Wednesday, April 27, 2011 | 11:10 AM
Custom Variables allow website owners to extend Google Analytics’ measurement capabilities and track information that is meaningful to them. In this series of three articles, Barbara Pezzi, Director of Analytics and Search Optimisation for Fairmont Raffles Hotels International, shares how she makes use of custom variables to better understand how to better engage with her customers. You can familiarise yourself with custom variables in part one of this series. – Ed.
We recently introduced the option of booking more than one room within a single reservation on our Fairmont sites. In the past, if a visitor wanted to book three rooms, she would have had to go through the checkout process three times.
This new option greatly improved the booking experience for our customers. We knew this both intuitively and anecdotally, but we wanted to understand the impact of this change with data. We wanted to understand the popularity of this new feature, which group of hotels benefited the most (e.g. city hotels or resorts), and what the impact has been on our booking rates.
Booking types - Session-level custom variables
We used a session-level custom variable in Google Analytics to help us answer these questions. Session variables are applied to a single session and help you understand specific behaviours that happen during a particular session or visit.
As with all custom variables, the code to add to your Google Analytics snippet is very simple: a single function placed in the confirmation page above the _trackPageview() call. We set a custom variable called “booker” each time a booking was made, and its value would be “single” or “multiple” depending on the number of rooms booked.
_gaq.push(['_setCustomVar', 1, 'booker', 'single', 2]);
Analysing the data
Using this custom variable, we could conveniently assess the proportion of sales through our sites for single or multiple rooms.
We are also able to assess corresponding traffic and conversion data and even see the increased value of “multiple” booking visits. By creating an advanced segment, I could identify which traffic channels sent me these customers and adjust my marketing activities accordingly.
Identifying relevant keywords
Since organic search traffic from Google is sending us almost 45% of all multiple “bookers”, we decided to drill down deeper and look at the keywords that sent us the traffic. We do a number of things with these keywords: add them to our paid search campaigns, optimise for them in our SEO strategy, and use them as seeds for identifying new keywords. Our multiple room bookers, for example, seem to favour our more traditional hotels and resorts. With this information, we can now look at adding content to our websites that would appeal to this group.
I can also easily identify which hotels seem to be more popular with multiple room bookers and advise the property accordingly. They can then use this information to create new offers that might appeal to small groups or families who are likely to book multiple rooms.
Identifying key markets
We were interested in identifying the countries of residence of our customers, and in particular, which locations were more likely to provide us with multiple room bookings.
Based on the data, we can now run adjust our marketing campaigns in the best performing markets to include multi-room offers.
Applying our learnings
Session-level custom variables allowed us to effectively analyse a scenario that was unique to our websites and wasn’t immediately available in Google Analytics standard e-commerce reports. We are now in the process of introducing the multi-booking functionality to the Swissotel websites and feel that we have a head start in ensuring its success thanks to the learnings we gained from our Fairmont sites.
Stay tuned for part 3 in this series, in which I will discuss page-level custom variables.