Google Data Studio and Hotel Revenue data: the most effective way to look at your performance
I recently started working with Google Data Studio which, by the time of this post, is still in its Beta phase. Despite that, I only have one word to describe the outcome after 2 weeks I spent trying and testing the tool: AMAZING!!!
First, Data Studio helped me to overcome one of the biggest issues I had since the very beginning when I started creating the RevANALYTICS project: making and displaying data in the most effective, readable and understandable way.
As a matter of fact, up until now I could only rely on various table-styled reports to display and combine different dimensions and metrics, but a table with a bunch of numbers and values may be a bit difficult to read, especially at the very beginning when one is not used to this kind of reports.
Google Data Studio allows marketers (and, as in my case, Revenue Managers) to easily create different types of dashboards like pie charts, scorecards and bar charts, by simply connecting a source that, in my case, is Google Analytics (but it can be Google Adwords or even external sources). In no time you can style, position and combine these dashboards in the most effective, easiest and quickest way. Looking at your hotel performance has never been so fun!
Let’s get a bit into more details.
It is not my intention to explain how to set dashboards up, it’s so easy and anyway full of “how-to” articles and tutorials out there in the internet, that it would totally be futile.
I’d rather want to share what kind of dashboards I set up, what kind of data can be displayed and how it may look like, always considering we are dealing with RevANALYTICS data.
The above is just a tiny little part of the overview page. In fact, I created many different pages within the same Data Studio file: other than the overview, I wanted to have a page for the most important revenue-related metrics such as Occupancy details, Length of Stay, Booking Window and Rooms&Rates.
Still in the overview page I created multiple pie charts representing device and source performance, divided by booking tentatives (Session) and reservations respectively.
Note that the list of sources, as in the example above, may not be reliable if there is no proper cross-domain tracking between the hotel website and its booking engine. Sources and channels users are coming from are first tracked on the website. The cross-domain tracking allows to pass this information over to the booking engine which, most times, has a different domain.
Scrolling down in my overview page I created a dedicated benchmark area, where dashboards take into account the performance of the previous period in exam:
At the end of my page, I created the following bunch of scorecards and funnel:
If, in your booking engine, users have the option to sign up for your newsletter, with the event tool of Google Analytics you can track how many subscriptions you got. In a scorecard you can have this number displayed and compared to the previous period.
The “No Availability” tracking is also possible through the Event tool in Google Analytics. Quite self-explanatory, this metric tracks how many times the booking engine responds with a “No Availability” message, meaning the booking search submitted by the customer doesn’t trigger any available rooms and rates.
Since a session that produces a “No Availability” is anyway a session, and it’s taken into account when computing the overall conversion rate, I was thinking of creating a secondary conversion rate metric (let’s call it “Conversion Rate Net No Avail”) that subtracts all “No Avail” sessions from the total session counting. This way the conversion rate may be considered more reliable cos only based on sessions that produce at least one result in terms of rooms and rates.
The higher this delta between the original conversion rate and the “Conversion Rate Net No Avail” is, the more often your potential customers do NOT get any results when performing a booking search.
Last but not least, the booking funnel. In Google Analytics is quite easy to set up a booking funnel based on Goals. Unfortunately, Data Studio is in no way connected to any Google Analytics funnel. What?!?
Imagine my frustration when I realized that, one of the best tool I have ever worked so far, it doesn’t have one of the most useful feature I used to work with.
This means that either one gives up with setting this up in Data Studio, or finds another way/workaround to make it possible. Luckily, with a bit of creativity and by looking at what other individuals with the same problem did, the booking funnel is properly in place and working.
The booking funnel gives a great overview as to how users interact with all different booking steps, specifically it shows, for each steps, how many users move forward, within the booking process, and how many jump out. With simple math you can then get the percentage of the exit rate per booking step (in red the in the above image).
The rooms&rates booking step is and will always be the page with the highest exit rate. Pretty simple, this is the most important booking engine page, that includes everything a potential customer is looking for: your products.