scrolling down, use non-default attribution model, and you can check that, and you can use any of these attribution models to give credit to these different store locations in a different manner. So anyway, just wanted to show you attribution across channels in Customer Journey Analytics. Good luck. -

For more information about Customer Journey Analytics, visit the documentation.

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