A small but potentially quite big change to Google Analytics has been pushed out. It relates to how sessions are handled, which you'll see in the "Visits" metric in Google analytics.

Most web analytics tools have to work out a "visit" metric to try and give you some idea of people coming to, then leaving, your site. The problem is that the analytics tools don't get a "goodbye" message when the visitor leaves the site, so they have to use other mechanisms. The traditional way is a timeout of 30 minutes without any activity from the visitor, or if the visitor closes his browser.

This change to Google Analytics introduces the idea of any change to the traffic source value resulting in a new session, that is a new visit. These values are set whenever a visitor arrives from an external site, meaning any new arrival basically, even if it happens within the previous 30 minute time-out bracket.

It's a pretty sensible change to the way the data is calculated and will affect all reports that include the "Visits" metrics. Any business wants to know how many people come through the front door, and how well they're converting them into paying customers. Even people who come through the front door more than once should be counted in that metric.

Details from Google about the change, including some rather panicky comments from users who are alarmed, can be found on the official Google Analytics blog post about the session tracking recent changes.

Eyeblaster just launched an interesting new report that shows a correlation between dwell time for interactive ads and  increased conversion rates. 

The connection is sort of obvious but nevertheless good to see some confirmation and wonder if we will see some more mini applications within display ads now comparable to Facebook apps.

How many times have you talked about a truly integrated campaign but lacked a diagram and metrics framework to properly explain and measure the interaction between channels? We recently designed the below campaign flow and simplified metrics framework for one of our clients to explain the interaction between the various different paid and organic channels, websites, social networks, retail outlets and CRM. 

 

Unfortunately we can't share the actual campaign results but the impact was amazing. The traffic levels increased significantly during the campaign and for the first time rivalled historic peaks from previous Christmas periods mid year. However, the integration of the analytics framework into the campaign planning process from the very beginning ensured that tracking best practice was followed and a maximum amount of data could be collected across all channels. Best of all, if the below framework is used across all campaigns they start to become comparable and a benchmark emerges but that requires a lot fo discipline on all sides.

 

But let me explain a little more about our thinking behind the metrics framework. First of all, we renamed the 'awareness' stage to 'reach' because those metrics are a lot less debatable for all channels (i.e. we know how many people search for something or were exposed to a banner but not really how many people actually become aware of a message). As metrics on 'interest' and 'desire' are actually hard to differentiate in the standard AIDA(S) formula we combined them into a single 'engagement' category (i.e. everything after a non-bounce and before an actual conversion). The 'action' metrics category stayed the same, it simply contains all the conversion data on actions we wanted people to take but doesn't have to be limited to sales of course. Finally, 'loyalty' is a hard one to measure at the best of times and pretty fluid so we renamed that stage to '+buzz' which stands for positive buzz or people talking about the company in favourable terms which is of course far from being loyal but we would argue it's easier to measure and one would be pretty hard to achieve without the other.

 

Anyway, what do you think? Please feel free to comment and help us to improve the model and maybe even share some actual metrics you measure at the different stages.

It looks like most marketers are still missing the point of social media, at least their metrics for success are not reflecting it.

According to the latest eMarketer chart below most marketers still rely purely on traffic to their websites as the key success metrics. What about customers complaining about a brand, they won't go and visit the companies website, right? Or take the new online store on Facebook, customers might never have to leave the social network anymore in the future.

If you agree that pure referral traffic alone is a bad measure for social media success have a read through our earlier blog post on social media measurement tips and tools to get some ideas of how to do it right.