Traffic management based on product performance with Google Analytics

The goal of the article is to provide the tools needed to determine which traffic acquisition channel is responsible for selling a specific product or set of products. We will do this in 2 parts. The first one deals with the direct tie between the product and the acquisition channel – please note we will be working in the realm of last non direct attribution model so it is all about the last known source. The second part deals with the situation where the product is hard to sell directly so we need to resort to more devious sales methods in specific using related products – in simple terms sell more product X by selling more product Y.

Part 1 – tie between the traffic acquisition channel and the product

Note that the following tool does not, by default, say which channel is the most effective – cost effective yet gives the information on sales volume related to source.

A prerequisite is of course a working GA property and ecommerce tracking implemented.

Believe it or not this report is available in standard reports though a bit hidden. Go to Conversions > Ecommerce > Product performance report.


Choose Pivot table for report display type.



Proceed to dimension and metric selection process:


  • Primary dimension can report on Product name, category and sku
  • Pivot by offers a selection of dimensions which you need to make sense of – depends of the questions you have:
    • choose a time based dimension if you need an answer when to sell
    • choose campaign if you want to see which campaign sold which product
    • choose basic default channel grouping (works only with standard ecommerce and not with enhanced ecommerce) or source / medium if you need a high level understanding what drives sales for a particular product (as in the current example)
  • Metrics are limited to product related scope

The table can be further filtered as appropriate – e.g. only products which generated > 10.000 product revenue.

Once the report is set you can use the Shortcut feature which will save most of the report settings and probably save you time on further reporting efforts.


Are there other ways to do this? Of course yet this is the easiest one for ad hoc analysis. Based on the report you can redefine your traffic management based on sales requirements – it gives a simple answer which channels you invested before which generated product X sales volume – this gives you the opportunity to test how a specific channel scales and can it give more.

Part 2 – Related products – Sell more X by selling more Y

So our product X is really hard to sell by itself. All our direct traffic acquisition efforts have failed (long tail campaigns) yet the product seems to sell but from completely unrelated campaigns. A solution may be that the product is more sell friendly by pushing campaigns for related products where users buy it as an additional product. So how to obtain this valuable piece of information?

Option 1 – Custom segment

Build a custom segment (the segment is user scoped) which will in return report the following – report on all products which have been bought in transactions, in defined time range, where Call of Duty: Black Ops III (our product X which causes problems) was in at least one of the transactions.


Option 2 – Related products – ecommerce feature

This is an ideal way to automate the data pull and gain some insights into correlation between products inside a transaction. It is usually used when you do not have access to a more advanced CRM / ERP which does these things – is built for these things.

Prerequisites include a working GA property, ecommerce tracking implemented and the feature enabled inside the GA view ecommerce settings.


Once turned on it allows us to fetch additional dimensions and metrics using Google Analytics Core API – more info on the subject:

For testing purposes you can use this nice addition to Google tool set – Query Explorer where you can fetch the data on the fly – basically test your query prior to any automation attempt.


After the basic setup is done you may do more tinkering in terms of filters applied – only specific product Ids or only results where the correlation score metrics is >0.8.

The end result is a table which displays the queried product Id, related product Id and the correlation score (values can be 0-1 – where values closer to 1 is what we are after – high level of correlation between the products).


This kind of report can then easily be replicated in Google Sheets using the Google Analytics extension which also allows filtering flexibility and scheduling / automation.



When you find products with high correlation score to your product X revert to part 1 of the article and see which channel is responsible for sales and test the scalability to improve both product X and product Y sales. 


Author bio

Zorin Radovančević

December 30, 2015 Google Analytics

Senior Web Analytics implementation and planning specialist - all things related to Google Analytics, Google Tag Manager and Yandex Metrica.


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