Better clicks, more bookings

More than 660,000 guests book more than 4.5 million overnight accommodations per year via the websites of Belvilla, one of the largest players in holiday accommodations in Europa. Full service provider, Belvilla, is part of @Leisure, which also encompasses brands like Casamundo and Eurorelais. Via the Belvilla, VillaXL, TopicTravel, Aan Zee and Ardennes Relais platforms, the organisation brings lessors, lessees and partner organisations together to find the perfect match between the holidaymakers and the 27,000 holiday accommodations in 24 countries. The company won the Zoover Award ‘Populairste Aanbieder Vakantiehuizen’ [the most popular holiday accommodation provider] several times.

The situation
No insight into the ultimate conversion results for marketing campaigns.

The solution
The use of self-service data blending to link online data to transaction- and product details.

Product improvement and higher returns on marketing campaigns thanks to insight into the campaign results.

The lessor and lessee are satisfied

The online platforms of Belvilla undergo continuous development to provide the best services to guests and lessors of accommodations. ‘We earn our money as intermediary between the lessor and lessee and are always looking for ways to further optimise our processes to keep both parties as satisfied as possible’, explains Roel Wessels, Head of Data Analytics. ‘The smart analysis of data that we have to our disposal, is an important tool in this mission. However, whether the data science efforts are a success or a failure, depends on the appropriate business questions.’

Valuable clients

A great example of such a use case developed in the Marketing department, where they work day in and day out on promoting the holiday accommodations online with the right target group. The department runs campaigns for the various Belvilla websites across a broad range of online channels. ‘We consider it very important to achieve maximum results with the available marketing budget’, explains Robin Telgenhof, Marketing Web Analyst. ‘All campaigns, as well as the behaviour of website visitors, are analysed in detail. In addition, we perform benchmark comparisons between the different brands. However, we had difficulty determining which characteristics of the offered accommodation had the greatest impact on the click ratio and value of a booking.’

‘We earn our money by connecting the lessor and lessee and are always looking for ways to further optimise this process so we can offer both parties an amazing experience’, Roel Wessels, Head of Data Analytics

No simple task

‘Merely looking at the number of clicks did not cut it for us. We want to be able to trace a booking back to a click and to the characteristics of the holiday accommodation in the advertisement. With this knowledge, we can improve our offer and the campaign returns’, explains Robin. However, for this analysis, we first had to link data from Google Analytics to the booking details and product attributes. This proved to be no simple task. Robin: ‘The analysis tools that we were using weren’t capable of handling the volumes of data that we wanted to integrate and analyse.’

Data blending

Belvilla deliberately chose to refrain from copying the data from Google Analytics to the existing data warehouse, and instead, gave the marketers a tool with which they could independently link online data to the data in the data warehouse. This form of data integration is also known as data blending. A proof of concept was executed, with consultants from Kadenza, using Alteryx software.

Robin: ‘During this proof of concept, we combined e-commerce data from Google Analytics with product information from our data warehouse. Alteryx made it easy to link all the data and perform the necessary calculations. We then visualised the results in a dashboard, using Tableau software. This way, we ended up with the best of both worlds.’ The dashboards provided the precise insights that were sought. ‘Now, we not only see which online statements effectively resulted in a booking, but we also see, for instance, how a holiday accommodation’s rating influences booking behaviour’, says Robin.

‘By relating the characteristics of the offered holiday accommodations to the actual revenue, we can improve our offer along with campaign returns’ Robin Telgenhof, Marketing Web Analyst

Self-Service Analytics

The proof of concept has also demonstrated that a product like Alteryx enables users to combine and prepare data independently, quite well, without the need for in-depth IT knowledge. Robin: ‘The outcome of the proof of concept was an initial minimal viable product for us. We see many more possibilities for better insight into the customer journey. The journey is becoming more and more complicated because of the role of social media and clients who switch between various devices. This makes it increasingly important for us, as marketers, to combine and analyse data in a smart way, to ensure that the contribution of each step in the customer journey is accounted for in our revenue calculation.’