Destination Page Analysis: Understanding How Visitors Browse Your Site

When you perform website analysis, you need to look at several different areas to understand how your site is performing and how it can be optimized. Three common areas of web analysis that apply to any website regardless of its industry are as follows:

  • Entry: How effective your landing pages are
  • Search: What your visitors are searching for
  • Exit: Where your visitors are exiting your site

A lot of emphasis has been placed on analyzing entrance or landing pages. You want to optimize your key landing pages so that visitors are moving beyond these entrance pages and deeper into your site content or conversion process. In most cases, conversions don’t occur on a landing page so the bounce rate metric (% of single-page visits) has grown in popularity as an indicator of whether people are moving beyond the first page they see.

Another key area of focus for web analysis has been internal search. You want to understand what your visitors are searching for so that you can deliver what they are seeking. When visitors are browsing your site, you don’t necessarily know what they are looking for, but in the case of internal search, they’re more or less telling you what they want by the keywords they use. Through the internal search reports, you can identify ways to make existing content or products easier to find, identify new content and product offerings to add to your site, and understand shifts in the interests of your visitors that can then influence which content or products ends up being promoted in your onsite and external campaigns.

To a lesser degree, web analysis might be focused on key exit pages. I still find it funny how some people view site exits as negatives. Eventually, all visits will come to an end (yes, even those to your wonderful website). Site exits are mainly concerning when they occur at a key stage in your conversion process, and visitors are prematurely ending their journeys before converting. Using an exit rate metric (% of site exits on a particular page), you can identify unexpected exit pages to evaluate and fix.

What about browsing behaviors?

If entry and exit analyses focus on the bookends of your visitors’ journeys, what about what happens between those two points? Internal search analysis provides some valuable insights into your visitors’ behaviors in the middle, but it’s only part of the picture. Some visitors are more likely to search while others have a tendency to first browse or navigate before searching. So how do you analyze browsing behaviors on your site?  Do you really know where visitors are going on your site?

You could do usability testing to explore these questions but that can be expensive and time-consuming. In addition, you’re only going to see a small sample of the customer journeys. If you stick with your web analytics tool, you could pull a Pages report to see which pages are most popular by page views or visits. However, this report would obscure where your visitors are actually going because it includes their starting point—the landing page that they found from an external link or keyword search. In order to identify which destination pages your visitors are gravitating towards during their session or visit, you need to use a different approach called Destination Page Analysis.

Destination Page Analysis

This analysis technique is no more complicated than analyzing landing pages by bounce rate or other pages by exit rate. It comes down to a couple of simple calculations. If you’re using Adobe SiteCatalyst, you can create these metrics as calculated metrics in your reports. If you’re using another tool such as Google Analytics, you can perform the calculations in an Excel spreadsheet.

In order to remove the entry-based visits from the Pages report, you’ll want to create a destination visits metric by subtracting entries (or entrances) from visits. You’ll also want to create a secondary metric of destination visit % (destination visits divided by visits). The destination visits metric tells you how many times the page was visited when it wasn’t the landing or entry page, which means the visitors sought out the page after arriving on your site. The destination visit % metric informs you of how often the page was found after landing on the site as opposed to being an entry page. A low % for a particular page means visitors are mainly using that page as an entry point; whereas, a high % means the page is being found once they’re already on the site.

Landing pages can be destination pages as well. The Destination Visit % metric will indicate how often they’re being visited during a session as opposed to being the start of a session.

If everyone found exactly what they wanted on their landing page, there would be no destination pages. (You’d also have no destination pages if your landing pages were complete garbage, but let’s not go there). The simple fact that you have destination pages means your visitors are seeking more content or trying to complete some task. Therefore, understanding where they’re going is important if you want to help them achieve their objectives and create a better user experience.

How to use destination page analysis

One of the main applications of this type of analysis is to evaluate your global navigation and main browsing behaviors. While you can’t necessarily discern which destination visits were a result of a search or part of a navigation path, you’ll find the main pages associated with your menu structure should stand out in your reports. You will want to compare the different sections or categories listed in your global navigation with the pages that appear in your destination visit report.

You might find certain parts of your global navigation are not being used by visitors (e.g., you have a link to your education section but no one goes to that category in comparison to other categories in your global nav). You might discover visitors are seeking out content that isn’t represented in your navigation menu (e.g., the boating loans page is a popular destination page but it isn’t listed as an option on the menu). These insights can help your UX design team to improve the user experience by aligning the navigation menu with the content your visitors want to find.

While path analysis can be helpful in specific scenarios (e.g., paths within a conversion process or paths from a specific page), it can’t help you with analyzing your global navigation or general browsing patterns because people can start browsing from any page within your site. Destination page analysis provides a high-level view of which content your visitors are drawn towards regardless of their starting point.

Use case: PowerPointNinja.com

When I perform a destination page analysis on my PowerPointNinja.com website, I find that my global left-hand navigation has plenty of room for improvement. As I compare the destination visits report to my main navigational categories, I find that several of them aren’t very popular (fonts, philosophy, etc.) as they don’t even crack the top 15 results in the table below.

The categories highlighted in red aren’t that popular, and I should look at optimizing my menu structure.

I could look at revising the labels, menu structure, or taxonomy to help visitors find content more easily. I always recommend testing changes to your navigation before deploying them unilaterally.

I don’t have sub-categories in my navigation, but they can be tricky to analyze if you do. It may not be fair to compare main categories with their sub-categories. However, if a sub-category is outperforming a main category, it begs the question of whether it should be pushed up in the information architecture of your site.

In a related analysis, I could filter the destination visits report for just articles to see which blog posts are most appealing to visitors once they’re on my site. I could then look to test cross-promoting those pages in more places across my website and look to create more articles on similar topics.

Limitations of destination page analysis

Just like any analysis technique, destination page analysis has its limitations. First, if you have multiple links to a particular category page besides your global navigation (sidebar, footer, etc.), destination page analysis can’t tell you which method was used to find the page (including search vs. browsing). You’d need to track each link separately to understand that level of granularity (I’m not a huge fan of link-level analysis, but that’s a topic for another blog post).

Second, just because a page generated a high number of destination visits doesn’t mean that page was the intended ending point. Your visitors may have arrived at a dead end in their intended journey. Using your reasoning skills, you can typically deduce what is occurring, but you can also place an online survey on a key destination page to verify your hypothesis.

Third, destination page analysis gives you no insights into the sequence or flow of the destination pages. However, once you’ve pinpointed a key destination page that you’d like to examine more closely, you can use path analysis to explore the upstream and downstream pages to and from that page.

Combining segmentation with destination page analysis

When you apply segments to destination page analysis, you can discover some interesting insights into what types of content or pages are being sought out by key visitor segments. For example, you could examine the unique destination pages for two segments: loyal customers and mobile visitors. For your loyal customers, you might end up streamlining the landing pages of your email retention campaigns so that these visitors can get to their desired destinations  more quickly. For your mobile visitors, you may factor destination insights into how you design and structure your mobile apps.

There might be other applications for this type of analysis that I haven’t thought of. Please share them if you come across any that could be helpful to other digital analysts. Good luck on analyzing and better understanding the visitor journeys on your site!

Summary

Destination Visits
Formula: Visits – Entrances
Interpretation: How many times the page was visited when it wasn’t the landing or entry page
Context: Visitors sought out the page after arriving somewhere else on the site
Insight: Identify the key destination pages/content that make up popular customer journeys
Response: Shorten the number of clicks it takes visitors to accomplish their site tasks

Destination Visit %
Formula: Destination Visits / Visits
Interpretation: How often the page was found after landing on the site as opposed to being an entry page
Insight: Low % for a particular page means visitors are mainly using that page as an entry point
Insight: High % means the page is being found after they are already on the site
Response: Remove ignored sections from global navigation and emphasize popular pages in the menu structure to maintain alignment with common browsing behaviors

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8 Responses to Destination Page Analysis: Understanding How Visitors Browse Your Site

  1. Gerard Rathenau says:

    Nice post Brent. I have a question:

    Can you segment how many visitors navigate from a category page to a product page with this method? Or only in aggregate figures?

    • bdykes says:

      Thanks Gerard. With this type of analysis, you really don’t get a perspective on what type of page they were on previously. Destination Page Analysis is going to indicate how many visitors found a particular page via browsing or navigation, but it doesn’t shed any light on whether the previous page was the homepage, another product page, or a category page.

      I don’t know what analytics product you’re using, but in Adobe SiteCatalyst you can designate a variable (s.prop) to track content types (home page, category page, subcategory page, product page, etc.). If you enable pathing for this variable, you would be able to see the pattern that you mention above.

  2. Gerard Rathenau says:

    Thanks for your explanation Brent. I use Google Analytics. Is s.prop the same as Visitor and goal flow in GA?

    • bdykes says:

      In SiteCatalyst, you have two main types of custom variables, s.props (used for measuring traffic-related activities) and eVars (used for measuring conversion-related activities). The s.prop variables can be used for path analysis if the pathing feature has been enabled for them (not on my default).

      You can track anything in the s.prop variables (content types, site sections, internal search terms, app interactions). They can be aggregations (e.g., multiple pages fall into each page type) or micro-interactions (e.g., tracking low-level app interactions such as button or link clicks). Using these reports for path analysis, you can see flow reports similar to what you have in Google Analytics. In this case, the “nodes” you’re familiar with in Google Analytics would form the different page types (home page, product page, category page, subcategory page, search results page, etc.), and you could see how visitors are interacting with the different page types. In SiteCatalyst, the page types are set programmatically during the implementation so you aren’t grouping them manually in the tool.

      I believe you’re right that the Goal Flow Report in GA is the closest thing to what I’ve described, where you can see node-to-node flows between category and product pages.

  3. sigaz21st says:

    Hi Brent – very nice article. I’m new to web analytics and the destination page analysis seems to allow you to take a step back from the complex details of path analysis to give broader idea of whats working on the site. A good place for a newbie like me to start. I am trying to sort the report set up in Google Analytics. My dimension is Page title and my entrances are equal to visits which is not useful. Do you or anyone out there know how to set up this report as displayed on this page in GA?? Your help would be som much appreciated. Thanks, sigaz21st

    • bdykes says:

      Sigaz21st, I don’t believe you can do this analysis natively in GA. You’ll need to export the page metrics (Pages by Entrances & Visits) to Excel so you can perform destination analysis. There are several GA plug-ins for Excel that you could use. Good luck!

      Brent.

  4. Reetesh Shah says:

    Hi Brent,

    Thank you for such a nice article. But, just for the sake of being sure I want to ask you a question. I use Google Analytics, so in this case when you say Destination Visits Formula = Visits – Entrances, here visits are unique pageviews or all pageviews?

    • bdykes says:

      In the case of GA, it would be unique pageviews, which is more or else the equivalent of visits in this context.

      Brent.

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