GA4 for Travel: how to enhance your business
We often talk about Google Analytics 4 or GA4 associated with activities related to eCommerce. Obviously it is possible to decline the flexibility given by this new tool also for the Travel industry. GA4 allows to obtain a greater volume of data and opportunity for analysis if compared with Universal Analytics.
In addition to the main reports such as Funnel, Pathing and Segment Overlap, with GA4 you can introduce parameters or events (let’s leave the difficult choice to those who deal with the data architecture) that can be used to improve audiences and above all to generate interesting ups and cross selling.
When it comes to hospitality it is key to understand the user behavior, the customer behavior and grab their attention through on-site personalization activities and cross-site remarketing / retargeting. With this in mind, Google Analytics 4 allows you to create and analyze an almost infinite number of combinations of data, useful for improving the user experience and increasing the probability of conversion, both micro (e.g. registration to the newsletter) and macro (booking made).
Furthermore, thanks to the offline data import, it will be possible to evaluate in addition to the various target ROAS also the habits of “loyal” customers, that is, those who book the accommodation facility every year, be it an hotel, a cruise, a camping / glamping or similar structure. Just think about the possibility of targeting top spenders in the next 28 days to provide upsells (e.g. courses, private pools, spa treatments, etc.), rather than offering the services they usually buy in the bundled structure, perhaps at a discounted price, but with greater margins.
Below you can find improvements that can change both data analysis and Conversion Rate Optimization for the Travel sector.
Reservation Lead Time
It means creating a parameter that contains the time to purchase the service in terms of days from the actual arrival at the structure. You can analyze user clusters and create targeted audiences to increase up and cross selling, according to the time remaining before the chosen trip starts.
For example, for those who book a room with a reservation_lead_time longer than 50 days, it will be possible to create an audience related to complementary services such as “sailing course”, “pitch upgrade”, etc. using both Google Ads and Google Optimize through the correct audiences.
Intended as the number of passengers / users who are involved in the purchase of the service. You can therefore create hyper-targeted segments and audiences to be imported into both Ads and Optimize, in order to customize the browsing experience and increase cross selling. as an example thonk about targeted adv or content only for users who booked 2 adults Vs kindergarden proposal for users who booked with a child under 5, etc..
Via Search Date you can track the search date of the holiday (whether successful or not) and analyze how users interact with the content of the site or app, according to the periods of greater or lesser request. You can generate accordingly “automations”, intended for promoting the purchase of the service in less “hot” and potentially “empty” periods.
Availability of the room / service offered
Knowing whether users view a room or services list page with the amenities offered full available or not, allows you to carry out an analysis specifically dedicated to user navigation and create targeted and effective onboarding or upselling strategies.
Rate Code means both the type of pricing requested by the user (eg. B&B, Full Price, etc.) and the possible use of discount codes applied during the purchase (eg Family & Friends). The types of Rate Code users are more interested in, in correlation with browsing through Search Date, allow you to set up automations that can improve the customer retention process, by anticipating their needs.
Google Analytics 4 for Travel: other improvements
Obviously as you can imagine, there are many other factors that allow GA4 to improve data analysis for the travel industry and generate useful analysis to improve turnover and user experience. Just think of all the interpolations that can be generated via the integration of offline data, or deriving from loyal users, or again from zero and first party data. There is such a plenty of data to unlock and explore!
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