Analyzing Customer Shopping Behavior in Advanced Analysis

Estimated Reading Time: 2 minutes

Last year, Google released their Advanced Analysis reporting interface for 360 customers. While the product is still in beta and continuing to be refined, I’ve found it really elevates Enhanced Ecommerce reporting—largely because the GA reporting interface wasn’t really designed for digging deep into reporting or combining reports with all that much ease. It’s not to say you can’t learn plenty about your customers with the EE reports in GA, but, if you want to dig deep and quickly, Advanced Analysis is where you’ll want to start spending your time.

Shopping Behavior Report

One of my favorite reports is the shopping behavior report. Why? Because it provides a simple, high-level view into how customers shop your website—that, anyone can pick-up on. This single report illuminates the opportunities for improving your ecommerce experience. Specifically, it will show you if you are doing any better at growing customers interest in your products, or perhaps, most importantly, their interest in checking out. 

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Product List Report

Next, the product list report is where you’ll find, on a last touch basis, the places where customers are finding your products, for instance, in search results. 

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That being said, these two reports don’t exist in the same place within GA, not even in a custom report.

Let’s say you wanted to take it a step further and drop in a device report to compare against Desktop and Mobile, well, in short good luck!

Thankfully, with a little bit of work, Advanced Analysis puts all of this at your fingertips in just about any way you’d like to see it. So, let’s head on over! 

Funnel Analysis

First, we’ll start out with a funnel analysis, then we’ll clear out the junk in the out of the box report.

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This is exactly where we want to begin.

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Next, we’ll recreate our funnel steps with a little-known dimension called shopping stage. Shopping stage is the dimension that powers some of your fancy EE reporting, but it can be used anywhere and is my secret weapon in funnel reporting.

Here is what the dimension looks like in a custom report (gross, I know)—we’ll need the stage names to create our funnel though.

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Shopping Stage Report in Advanced Analytics

Using the shopping stage names, I’ve created steps within AA to match the funnel report in GA.
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And now our shopping stage report is reborn in Advanced Analysis.  Looks familiar, right?

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Shopping Stages Report + Product List

Going back to my original example of combining the shopping stages report with the product list is a breeze, I just add it as a breakdown.
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So, what can we learn from this report? Well, first off, where customers are finding our products in the most frequency is in Category lists, so, if I were to begin optimizing my site, this seems like a great place to start
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Our user add-to-cart rate isn’t terrible in comparison to other product lists, but, given the scale, I’d still like to see if I can’t improve this performance.
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Product Category Dimension

For my next trick, I’ve limited the Shopping Funnel performance to just the ‘Category’ list using a filter.
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I then drop in my product category dimension, and I can see which group of products are driving or drawing from my add-to-cart rate. Basically, everything is looking good, except for the dang ‘Home’ category, so it’s going to be my next filter.

I could go to a couple of places next; either 1) dig deeper on the product side or 2) start looking at my marketing channels.

But, because advanced analysis is so easy, I’m going to do both… at once!

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From here, we have a couple of business questions to look into to close out this analysis:

1) How is pricing in the well-performing categories compared to non?

2) Have we had any recent promotions that could be impacting performance?

3) Do we just have a couple of products bringing down the category?

Web Analytics Wednesday on 2/13 in Chicago

This is just one example of the power available to you in Advanced Analysis but there’s plenty more. If you happen to be in the Chicago area and are interested in learning more or sharing your experience with other folks in the industry, please join me for InfoTrust’s Web Analytics Wednesday on 2/13 in the Merchandise Mart.

 

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Originally Published: February 5, 2019

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September 28, 2023
Originally published on February 5, 2019

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