Pages in FullStory

What is a Page anyway?

In a traditional sense, a “website” is equivalent to a domain (like foo.com), and a “page” within that site is equivalent to a single specific URL (like foo.com/about). For many content-centric landing pages, or basic websites, this definition makes a lot of sense!

But today, most modern websites and web applications do a lot more than just serve static content pages at static locations. Their URLS are more sophisticated, often dynamic, and generally contain data in them.

For example:

https://www.ecommerce-co.com/p/special-toaster-over-GHJAVFM/GR12330-1A 

is really an instance of a “Product Detail Page”

https://www.ecommerce-co.com/p/*/* 

When analyzing interactions with your Product Detail Page, you generally want to look across all Product Detail Pages. You also don’t want to mix in interactions from different pages like the “Product Search Page,” or your main marketing website.

To scope your page-centered analysis to the right level of granularity, FullStory uses machine learning to identify general URL patterns across similar page structures, without requiring any instrumentation on your part, and uses them by default across the platform.

When you see Page analytics in FullStory, like in Click Maps, Scroll Maps and Segment cards, these are based on “logical pages” like aggregate Product Details Pages rather than concrete URLs which could contain a massive amount of variation. In this example, if a particular Product Detail Page gets enough traffic on its own, it’s possible FullStory will separate that one into its own logical page.

Because FullStory is constantly learning about your site’s URL and page structure patterns, logical pages will evolve over time and may cause data fluctuations for a given Page. The data you see is always using our best fit clustering at the present time, based on historical trends.

Example of Combining Multiple URLs into a Logical Page

Imagine you are shopping for blenders on ecommerce-co.com. You could see two different URLs for blenders with different words on the page, but this page is the same Product Details Page.

FullStory is able to use machine learning to know that counts should be combined across certain sessions by matching their UI structure, even if their content is different.

The fact that multiple URLs had the same UI structure allows us to interpret what parts of the URL are variable. Using that intuition, we can turn this:

https://ecommerce-co.com/p/special-blender-GHJAVMY/GR156560-2A

https://ecommerce-co.com/p/other-blender-GHsdfVME/GR123301-1B

https://ecommerce-co.com/p/special-toaster-oven-BLEAVFM/BL133630-8Q

into this (ie. The “Product Details” Logical Page): 

https://ecommerce-co.com/p/*/*

 

Analyzing Specific URLs

But what if you want to know specifically how many people clicked on things related to your concrete URL

/p/special-toaster-over-GHJAVFM/GR12330-1A

All Page Insights results respect the current segment. So adding a Visited URL Segment search for PATH is p/special-toaster-over-GHJAVFM/GR12330-1A will constrain your results to only users who hit that URL.

Screen_Shot_2020-07-27_at_4.14.42_PM.png

Keep in mind, if those users also hit other Product Detail Pages in the Page cluster, data from those page views will still be included.

 

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