Before digging into the data, it is important to understand a few basic concepts. Without a base in the key concepts of web analytics & GA, it is very easy to misread or misinterpret GA reports, which can have dire consequences, and we certainly don’t want that. But we understand if you are pressed for time, so click here to go straight to the Useful Reports section (just come back and read this part later). - No tracking data is 100% accurate – This is a general tenet to keep in mind no matter what data/reporting you are looking at. There are flaws in all tracking methods and as Heisenberg (no, not Walter White) theorized, the very act of measuring an event changes the outcome of the event, making it impossible to perfectly capture reality in data. As a result, the data in a GA report will likely not exactly match data from other sources (e.g. AdWords, brand reporting, etc.). - Google Analytics does not automatically track revenue and cannot track it for certain sites – One of the most interesting features of GA is Ecommerce tracking, which allows site owners to see where their revenue came from (i.e. Organic Search, Paid Media, Social Media, etc.) and how users behaved before they completed a purchase (e.g. they looked at an average of 10 pages before purchasing). Unfortunately, Ecommerce tracking is not available for branded hotels because the brands do not allow hotels to place tracking code on the brand reservation pages. For independent hotels however, Ecommerce tracking can be enabled as long as the hotels’ booking engines support the integration; however, setting up Ecommerce functionality can be tricky so it is not enabled for many boutique hotels. If you have an independent hotel, make sure your Booking Engine supports GA Ecommerce integration and find someone with GA experience to help you get it set-up. - Set the date range before you look at any data in GA – Data without context is meaningless, so set the date range to help make sense of your data. We recommend using Year over Year data if available because Month over Month data can be misleading due to seasonality. Get the full story at Blue Magnet Interactive