For the most effective web analytics,
Google.com redesigned its old software and introduced Universal Analytics to the world Universal Analytics should make cross device tracking possible, i.e. better track the customer journey.
If you are a layperson at Universal Analytics for the first time, you will probably not notice any difference. You hardly notice that Universal Analytics is traded as "The next big thing" on the user interface, everything looks like Google Analytics - apart from additional menu items in the administration for tracking information. The additional menu items are underlined in red in the image
Session settings: Here you can choose the length of a session. By default, Google Analytics had set 30 minutes. With Universal Analytics you can choose between 1 minute and 4 hours. The second value indicates how long a campaign can be measured. In Universal Analytics a maximum of 24 months.
Sources of organic search: Additional search engines can be added here. For example, if you consider Herold as a search engine. Here you will find a list of all search engines integrated in Analytics
Referral exclusion list: All domains that are stored here are not output as "Coming via a referral". Often you don't need this option - it makes sense, for example, if the analytics code is not integrated on each of your pages.
Search term exclusion list: Particularly useful if you enter your company name or main products here. Users who come across these terms already know your company and should be listed as direct traffic rather than search engine traffic.
Integration of other data in Universal Analytics
This is probably the main advantage. Universal Analytics can process data from almost any device that is sent to Universal Analytics. You can track transactions that take place in the shop, e.g. via a customer card program that is linked to a user ID. However, this is associated with a very deep knowledge and programming effort. For an example, see this post by Julien Coquet. An interesting feature is the linking of CRM data. These can be linked to the data of logged-in users - this gives you further demographic breakdowns of user behavior.
