We find it quite interesting to analyse the frequency that people make use of their A1WebStats data.

Some people are content to receive the daily email showing them which companies visited the website in the previous days.  These are the ones that could be benefiting a lot more by using the true power of the system instead of just focusing on which companies have visited their website.

Other people log in periodically and run certain types of reports, seemingly with a clear objective in mind.

And then there are what we (nicely) call the ‘serial lookers’.  These are the people who have A1WebStats in their browser for long periods of each day.  Take, for example, the screenshot below, which shows one subscriber’s use of the system over several hours on one day (7 September) …

Looking at the grey part of the screenshot you can see that they came into the site via the http://www.a1webstats.com/stats/login.aspx page.  That’s where they enter their login details.  From then they would have accessed their data.  The ‘Page Reload’ row below that shows the same page url again.  What actually happened was the system logged them out (for security purposes) inbetween their last view of the data and when they wanted to look at more data. So, when they go back to look at more data they have to ‘login’ again.

So what the screenshot above shows is that during that one day, they re-logged into the system five times.

You’ll notice the 1 day(s) since last visit link.  This shows us that they came into the website the day before and we can view their login activity in the screenshot below …

Again, looking at their A1WebStats data we see that it’s actively used during the day.  One more example below shows the day before.  Same subscriber and similar use of the system …

That subscriber (and there are many similar) could be doing one of the following:

  1. Micro-analysing website visitors throughout the day, to see what it tells them.
  2. Running different types of reports.
  3. Using the system inefficiently.

This last point is important because while on the surface it looks positive that the subscriber is regularly logging in and making use of the system, it could be that they’re not using it in a way that would make better use of their time.  So, when identifying such patterns, we make contact with the subscriber to see how they’re getting on (which can spark off ways they can better use the system).

We don’t sit there all day looking at individual visitor paths because we have other systems that tell us how subscribers are interacting with the system.   However, if we identify patterns that may imply that a subscriber is not getting the full benefits from A1WebStats then we will usually make contact to see if we can help.

If we did a poll of how many people download something online (which could be free entirely or initially), but after awhile they lost interest in it, we think the numbers would be quite high.  Sometimes it’s not really clear how to use a system (and we wouldn’t expect anyone to fully ‘get’ how we see A1WebStats can be used to its full potential) and because people are busy, they sometimes give up.

Every A1WebStats user will have a different way of using the system but generally they fall into a few groupings:

  1. People who rarely log in but use the daily reports emailed to them.
  2. People who log in for a specific purpose periodically, but not every day.
  3. People who log in every day to look at certain areas of interest (we always advise that people look at ALL visitors, not just those identified as being ‘companies’).
  4. People who log in every day and log back in several times during the day, using the system as much as they can.

So, there is no ‘one size fits all’ when it comes to recording how often people use A1WebStats (and we suppose this applies to any type of analytics solution) but subscribers can be assured that we’re keeping an eye on such patterns so that we can help subscribers get the best use out of what we offer.