What’s advanced e-commerce in Google Analytics

As we have mentioned in other posts about Analytics, Google Analytics is an advanced tool for tracking the user within a web. 

To do this, Analytics offers diverse features we can carry out installing a tracking code, generating events, modifying some settings, or creating new segmented-traffic channels. 

Among all the features it has, the ability to track e-commerce stands out.  We can enable an option to enhance this functionality in the Analytics control panel: it’s called Advanced E-commerce Tracking. 

Unlike the e-commerce tracking feature Google Analytics uses as default, this setting enlarges the products tracking information, offering new variables and much more information. 

In today’s post, we’ll review the data we can extract from the Advanced E-Commerce feature in Analytics and how we can use it to reach conclusions.  We’ll not show its implementation since the purpose of this article is to show its potential and provide a basic understanding of it.

This can be found in the Conversions section, where you read “e-commerce”.  In this section you will find:

• Overview: A generic graph of the sales. 
• Shopping behavior: Here we can see a funnel of all sessions that have entered the web, and where they abandoned, as well as those who bought.  In addition to that, it’ll identify new and recurring users.

• Behavior in purchase processing: It’s a funnel, but only about the checkout of the web.  This will help us identify if there’s a step in the checkout where people have problems and analyze why that is. 
• Product Performance: Information on products that have been sold, those who have been returned and the amount. 
• Sales performance: Orders made, returns, orders’ revenue and the products within these orders. 
• Product list performance: Here we can deeply analyze the searches made within the web.  And within these searches:

1. Products that have been printed
2.  The clicks percentage
3.  The clicks
4.  How many times the product was added to the cart
5.  The number of times the payment process started
6.  How often payment was completed 

This information will be useful to identify the best products for the user since it isn’t always the best-selling one. 

• Marketing: An assembly of sub-sections in which we find sections aimed at analyzing marketing strategies: 

1. Internal promotion: Featured items on the web that are analyzed for their effectiveness
2.  Order Coupon: Coupons used to make an order
3.  Product Coupon: Product coupons used
4.  Affiliate Code: Allows to analyze the affiliated members who have contributed to the purchase of products on your website

Within the advanced e-commerce tracking in Google Analytics, aside from all these sections, there are several secondary dimensions we can choose from if we derive information using code.

Some of the more important or useful dimensions are the following:

• Brand: Product brand (although if you don’t want to show the brand, we can use an ID brand to cross it with our database later).
• Category: Product category (if it belongs to any type of product like t-shirts, towels, hats, etc.). Categories can have a maximum of 4 sub-levels (Cat1/cat2/cat3/cat4).
• Variant: Product variant (this includes sizes, colors or other variants)
• Position: The position the product was printed, into a list of products.

There are several ways to use this information to our advantage. Probably, many of these options are clear, but for others, we need time and dedication, so we recommend some points to keep in mind.

If we see that there’s a very high drop-out percentage of users in a specific funnel, it’s recommended to insert  events  at that stage to analyze what may be happening and correct the problem.  

Many times, if we know the web, it’s more difficult for us to notice the defects. But a user that doesn’t know it is more likely to find errors or defects in the functionality.

Inside Analytics, we can extract the products with more impressions, and compare them with the average position, clicks, CTR, and sales.

With this information, we’ll possibly discover that the product which occupies the first position is not the best-selling one, or that the product the users check the most has the largest dropout percentage.

This information, analyzed and used to improve your site, can easily boost sales.

At the end, it’s data that gives us indications of what the user is looking for, where he gets it and where he don’t.

Within the Analytics settings, we can find an option to import data, where we can import product returns or sales from other not web-based platforms.

This can be useful to identify the channels in which more returns occur or to compare the sales of your website with the sales of other platforms.

The only problem is that the imported data can’t be synchronized with the dates, the data appears from the date it was imported. This means that if a sale occurs in a certain week and the return occurs the next week, to see the return, you must select both weeks.

The Advanced e-commerce in Analytics is a powerful tool that will allow us to obtain more information about our business and how it’s working.

For the code implementation, you can find more information at  Google Developers, although it is convenient to have a person or agency with prior experience to plan a successful web analytics strategy.