Google Analytics is designed to work best for ‘marketing’ sites where you want high-level views of volumes of hits and are concerned with converting those hits into paid leads.  While there is definitely useful info there for a reading list system, as we know, it is not the end of the story.  

Google Analytics is a system for client-side collection of data. This means it runs on your user’s computer, and as such is subject to many things outside of your control. This means there is no guarantee that theGoogle Analytics stats are going to reflect all traffic. 

When capturing basic hits to a reading list, things like browser advert blockers, security settings and a host of other user setting combinations mean that we can’t always rely on Google Analytics capturing that interaction from the user. 

When we’re wondering where that user found the reading list, we might be thinking they are coming from a link in the university virtual learning environment (VLE), or maybe from a link given to them in class. Again because of client-side restrictions on how traffic sources are identified, as well as some restrictions that are built into the internet’s security model, there can be some ‘missing’ data when traffic from the VLE is redirected to a login service to login and back to the list.  We can only see the last link in the login redirection chain, and so can’t tell whether they came from the VLE or not.

These are all problems inherent in trying to capture usage statistics from the client end of the conversation.

But there is another way to get the stats we care about.

Talis Aspire is a system hosted for you in the cloud. This means that to view any reading list, or to use any functionality, your request has to come to our servers.  This is why Talis have moved to collecting stats about what users are accessing from the point of access… i.e. we can collect stats right here on the servers that are serving requests.  We are also moving to adding our own specific stats ‘collection points’ within the new list view and list edit interfaces. This means that we can be much more specific about which stats we’re collecting and do things that go beyond what Google Analytics can tell you about people interacting with the reading list.

We’re collecting this mass of data on user behaviour into what into our new Advanced MIS data warehouse. Essentially this is a database containing both the application data and events which describe how that application data is being used.

Having this data collected into one place and updated almost as it happens, means that you can now answer with certainty questions like:

  • Who is viewing reading lists?
  • When are they viewing lists?
  • Are they also viewing items on the list?
  • If they viewed the item are they then clicking on the link to take them to the resource?
  • Was that link they clicked on to an ebook, an article, a digitisation or a regular web URL?

So while there is still value in having Google Analytics to give you an idea of how your reading list is being used, you can now get a level of detail that means you can build tools for personal tutors that show them whether the student they have an appointment with has accessed any of the lists for their course. And if they accessed the list, did they also click through to view resources?

To see more about what data is included in Advanced MIS, you can view the full documentation which details exactly what data is available.

Talis Aspire Advanced MIS is available to try now as part of a trial. If you are interested in getting access and seeing what the data is saying about your students, please raise a support ticket and we’ll make sure you speak to the right people.