Creating value buckets in Data Views for analysis

Transcript

Hey everybody. It’s Doug. In this video, I want to show you a really cool feature available to you in Customer Journey Analytics when you are configuring your components in a data view. This feature is not available in Adobe Analytics but is available here in Customer Journey Analytics. The feature is Value Bucketing and I want to show you how to set it up. Now, you see here that I have product price selected as this component, this metric selected. And this metric is obviously the product price, right? The price of the product that somebody is purchasing. Now, that’s great and that’s a metric, but one of the things we can do is we can turn any metric into a dimension so that it can be on a row in our table and you can apply other metrics to it. And let me show you what I mean. If we take product price and we duplicate it and it goes up here to the top and I’m going to select that one and now I’m going to name it. And instead of product price I’m actually going to change this a little bit and call it product price groups.

And maybe I’ll just do this.

Okay, product price groups. Now I’m going to change this from a metric to a dimension.

And so, it comes down here in the dimensions list and it becomes a dimension for your reports. So, you can drag it into a row and then apply columns of metrics to it. For example, you know, how many visits or visitors made a purchase of this amount, but if it was just the price, that could be any price, right? It could be so many different prices which would result in so many different rows. So, when you actually have a numeric dimension, right? Basically a metric that you have moved into the dimensions area here on the right-hand side you can scroll down and now we have this section called Value Bucketing. And so let me grab that again. And so, we can say bucket the values and you can start creating these buckets. Now you can see by default, it gave me three buckets less than five, five to nine really, less than 10, five to less than 10 and then 10 and up. So, depending on my product prices let’s say that my prices are a little bit spendier than that, I can always just go over here maybe I can even get rid of that middle one. And now you can just have, you know less than five or five and more if you want but let’s say that I just want some $50 increments. So, I’m just going to go less than 50. And I’m going to say, add a bucket and I’m going to say 50 to a hundred and I’m going to add a bucket. I’m going to go a hundred to one 50. And as you can see I could keep going, but really no need, obviously, right? So you can see here that I would actually just have four possible values in the rows if I brought this into a table, I’d have a less than 50 row, I’d have a 50 to a hundred, a hundred to 150 and a greater than or equal to 150. So, I’d have each of those on a row in my table. So, I could see how many orders were in each of those buckets. I could see how many people have purchased in those buckets. I can add anything there. Maybe we could even break it down by geo you know, so great things here. This is a really cool feature and available to you here in Customer Journey Analytics, can be helpful for much more than just revenue prices and stuff like that. But anytime you want to have a numeric dimension and have a group together you can use these value buckets. Good luck. - -