Vacanceselect

Finding your dream holiday with just one simple click

The main objective of Vacanceselect is offering the best vacations, based on the personal wishes of the customer. But being active in 9 different countries and in 12 languages, having thousands of different ads and having to take into account the availability of the campsites, it is quite a kill to find the dream holiday easily.

Machine learning, relevance and predictive data

For Vacanceselect, DEPT® created a campaign that called for finding your dream camping holiday with a simple click. By serving personalised ads in combination with personal landing pages, based on machine learning, we’ve created not only insights into the wishes of the customer, but also in the availability of the campsites. This way bookings can be made as easy as pie.

The best holidays, based on the personal wishes of the customer

The strategy

By dividing the campaign in three pillars, emphasis was laid on several aspects. The first aspect concerned the automation of the availability of the campsites. Meaning that unavailable campsites are being paused automatically and campsites with high availability will get higher bids and positions. This all with the help of using machine learning. The second aspects concerned optimizing relevance. Relevance in ad copy and dynamic landing pages were the key factors for addressing new visitors, returning visitors and existing customers. This way the user gets exactly the information he or she needs. The third, and last aspect concerned the use of predictive data. Using this data, the booking behaviour of customers can be predicted, which leads to the exact knowledge in which period people are more likely to book their vacation.

Results

The campaign was responsible for a total revenue increase of 31%, with only 2% increase in media budget, more than expected beforehand. Also, this case won a prestigious Dutch Search Award for the best project in travel industry!

Questions?

VP of Growth, Experience and Engineering

Lizzie Powell

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