Server Side Sessionization: With “Universal Analytics” the “sessionization” occurs at he server side. The new analytics.js will not maintain any tracking information (other than an anonymous identifier).
It represents important advantages allowing to add new search engines in traffic sources, configure the timeout of a cookie, classify some cookies as direct traffic (yoursite.com in a search engine), and last but not least the unique ID allow us to integrate the behavioral information of a user to al the information from that user, stored in another sources like a client database or CRM.
Customized segments and metrics: The above mentioned enable to configure the custom dimensions and metrics right on the tracking code and in the administration section as shown in the following image.
_gaq.push([‘_setCustomDimension’,1,’Custom Dimension 1′]);
Measurement protocol: This is similar to the well known EDS (External data sources) from other platforms. This feature allows to send information from any source to Google Analytics scaling its possibilities to a new level. So now you can send to Google Analytics information related to external sources Call Centers or CRM, among others, to measure even measure a conversion generated offline. This will be done with the current method __utm.gif (image) and the information is send with the GET or POST method. As long as you use the Google Analytics protocols in a correct way, it will always accept the sent data.
Besides, will be possible to assign marketing and other costs to a particular user. So we can start talking about the model proposed by this blog, the Analytics 2.0 model, in which instead of analyzing ROI we will be able to analyze ROCI (Return on customer investment) allowing us to understands which segments of clients are making us earn money and witch other we are losing money so we have to stop investing money on them.
Dimension Widening: This feature permits generating more and better decision making scenarios based on custom dimensions and metrics, helping us understanding the impact (if there is any) of thousands variables towards a particular conversion (sales, registration, etc). Some post ago we talked about how to do that by using variance analysis (anova). This feature is an insight generating machine! in my opinion one of the best features ever introduced by Google Analytics.
This is becoming interesting. I went with very low expectations to the summit, waiting for “Much ado about nothing” but finally we see a light at the end of the tunnel, it’s far, but it’s there!