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Automate your tag clouds with Omniture

One of the nice things about Omniture is the ability to export information out to other systems. We use this feature to generate tag clouds on our site, based on the most popular courses viewed over the last 30 days, segmented for different audiences.

One of the nice things about Omniture is the ability to export information out to other systems.  We use this feature to generate tag clouds on our site, based on the most popular courses viewed over the last 30 days, segmented for different audiences.

In order to do this, there are a few things that need to be done first.

Firstly, we report course views as products, passing a shortened name of the course from our content management system and database, to the s.products variable, such as:

s.products = “;Marketing-and-the-Media”;
s.events = “prodView,event5”;

We have set up event5 as a success event, signifying a course view.

As we have multiple pages associated to a course, we make sure that we only pass the s.products and s.events values once per course view, irrespective of the page within the course a user is looking at.  This is done by using some custom code within our s_code file.

In SiteCatalyst, we then use SAINT classifications to generate Course-based reports, associated to schools, faculties, type of course (undergrad or postgrad) etc.  This allows us to get in-depth information on our course activity, along with conversions etc.

Audience segmentation

segment_builderA common reporting segmentation for us is to compare Australian traffic to International traffic, so we have created two segments, using the segment builder.

The Australian segment includes any visit where the GeoCountry was Australia.  The International segment includes any visit where the GeoCountry was not Australia.

Exporting the data

dw_reportWe then use DataWarehouse to create two reports, based on the last 30 days of activity.  Each report uses the segment defined above, with the Course name and the number of Product views (as we use the product variable to set course views).

These two reports are scheduled on a daily basis to export the data to our FTP servers as a CSV file.

Once we have the files, we import the data into a database along with the date of the file, so we can use that later.

Now we have the last 30 days of activity, by each course, by traffic source as a dataset that we can use on our site.  It’s then a fairly straightforward process to match the course name with the URL of the actual course, so it can be used as the link on the tag cloud.

The end result

Each day we query the database and using standard tag cloud calculations, we are then able to re-produce the data back out onto our site.  We currently feed the data back out as an XML file which is read by our Course Browser flash tool – showing both a Domestic and an International view of the most popular courses.

tagclouds

We’re also working on something similar for internal search terms, which will be used to populate a “search as you type” functionality on our search forms, but it will be segmented by audience type – Staff, Student or Anonymous (being general traffic).  That one is a little tougher, because we have to associate the most common destination clicked on, with the searched-for term.  But more on that in a later posting, once we have it working.

So, using a combination of Omniture SiteCatalyst, DataWarehouse and segmentation, we’re able to easily offer our users with quick navigation methods to various pieces of content, thereby enhancing their user journey.

The content and advice contained in this post may be out of date. Last updated on August 9, 2009.

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