Using PadiTrack to Measure Site Navigation

PadiTrack is an easy to use, free tool that enables you to extend Google Analytics with more flexible goal funnels and other navigation path tracking.

PadiTrack offers several advantages over Google Analytics for setting up goal funnels:

1. Historical data – with Google Analytics, setting up a goal funnel means the data is reported starting the day the funnel is set up, so no historical data is available. With PadiTrack, you can set the date range as far back as your Google Analytics data goes.

2. Segmentation – advanced segments can’t be applied to funnels in Google Analytics, but PadiTrack provides the opportunity to apply segments, including custom advanced segments that you have set up in your Google Analytics profile! (Late-breaking: the *new* Google Analytics now in beta allows for segmentation of goal funnels – but it’s not fully rolled out yet.)

These strengths make PadiTrack a powerful tool for monitoring progress down the goal funnel, but also make it very useful for understanding navigation from one page to another.  This especially applies if you have a dynamic site and want to understand the movement of visitors from one page ‘type’ to another. For example, you may have ‘product category‘ pages with URLs like ‘‘ and ‘product detail‘ pages that have URLs like ‘‘. If you want to know frequently visitors go from category to product pages, you have several options:

  1. Simple calculation: If the only way a visitor can get to a product detail page is via a category page, the calculation is straightforward, based on unique pageviews of each type in the Content Report. But modern sites are rarely so strictly laid out, since we usually want prospects/customers to be able to get to product detail pages via search (off-site or on-site) or other convenient means.
  2. Set up a Google Analytics Goal Funnel either with with product detail pages as end goal, or as part of larger goal. Sensible approach, but doesn’t help if you want to see last month’s results in order to make a decision on testing priorities. Also, only the first step can be set as required, so it is not uncommon to see leakages in to the funnel steps from pages that are not previous steps. And you can’t segment the funnel data – at least not until you have access to the new features currently in Beta.
  3. Use the ‘Navigation Summary’ report, which is helpful in getting a sense of flow through a given page. But it only applies to individual pages (including previous and next), is based only on clicks, and only shows a limited number of pages in the ‘next’ list. The ‘class’ of pages we want to measure may be dispersed over a large number of individual pages.
  4. Use ‘In Page Analytics’: again, only one page at a time and, while it can be a helpful visualization, tends to be an unreliable data source.
  5. PadiTrack gets around all these issues! You can use various match type options or regular expressions to identify page types by URL or Page Title (bonus!), select your desired date range, and *boom* dat’s it. For more granularity, you can filter by top referrer or top keyword or apply GA advanced segments.
Paditrack select page

Example: setting up first step in PadiTrack

Once you set up your steps – as few as 2 or as many as 5 – PadiTrack will create the funnel on the fly for your chosen date range:

PadiTrack conversion funnel

PadiTrack Funnel/Navigation Path

So we can see in this case that about 15% of those visiting a category page went on to a product detail page during their visit. Depending on our expectations/goals, this may warrant testing changes to the category page design in order to improve flow-through to product details. Or you can extend the funnel by adding more steps (up to a total of 5) to assess further progress toward the end goal. Or you may compare this to other key navigation steps on your site to prioritize testing efforts. All easy to do, with results available in minutes.

Care to share any thoughts or experience with PadiTrack or other conversion funnel/navigation tools? Please do!

Google Analytics: Rewriting Page URLs to include ‘WWW’

Avoid disaggregating page data in Google Analytics by applying a filter to force all ‘www’ domains to be displayed in Content reports as ‘www’ version ( as opposed to

Out of the box, Google Analytics displays URLs in Content reports without using the domain name (‘page1.html’ instead of ‘‘) . This makes sense in most cases, since it is redundant and you probably know what your domain name is. However, there are a variety of situations where you may want to display the full domain name, most commonly when your site is spread across multiple subdomains. (,,, etc.)

It is easy enough to add a filter to your profile that will cause the full domain/subdomain to show up in your Content reports. (And, of course, if you want to track across multiple domains and subdomains, you’ll need to modify your GA tracking code to accommodate this.)

Potential Issue: Page Data Split Between Two Versions

All well and good, but there is an issue that arises when the full URLs are displayed in Content reports on sites where visitors can access the site at both ‘’ and ‘‘. As a result of these two versions of  the domain, the same page may be reported on separately, in the ‘www’ and ‘non-www’ versions:

Page data split between www and non-www

In the example above, the same page is shown in two separate versions, one with 16 pageviews and one with 6 pageviews. Not cool.

For search engine optimization,  this causes canonicalization issues and is best dealt with via 301 redirect. However, this may not always be possible – at least in the near term, particularly if you don’t have access to your server settings – and you may want to have your data as accurate and relevant as possible NOW.


By applying an additional filter ahead of the filter that adds the domain to the adds the domain to the URI, we can force Google Analtyics to include the ‘www’ at the beginning of the domain in cases where it is not already present. The desired result:

Page data consolidate as 'www'

Here we can see that the data for ‘default.aspx’, previously split between two ‘pages’ in the report, is now consolidated to give us a more relevant picture of what is happening with visitors to the site: 22 pageviews of this page (16 + 6). Aaahh…that feels better!

Two Filters Used: one to add ‘www’, one to show full URL

This solution was reached by applying two straightforward filters to the GA profile:

1. A filter to recognize situations where the hostname starts with the ‘raw’ domain without ‘www’ (‘’ in this example) and then adds ‘www’ at the beginning of the hostname in these situations. This filter will not add ‘www’ in cases where it is already present, nor will it add ‘www’ in cases where the page is on a subdomain. It does assume that you have a single domain, so it would have to be modified in the case of cross-domain traffic. It also assumes that you want to add ‘www’ to all URLs, as opposed to removing ‘www’ from all URLs. If you prefer no ‘www’, just flip the fields around.

Filter 1: Add the WWW

2. The usual filter for displaying the full URL including domain. I have included a leading ‘/’ in the Output To -> Constructor – this is not typically recommended in official documentation, but I did see it recommended somewhere by one of the big names in the field, so I figured I should try it and have seen no adverse affects.

Filter 2 - included domain

That’s all there is to it. Works for me and I hope it will work for you, but let me know if you have any feedback.

This post goes out to my friends at (or if you prefer 🙂 ).


One approach that I had high hopes for didn’t pan out. Not sure why:

Filter attempt with search and relpace that didn't work

Google Analytics Content Drilldown – More Useful Than It May Appear

For a lot of websites, the ‘Content Drilldown’ report does not appear to be particularly useful. In fact, compared to the ‘Top Content’ report, it often seems…completely redundant. For example, the only difference in the reports shown below is the name. (Aside from the difference in the number of pages – which we’ll get to later.) Furthermore, when you drill into an item on either report by clicking on it, you get to the same detail page. But, as I have (finally) come to realize, there is in fact more here than meets the eye, and for some sites the ‘Content Drilldown’ report may provide crucial, under-used perspective on site usage.

GA top content report

GA content drilldown report

(For many sites, there is no noticeable difference between the ‘Top Content’ and ‘Content Drilldown’ reports.)

The difference, as demonstrated in the screenshot below, is this: the Content Drilldown report (as its name admittedly implies), shows activity at the folder level, not just page level.  Depending on the structure of a given site, this can provide a very useful aggregation of data by folder that allows for easy comparison of performance between different sections of your site.

GA content drilldown report with folders

This example is for a site that is almost entirely structured in folders. Other than the home page (/index.asp) everything in the Content Drilldown report represents different sections of the site, organized by content.  ‘Index.asp’ shows up in the report because it is at the root level of the domain. So by rolling up all the pageviews in a given section, we can see in this example that while they are doing pretty well on the ‘shopping’ section of the site, in terms of exit rate, they are losing a lot of visitors in the ‘ideas’ section. Could be a good area to focus on for improvement!

And from here, when you click on one of the items in the report, you drill down into the next level of folders/pages. (Note that at each level, the number of ‘pages’ viewed refers to folders and/or pages at that level – hence the difference between the number of pages in the ‘top content’ and ‘content drilldown’ reports in the first example above.)

It’s also worth noting that if you are tracking different subdomains within your site and you have a filter in place to show full domain names in content reports, the Content Drilldown will start at the subdomain level.

With the advent of more flexible custom variables, site sections can also be tracked by applying these variables to pages. That approach has some advantages, but it involves changes to the GA tracking code. (And warrants a separate blog post!) Meantime, if you have your site architecture in order, the Content Drilldown can get you a long way right out of the box.

Entrance Sources in Google Analytics: Don’t Go There

The ‘Entrance Sources’ report in Google Analytics offers little, if any, value but holds great potential for confusion.

We all love Google Analytics for the super-intuitive interface that makes it easy to navigate around and generate reports that quickly tell us what we need to know.  Especially helpful for those who might not be in there every day but still have business questions that need answering.

But, there are some places in Google Analytics where the terminology tossed around is maybe not so intuitive and can actually be downright confusing. Case in point is the ‘Entrance Sources‘ report. This came to light in a recent client scenario:

1. A micro-site (let’s say ‘’) was created for a promotion to drive traffic to a specific page on the main site (let’s say ‘/community/…’).

2. The client was looking at content report to see how the page was doing in terms of traffic, and saw that it had 2,768 unique pageviews, indicating that there were 2,768 visits that included a view of this page.

GA Content Report

3. The client wanted to know how many of these visits came from the micro-site, so she did what seemed like a logical thing: clicked on that page in the report and then ‘Entrance Sources’ under ‘Landing Page Optimization.

GA Content Details

Here’s what she saw:

GA Entrance Sources

So now total unique pageviews have seemingly gone from 2,768 to 7,134 of which the micro-site is accounting for 6,611, well above the number of pageviews shown in the previous report.  Clearly, something amiss.  And yet, if a reasonably intelligent person steps back and takes a look at it, what else could this report mean?  Other than it shows the  pageviews/unique pageviews/avg. time on site/etc for the page indicated in the Content box based on the Entrance Sources listed in the ‘Source’ column? Especially given the large bold heading that yells, “This page was viewed 8,722 times via 25 sources“.

In fact, it means something quite a bit different, although there are no clues. You just have to be in the know. 🙂 For those who are in the know, this report actually indicates the total number of pageviews/unique pageviews/etc throughout the site for visits that a) arrive from the source indicated and b) land on the page shown in the Content box – but then may continue on to other pages.  And that’s the catch: all the other pages are included in the count of pageviews and other metrics.

So for starters, the large bold heading should yell something more accurate like, “This page (and subsequent pages) were viewed 8,722 times via 25 sources”.

The current presentation may strike some as bizarre, misleading and possibly even useless. There could be some method to Google’s madness – but maybe not. The best thing I can think of was that this report could provide some insight into the site-wide impact of different source/landing page combinations that could inspire a person to try to direct more traffic from a given source to a particular page rather than others that may have relatively less flow-through.  But really, there’s easier ways to get this kind of direction.

Which brings us back to the client’s initial question: how many visits came from the micro-site and entered the main site on the /community/ page? There are a couple ways to answer this question:

1. Top Landing Pages: breakdown or pivot by Source. In this pivot table view we can easily see that the drove 2,166 visits to the /community/ page.  And with only a 11% bounce rate – not bad!

GA Landing Pages

2. Traffic Sources – Referring Sites: breakdown or pivot by Landing Page. From this view we can confirm that drove 2,166 visits to our /community/ page, of which 75% where new visits. Great confirmation that our micro-site is attracting new potential customers.  And from this report we can easily access Goal data to gain some insight into the quality of these new visitors.

GA Traffic Sources

So these views help us get to the larger question at work here: is the micro-site project having the intended effect and providing the desired return on investment? Although we don’t have all the data we need to answer that question (amount of investment, target return, baseline data, etc.) we can certainly see that the micro-site is having a positive impact in terms of both quantity and quality of traffic being generated – and that’s a great start.

Hopefully, this clears up the confusion that can be caused by the Entrance Sources report. My advice: don’t go there. But I’m open to ideas if anyone else has profited from this report.

Note: the foibles of this report are also discussed in Google Analytics Help here.

Tracking Outbound Links the Easy Way with Google Analytics

Stephane Hamel at Immeria offers an elegant solution to a cumbersome problem

Google Analytics is, of course, a powerful tool for measuring onsite performance and supporting decisions around how to improve better results. For one thing, you can easily get a bead on where visitors are leaving your site just by checking the ‘Top Exit Pages‘ report.

Exit Pages ReportHigh % of exits may be fine for a goal completion page (‘thank you’ for your order) but may not be so good when it is your home page, as in the example to the right, and almost 80% of visitors to the page are exiting from there. So we would want to look at this page and see what can be done to increase the stickiness to the site.

With all its power, one thing Google Analytics can’t tell us is where those who leave the site from this page are going, even if they are using exit links on our site. At least not out of the box (the same is the case with most web analytics platforms). For example, in the case shown in the screenshot, it turns out that there are several major calls to action on the site’s home page that lead off-site. It would be very helpful to know which, if any, of these links are being followed by visitors.

Now, I know what you’re saying: easy – either tag them as virtual pageviews ( onclick=”pageTracker. _trackPageview(‘/Exit-Links/’);” ) or apply event tracking. Which is fine, except that it has to be done on a link-by-link basis. That may be okay when you have a couple of featured links on a home page, but I have another site that acts as somewhat of a portal to breweries in British Columbia, with tons of links to other sites. Hand-coding dozens of links is not my thing (and this is a small site).

But Stephane Hamel has come to the rescue with some tidy GA Javascript that automates the process of tracking outbound links and/or file downloads in Google Analytics across your site.  All you need to do is:

  1. Grab this Javascript file and place it on your server.
  2. Add this Javascript line below your GATC (with appropriate reference to the Javascript file location):

Additional line of Javascript below GATC

One other thing you may want to do: check the Javascript file to see if you want to change the settings that determine whether outbound links and downloads are tracked as virtual pageviews or events. The default is to track both as events, which may work for you.  Depending on the content, I generally prefer to track outbound links as events (I don’t want them inflating my total pageviews) but track downloads as pageviews (on the basis that a pdf product spec sheet is, in a sense, a ‘pageview’ of a different kind.)  The added advantage of using pageviews is that they can be tracked as goals.  If you want to change either of these settings, look for this area in the code and make changes accordingly:

Settings in gaAddons Javascript file

There, that was easy. Now I can see which exit links visitors are using most often, which opens up all kinds of opportunities for content development, partnerships, etc.:

Event report showing exit links

This has just been turned on a couple of days ago, but I’m already getting an idea of who I should go talk to about getting some free beer! 🙂 And depending on how that works out, I’ll be able to assign value to this event.

Worried About Google Analytics Opt-Out? Nah (At Least Not Yet)

On March 18, there was a brief announcement on the Google Analytics Blog giving a “head’s up” on Google’s plan to release a browser plug-in that will allow web users to opt-out of Google Analytics tracking.  Naturally, this sparked some vigorous commentary, with opinions ranging from ‘disaster‘ to ‘non-issue’.  (Haven’t actually seen anybody – at least any internet marketers – suggesting it might be a GOOD thing.) Eric Peterson had probably the most complete coverage of the issue, with some astute observations regarding Google’s privacy motives being tied to their interest in collecting data from US federal government sites.

My own inclination is to side with those that believe this will have little impact on web measurement for those employing Google Analytics on their sites, for the following reasons:

1. Low Usage: The opportunity opt-in or opt-out is largely ignored by humans, who tend to go with the default, as Dan Ariely has so convincingly pointed out in recent years.  If it works that way for organ donation, we can be pretty confident that is how people will respond to analytics tracking.  Especially since Google Analytics is already set up to not collect personally identifiable information.

2. Existing Limitations: Web analytics data is already fraught with limitations caused by use of cookies, javascript, and half-baked implementation.  These will likely continue to add up to more impact than any opt-out system.

3. Trends: Even if there was some initial adjustment as masses of users opted-out, there would still be enough data for most sites to establish valid trends moving forward. And data trends are arguably more valuable in web analytics than raw numbers.

4. Strategic Interest: Google has a strong interest in encouraging widespread usage of Google Analytics and has made huge efforts in the past to make this tool as attractive as possible to as many site owners as possible. Unlikely they are going to put all that marketshare at risk.

So this is definitely something we want to keep an eye on in order to determine the implications as details are revealed and the program actually rolls out.  We’ll watch, but we’re not worrying – at least not yet.

After all, as Mark Twain said: “Worrying is like paying interest on a debt you don’t owe.”

Power, Flexibility, Intelligence: the New Google Analytics

Google Analytics has some very cool new enhancements announced on the Google Analytics Blog today.  It may take some time to get the full appreciation of these improvements, but it is clear that these moves have increased the power and flexibility of Google Analytics, taking it another step toward being a fully-featured enterprise analytics package.

The primary changes announced are:

  1. Engagement Goals – now you can set goals based on time or pageviews, in addition to conversion events. Major bonus for site’s wanting to track engagement.
  2. Expanded Mobile Support – now identifies and tracks traffic from a wider range of mobile devices, and can tracking use of apps.
  3. Advanced Filtering – can now apply filters to multiple metrics within the same report.
  4. Multiple Custom Variables –  whereas previously only one custom variable could be set on your site, using the _setVar() function, it is now possible to use more custom variables for visitor segmentation.
  5. Alerts – automatic and custom alerts designed to help users focus on changes that are the most meaningful in terms of their site goals. Below is Google’s short video explaining this feature:

So this is some pretty big stuff. Not all the features will be available to every account right away, but it will be great to make use of them as they do become available and offer new ways to extract valuable insights from the data.