Learn how to use the Attribution Panel and Lookback Window to understand customer behavior and customize how dimension items get credit for success events.
As soon as I thought about the Attribution Panel and Lookback Window, I was reminded of the song “Back in Time” by Huey Lewis and the News; then of course, I was also reminded that our typical response to many new tools like these is to just put off trying to use it, because they look so complicated.
I mean really, just look at all those options, switches, panels, readouts, and knobs. And seriously, let’s talk about that flux capacitor. Wait, did I just say flux capacitor?
OK, I will admit the Attribution Panel is a fairly complex tool; however, our typical job as analysts, day in and day out, is to use a highly complex tool to look at what happened in the past. That tool is called Adobe Analytics!
Therefore, why should we allow something like a little fear to stand in the way of such a cool and powerful tool that allows us to literally look backward in time every day?
We’re all about that stuff, right? RIGHT???!! (I mean, c’mon, I’m pretty sure it’s still OK and “politically correct” to call us geeks?)
Ah, who cares? Gear up, Geeks, Nerds, Goobers, Dweebs, and Techies (yes even the Trekkies), I can hear the car stereo now:
“So take me away, I don’t mind! But you better promise me… I’LL BE BACK IN TIME!”
I have your attention, now, right? Great!
Let’s break things down a little bit. Now that we’re all excited about time travel, let’s take a step back and establish what the Attribution Panel really is:
No, no, no, no, no! Let’s not get distracted just yet. Maybe, let’s try that again:
In Attribution, simply consider how events/actions might be caused by an individual, several individuals, or one or any number of different things over time.
According to Adobe, attribution gives analysts the ability to customize how dimension items get credit for success events. In fact, no given customer journey is ever truly linear and is less often predictable. Moreso, each customer will proceed at their own pace; often they might double back, stall, drop out, or engage in other non-linear behavior. These organic actions make it difficult or practically impossible to know the impact of marketing efforts across the customer journey. It also hampers efforts to tie multiple channels of data together.
Does any of this sound familiar to you? Think about it in the context of Marty McFly’s journey:
From the point when he fled the Twin Pines Mall parking lot to when he literally threw himself out of the DeLorean before it was obliterated by a 210-ton locomotive seems far from linear, and it’s nothing anyone could have predicted.
Yet, through the power of movie magic, we get to follow Marty’s path through time and understand all of his touchpoints, his stalls, double-backs, and dropouts.
In real life, we get to use the Attribution Panel to see several different things. For instance, the Attribution Models show us how our conversions are distributed across hits in any particular group.
Simply put, if 10 people press a button to step through a door, our Attribution Models are going to tell us which of those 10 people we want to give the credit for pressing that button. With that in mind, here are some examples of how the attribution models might affect those 10 people:
For additional information about this and the remaining Attribution Models, click here.
To make this even more interesting, let’s talk about the Lookback Windows.
Yup, here we go - take us BACK IN TIME!! Because here’s where the fun begins!
Adobe defines Lookback Windows as “the amount of time a conversion should look back to include touch points. Attribution models that give more credit to first interactions see larger differences when viewing different lookback windows.”
If you’ve seen ALL of the Back to the Future movies, then you know Marty McFly went back in time more than once, and you also know he went back to 1955 more than once. If we hinge upon the acquisition of “Gray’s Sports Almanac” as our conversion event, then consider the following:
Depending on our Attribution Model and Lookback Window, we can end up with some interesting scenarios:
And at this point, I hope you’re starting to get the idea.
So, what does all this mean for us as analysts?
The Attribution Panel and Lookback Window give us the power to look beyond the simple, surface-level data and dive deeper into the customer journey. By understanding which touchpoints had the greatest impact on conversions, we can make informed decisions about our marketing strategies and allocate resources more effectively.
Remember, after you have your Attribution Models and Lookback Windows selected, you still have the ability to further manipulate your data by filtering it with a segment or any other component you wish. Furthermore, after the Panel is rendered, you have all the functionality of a traditional Workspace, which means you’re officially licensed to drive 88 mph!
Now that you’ve got the concepts down, imagine you’re running a marketing campaign and trying to determine which channel is the most effective for driving conversions. With the help of the Attribution Panel, you can see not only the Last Touch, but also the First Touch, Same Touch, and any other model you choose, to determine which channels are the most effective in driving your conversions. Then, this information can be used to optimize your campaigns and improve overall performance.
Now that you’ve seen what it can do, don’t be intimidated by the seemingly complex features of the Attribution Panel. Face it. Embrace it. Understand it. Most of all, use it to your advantage. The Attribution Panel and Lookback Window are the keys to unlocking a deeper understanding of your customers and their journey with your brand.
Now, we can travel “back in time” with confidence and use the power of our trusty time machine (aka, Adobe Analytics) to make data-driven decisions; and, most importantly, remember, “Where we’re going, we don’t need roads!” (Just a flux capacitor, and a keen eye for attribution!)
This document was written by:
Jeff Bloomer, Manager, Digital Analytics at Kroger Personal Finance
Adobe Analytics Champion