Steve: In my last blog, I talked about some of the use cases for Webtrends Explore that we have seen from our clients over the last 9-12 months. Recently, I spoke with Thomas Gerstmann from e-dynamics who works with one of our large airline clients to get his perspective. Thomas, thanks for providing details about your experiences with Webtrends Explore. Can you tell me a little about you and your company?

Thomas: Global travel companies are at the forefront of capitalizing on the multi-channel digital customer experience. As a Senior Intelligence Consultant at e-dynamics working for a major airline, it’s vital for me to provide insights into how users interact with one or more of the airline’s different digital touch points.

Steve: Explore was built to enable unlimited exploration of Webtrends 1st party data in a very flexible and ad hoc way to look for unexpected behaviors and drill into the causes. Can you give us an example of how you are using it with your client?

Thomas: I’m using Webtrends Explore for intuitive and continuous ad hoc analysis with the goal of reducing online errors for the airline, and in doing so, increasing conversions.

The airline has a number of digital channels: a classic website, a mobile website and some apps. The existing Webtrends tag is tracking each as an individual data source – identified by unique data source IDs (DCSIDs). In Explore, we can see all of the data from all of these digital channels in a single view and then segment our analysis to the specific data sources we are most interested in.

Steve: Can you provide more details on how you identify online errors?

Thomas: In Explore we start with a new view based on the data source dimension. So what do we see? For each of the data sources representing each channel are shown some standard measures. It shows how many users, sessions and views every channel has had by default.

But we are interested in more than that. We are interested in seeing the online error rates by channel. So, we use Explore’s ability to configure and add individual measures to build some new ones based on our custom parameter for “errors.” So with these new custom measures created, we can see the following measures in the view:

  • Views (standard measure)
  • Sessions (standard measure)
  • Views with an error event (custom measure)
  • Sessions with an error event (custom measure)
  • Session error ratio (a calculated measure: error sessions/sessions)

With the three additional measures configured in Explore’s measures tab, we can now see how many errors are happening on each channel.

Steve: Because Explore is evaluating all of these “views” of your data in real-time, you have the freedom to interact with the data and add measures on the fly as you did above. One of the most powerful features is the ability to segment your data in any way using any of your standard or custom variables. There are no limits. This comes in really handy if you want to continue your analysis and, say, look a little deeper at only the traffic for a single digital property.

Thomas: Exactly. Let’s say it’s the mobile portal that has the highest error ratio. That would be a good reason to analyze the mobile website errors in detail. To do that, we now add a new segment to our existing view. This can be done very quickly with one to two clicks. This segment reduces the view to that data source for the mobile website only. With simple segmentation, we now see only one data source.

Steve: The view that is shown is now specific to that segment. Any number of dimensions can be added to the view at any time. A dimension can be any parameter you collect including any and all custom parameters. What do you do next?

Thomas: Now we want to know which error codes occur on the different pages of the mobile portal. To find out, we add two additional drilldown dimensions to our view:

  • Second dimension: the page number
  • Third dimension: the error code (this is a custom parameter that we have added to the tag)

Two things are now possible – first, we can browse through the mobile website’s page numbers with the most errors, and second, we can drill down into the top error codes for those page numbers. Not only is this a very interesting analysis but it would normally take me multiple reports, exported data and recombining to reveal these top errors by page number!

But what if we want the top error codes independently from any page name? This can easily be achieved by dragging and dropping the error code dimension to the left of the Page Number dimension, swapping their relative positions. This re-evaluates the view on-the-fly to provide a different analysis.

We now have arrived at some new and valuable insights on the mobile website:

  • The top page numbers with errors
  • Overall top error codes
  • The top error codes for each page number

These insights can now be used to reduce errors and optimize the mobile website.

Steve: Now that you have identified the most common errors on your mobile portal, what do you do to drill deeper into where the errors are coming from and uncover some additional valuable insights?

Thomas: One example is that we can look into the different countries and languages to uncover our distribution of customers. Just add the new dimension “country” as a drilldown dimension to your existing view.

Additionally, we can analyze the error codes per country and per page number to look for a connection between countries or languages and the resulting error codes. To do that, simply add one of these parameters as the next drilldown dimension.

Or we may want to focus on one of the countries and exclude all others. Simply add a segment for the wanted country. We can also easily remove the segment that we applied to give us a view of just the mobile website. By removing this, we can find the top error codes by page number and country for the segmented countries – but this time across all platforms and websites, not just mobile.

For me, Webtrends Explore provides a combination of easily accessible and flexible capabilities that make this kind of analysis so much easier. You can continue to combine different segments, dimensions and measures as much as you want, and dig through big datasets until you find new, valuable insights. There are just a few clicks needed to customize the existing views, and it is easy to find new ways to focus the view for deeper analytical insights. And all of this analysis took only minutes to run through.

I hope you will join me on the Webtrends User Forum and share your experiences using Webtrends Explore. I’ll see you there.


Thomas Gerstmann (@thomasgerstmann) is Senior Intelligence Consultant at e-dynamics, a Webtrends Partner from Aachen, Germany. e-dynamics is one of the leading, independent consultancies for Digital Analytics and Web Intelligence.