How to Use Filters In Google Analytics to Analyze Ecommerce Sites
When analyzing data on a site that has thousands of pages, it is often useful to group data by page type and measure the performance of those page types. As an example, let’s say that you have an ecommerce site. A typical ecommerce site will have:
- a home page
- landing pages
- regular content pages (you could segment these further – create logical groupings)
- category pages
- product pages
- a cart page
- a checkout page(s)
- and a receipt/confirmation page.
If you have thousands of product skus, analysis on the performance of all of your product pages (in aggregate) is sometimes not easily accomplished. We will discuss two ways to easily accomplish this.
Option 1: Content Filter Approach
If you have a URL structure such as www.yourwebsite.com/products/product-name.aspx, you can apply a filter to your top content report (or landing page report) to look at all pages that begin with /products/.
The green-highlighted area above contains the aggregate data on product page performance. You can also use a regular expression to filter your pages to look at a specific URL structure.
Option 2: Profile Filter Approach
If your URL structure is a bit more complicated but does have a distinct pattern to indicate whether it is a category or product page, then Google Analytics profile filters are a great option. Note that you should create a new profile and add these filters to that new profile.
WARNING: Do NOT add these filters to your current profile, as it will manipulate all data going forward. This technique is also great if you prefer not to go in and apply filters each time you want to look at this data.
Let’s say that you have the following URL structure for your category pages and product pages:
- Category Pages: www.yourwebsite.com/shop/<category-name>
- Product Pages: www.yourwebsite.com/shop/<category-name>/<product-name>
This is a bit more complicated to filter for in your Top Content report right? If you just put in a content filter of /shop/ it is going to match both category and product names.
This is where the power of a Google Analytics profile filter becomes useful. Profile filters are filters that are applied before the data enters the report database on the Google Analytics servers.
Given the URL structure above, you’ll want to add two ‘Search and Replace’ filters — one for products and one for categories. The order of these filters is also important because if you have the category filter first, then product pages may be rewritten.
Product Page Rename
Category Page Rename
As mentioned previously, the filter order is important, so after you add these, be sure to assign the filter order to ensure that the product search and replace filter comes before the category search and replace filter.
So, what are these Google Analytics filters doing?
It is fairly simple. If a pageview is tracked as /shop/<anything>/<anything>, then the product filter is going to rewrite that and make it come into the reports as /product-detail. This will always be the case and as a result, all product pages will show up as an aggregated entry of /product-detail. Then, if a pageview is tracked as /shop/<anything>, it will be rewritten as /category and populate the content reports as such.
In this example, you’ll be able to quickly go into this new profile and look at the category and product pages in aggregate. You’ll easily be able to look at the landing pages report or create a custom report in Google Analytics that leverages this page-type grouping.
Compare Page Types Side-by-Side
The biggest advantage of the profile filter approach over the content filter approach is that you can easily compare the page types side-by-side and throughout content reports. The new profile switching feature in Google Analytics version 5 remembers what report you are looking at, which makes it easier to switch between profiles when performing analysis.