| schedule 6 minute read | label Product Information Management

Is it time for more specialised analytics tools?

new york city

Let's give it up for our CEO, Morten Hellesøe Poulsen, who shares his insights and musings on the future of e-commerce analytics tools and product-based analytics. Time has come to get the analytics tools up to speed with the complex reality we live shop in!

There’s a big difference between running a travel blog and running an e-commerce business. The online space has matured to such degree that it’s difficult to believe a one-size fits all analytics tool can cover all the different needs out there. These days, the data and tools used for a blog and for a web shop need, of course, to be tailored to each type of site.

Tweet this: These days, it's crucial that the data and tools used for e.g. a blog and a web shop are tailored to each type of site.

In this post, I'll touch upon some of the things I found missing in the web analytics tools I’ve tested for e-commerce over the years, including my time working as a Product Specialist, and explain why we have decided to create yet another web analytics tool in Plytix; one that is optimized and tailored for e-commerce.

I'm aware that many of the things I refer to in this blog can be achieved through workarounds and many of you reading this blog will know how to do so. The underlying question is, however, whether we can justify spending time on these workarounds rather than adding a complementary analytics platform to our existing toolbox?

Web analytics tools are built for site optimization

Before we get started, let me clarify that I love Google Analytics. I think it’s a fantastic tool, and I use it daily. If you could see my accumulated Time on site across all devices for the last 6 years, I would say that GA is the number one - with Facebook as a close runner-up (I am not gonna lie).

But let’s face it, Google Analytics was built for the purpose of measuring activities on your site and it will probably give you the best data for optimizing your website. Google Analytics also offers an E-commerce section with the purpose of measuring the performance of your web shop, but unless you pair it with data from your CMS analytics dashboard and other sources and then crunch some serious numbers in Tableu or Excel, it doesn’t really give you much to go with. Let’s look at a few examples.

Product-based Analytics

With the release of Google Analytics enhanced e-commerce tracking, even Google has underlined the importance of tracking at product level. I’ll explain in the following why product level tracking is crucial to your business.

Let’s say that you go to your e-commerce section in Google Analytics and look at your product overview. You notice that Product A had 7 conversions in the last 10 days. What would then be the next relevant thing to look at? Personally, I’d like to see those conversions for product A in relation to the number of times the product was viewed on a product page or even a listing page. On top of that, it would be interesting to see how many times product A was added to the cart and maybe removed from the cart. Without this data, I have no real indication of how my products are performing.

So, without an analytics tool to give us data that revolves around products. e-commerce tracking is as good as worthless. This is where Google Analytics Enhanced E-commerce tracking comes in.

Is enhanced e-commerce tracking really necessary?

If you run an e-commerce business, then yes! You need a way to investigate the user’s path to conversion and for that, you need data that revolve around your products. And the fact of the matter is that the data presented in Google Analytics isn’t sufficient. Why do I think product-based analytics is so important? Well, it started when I began asking questions like a PMM (Product Marketing Manager)...

I’ll share some of those questions with you here:

How many times has my product been viewed on a Category Page?

This is one of the things I believe Google Analytics lacks big time. This metric is super important in order to for me to understand how my products perform.

Let’s take the example of two products with the following stats shown in Table 1.

Table 1

Product A

Product B

Product page views






Product page/conversion rate



In the standard Google Analytics interface, I can see how many times an individual product has been viewed on a product page - if the URL structure of my website is correctly set up - and I can see how many times the product has converted. With this data, I am forced to think that product B is a more interesting product, but the truth is that I don’t actually know for sure.

See, it’s very difficult to know how much real estate each product has on a product category overview page. It could be that Product A is featured on page 1 or 2 on the category overview. Furthermore, to know how many times each product has been viewed, I would have to know all the different category pages by heart, know in which ones product A and product B appears, and then add the session numbers for each of them.

It could easily be that product B is featured in more category overview pages than product A and therefore has more real estate. Making a head-to-head comparison of the two products unfair.

Instead, imagine an analytics platform where the data revolve around the product. That would mean that we could have this data set:

Table 2

Product A

Product B

Category view



Product page views



Product view/category view






Conversion rate/product page



Now I can assume that if Product A were featured as frequently on a product category page as Product B, we would be able to sell more.

Compare analytics tools


How many times has my product been added to the basket?

Another thing I have often felt was missing is an understanding of how many times my products are added to a basket and, even more importantly, how many times they are removed from the basket. What I see in most analytics tools (unless I do some heavy tagging and custom reports and filters) is product page views, check-out page views and then conversions.

That’s all fine, but…:

  1. I can't see all products that have been added to a cart directly from the Category page
  2. In a funnel visualization I only see the last product page before check-out, but don’t know if that product was added to the cart or not
  3. When entering the checkout page, I can’t see which products are there and if any products are removed before checkout
  4. If a conversion occurs after a product page has been viewed, I don’t know if that specific product was added, and then removed, from the cart or never added at all.
  5. Etc...

As you can see, it’s difficult to assign a value to the products. Let’s say that a user has viewed 10 products and then reaches the checkout page. Do we know which products have made it to the basket? Again, it is doable, but it requires some heavy lifting on your part to get that data from your analytics tool.

This was just a few examples of the questions I find it hard to get answered in the standard analytics tools.

Setting up Google Enhanced E-commerce tracking

Let’s have a look at what we need to do in order to set up Google Analytics Enhanced E-commerce tracking. In Plytix, we have run some tests and set up Enhanced E-commerce tracking on several accounts in order to compare it with our own analytics platform. The first thing that becomes obvious is that setting up Google enhanced E-commerce tracking is a time consuming process. First of all, Google Analytics doesn’t store a database of all your products, so you have to send all attributes such as SKU, name, price, and so on. And you have to do that for every single event (product listing, product page, add to cart etc). Let’s have a look at the required installation.

Example of Google Analytics Enhanced E-commerce tracking setup:

ga('ec:addProduct', {
'id': pr['id'],
'name': pr['name'],
'category': pr['category'],
'price': pr['price'],
'quantity': amount
ga('ec:setAction', 'add');
ga('send', 'event', 'UX', 'click', 'add to cart');

Compared with the same integration with Plytix:

_pl('track', pid, 'addtocart', amount);

As you can see, with Google Analytics you have to send all attributes with every single event, which means that you are sending a lot of redundant data.

With Plytix, all the product details are already stored in a database, so it simply requires a unique product identifier. Thereby we’ve saved ourselves a lot of time in the integration, as well as the hassle of sending redundant data every time an event occurs.

Remember that Google Analytics Enhanced E-commerce tracking is not part of the standard Google Analytics integrations, so you can’t just install Google Analytics on your webshop and expect product level data. Only few plugins are available, and they’re often expensive. With Plytix, integration is extremely smooth. So far, Plytix has released plugins for Magento, Prestashop, WooCommerce, and Shopify, and we will hatch the next batch of plugins early next year. If your webshop operates one of the above systems, than integrating with Plytix is as easy as installing... well, a plugin on your website.

Should I use Plytix and Google Analytics, or can I make do with Google Analytics?

You always need tools like Google Analytics to measure the performance of your site and apply those insights to improve user experience, but if you run a webshop you need to have product related data as well.

With Google Analytics Enhanced E-commerce tracking you have the benefit of having all your analytics data gathered in one dashboard, but you will lose out on some crucial features and data sets that only Plytix can provide.

With Plytix you have an analytics tool that is more user-friendly. For instance, you get the option of grouping products, which is relevant in order to compare for instance the spring collection with the fall collection, or your blue shirts with you black shirts. On top of that, Plytix comes with an easier integration process and gives you access to a free CDN and database where you can get all your packshots for free in high resolution.

And as the icing on the cake: if you’re a brand, you get to see how your products perform across all the third-party sites where they’re sold. 


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