Share on facebook
Share on twitter
Share on linkedin
Share on email

Reporting Differences and Common Discrepancies Between ‘Revenue’ and ‘Product Revenue’

Reporting Differences & Common Discrepancies Between Revenue and Product Revenue

Have you ever noticed that the Google Analytics data model includes two metrics for reporting on revenue collection: revenue and product revenue? And not only is it confusing that there are two different metrics essentially reporting the same thing—they’re often not in alignment.

What gives? Allow me to explain the nuanced differences between these two metrics and why it is actually important that the data model includes both.

Scoping Differences

The first thing to know is that both of these metrics are intended to report on revenue at different scopes of reporting. In an eCommerce context, there are typically two different levels of reporting—order-level and product-level. The order-level represents a single purchase event, and the product-level represents all the items included in the purchase (of which there can be several). Another way to think about it is that order-level revenue is the total amount collected from the entire shopping “cart,” whereas the product-level revenue is the amount collected from each individual item in the shopping cart. Because of this one-to-many relationship between a single order and the multiple products in that order, the Google Analytics data model leverages two different metrics to report on revenue at each of the levels.

  • Revenue: The aggregated metric for the entire purchase. This used for reporting revenue at the session and user levels and is the metric most commonly used reporting across the various Google Analytics reports.
  • Product Revenue: The metric representing individual product contributions to total revenue. This is used for reporting exclusively at the product level and is generally only included in the product-based eCommerce reports in Google Analytics. 

Implementation Differences

Not only is there a difference in scoping, there is also a difference in how the data is collected and processed in Google Analytics. The order-level “Revenue” metric is the summation of the cart total that passed in the purchase event as a single value (i.e. sum[cart total]).  The product-level “Product Revenue” metric, on the other hand, is the sumproduct of the unit price and quantity for each product in the order (i.e.  sum[price X quantity]). Because there are more inputs used in the calculation, this requires additional backend processing in Google Analytics to derive the metric from what gets passed in the purchase event

Below is an example of a purchase event showing how each metric would be reported in Google Analytics based on the values passing in implementation:

Common Causes of Reporting Differences

Because of these aforementioned scoping and implementation differences, it is not uncommon for there to be (sometimes significant) differences in the values reported for revenue at the different levels. Here are the most common reasons that help explain those differences:

  1. Order-level “Revenue” includes additional values for tax and shipping amounts that are not easily applicable to each item at the product-level “Product Revenue.”  This will result in the order-level “Revenue” reporting higher than “Product Revenue,” which would not be accounting for those additional amounts added to the order.
  2. Coupons are applied to the order-level without discounting the individual product prices. This will result in the discounted order-level “Revenue” reporting lower than “Product Revenue,” which would still be calculated based on the full-price items.

Questions about Your Revenue Reporting?

Now that you understand the scoping and implementation differences between these two similar metrics, it is important to remember that they both exist in the data model to serve different purposes. “Revenue” serves as your baseline revenue metric that you will use to understand your overall revenue collection from your site in the majority of your reporting. “Product Revenue,” however, is more specifically used to understand how much revenue each of the individual products on your site is contributing and can be particularly useful in a merchandising context to know what your top-selling and/or underperforming products are.

Hopefully you now have a good grasp of what differentiates these two revenue metrics in the Google Analytics data model. Certainly contact our team today if you have any questions specific to your eCommerce revenue reporting.

Interested in Knowing More About Revenue And Product Revenue?

Reach out to the experienced team at InfoTrust today.
Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn
Share on email
Email

Other Articles You Will Enjoy

What Advertisers Need to Know about Server-Side Analytics and Tagging

What Advertisers Need to Know about Server-Side Analytics and Tagging

Server-side tagging is the process of moving tags and third-party scripts off of your company’s website and onto a server that your organization owns…

Customer Profiling Using Google Analytics Data – An RFM Approach

Customer Profiling Using Google Analytics Data – An RFM Approach

As an analyst at InfoTrust, a partner once asked for help building customer profiles using data from Google Analytics. They needed help with defining…

6 Considerations for Server-Side Tagging in Google Tag Manager

6 Considerations for Server-Side Tagging in Google Tag Manager

One of the hardest things about diving into a new technology is that you don’t know what you don’t know. Here at InfoTrust, we…

3 Ways Enterprises Use Google Cloud for Marketing in 2021

3 Ways Enterprises Use Google Cloud for Marketing in 2021

As a data scientist with InfoTrust, my team and I have the opportunity to work with marketers from some of the largest organizations in…

Why Executive Teams are Resisting Google Analytics 4 (and What You Can Do to Change Their Minds)

Why Executive Teams are Resisting Google Analytics 4 (and What You Can Do to Change Their Minds)

Few can dispute that the future of analytics will be driven by machine learning and artificial intelligence. With Google’s launch of Google Analytics 4…

What is a Data Clean Room?

What is a Data Clean Room?

“Data clean room” is a growing buzzword in marketing, analytics, and advertising industries. Although data clean rooms aren’t an entirely new concept, they haven’t…

4 Advantages of Server-Side Tagging in Google Tag Manager

4 Advantages of Server-Side Tagging in Google Tag Manager

Server-side tagging is a hot topic these days in the analytics world. For the uninitiated, server-side tagging allows users to move measurement tag instrumentation…

3 Reasons Why Analytics Teams Run Adobe Analytics & Google Analytics Side-By-Side

3 Reasons Why Analytics Teams Run Adobe Analytics & Google Analytics Side-By-Side

Making the most of clients/prospects’ data is the driving force of the conversations we have on the Infotrust partnerships team. When I sit down…

Will I Lose Data Moving from Universal Analytics to Google Analytics 4?

Will I Lose Data Moving from Universal Analytics to Google Analytics 4?

As web analysts begin preparing for the fourth generation of Google Analytics, aptly named “Google Analytics 4,” a few common questions have cropped up…

Talk To Us

Talk To Us

Receive Book Updates

Fill out this form to receive email announcements about Crawl, Walk, Run: Advancing Analytics Maturity with Google Marketing Platform. This includes pre-sale dates, official publishing dates, and more.

Our website uses cookies and may collect user information to provide a good experience. Read our Privacy Policy here.

Leave Us A Review

Leave a review and let us know how we’re doing. Only actual clients, please.