Szallas.hu success story: Solving marketing attribution for the leading booking portal

About Szallas.hu:

Szallas.hu (szallas.hu) is Hungary’s #1 accommodation booking portal, annually delivering bookings in value of €90 million for its accommodation partners. With 15.000 contracted direct partners, available in 8 languages, and offices in Budapest, Zagreb, Warsaw, Cluj-Napoca, the Szallas Group is rapidly growing in Central Eastern Europe.

The Szallas.hu Group websites have more than 1 million registered users and are visited by more than 2 million users every month. It also helps customers find suitable accommodation with over 1.2 million independent and valid customer reviews.

The challenge:

Szallas uses many advertising platforms: Google Ads, Microsoft Ads, Facebook Ads, Criteo, RTB House, and others. 

With so many different advertising sources there was no single place to analyse cross-channel marketing performance. To understand the ROAS and CPA of different campaigns, Szallas’s marketers had to manually go into each ad platform and check the cost, revenue, and other key metrics to understand the performance of each channel and campaign.

Not only did it take a lot of time and effort, but it was also difficult to understand the real impact of each marketing channel and campaign. Attribution models of Facebook, Google Ads, and other ad platforms tend to give much more credit to themselves as there is no deduplication for post-click and post-view. Because of this, if you combine attributed conversions that you see in all your advertising platforms, you would see many more conversions than you’ve actually had.

At the same time, while Google Analytics 360 showed the true amount of total conversions, it was difficult to understand how many conversions each marketing channel and campaign brought. Of course, Google Analytics multi-touch attribution models can distribute the value from the conversion between multiple user sessions according to some logic. However, the main problem regards interrupted customer journeys — nowadays people use multiple browsers and devices with different cookies, so there is no way to stitch a full customer journey together. This also happens due to technical limitations such as ITP and private browsing that remove or limit cookies.

Because of this, all existing attribution models tend to undervalue upper-funnel channels such as social or display campaigns while giving more credit to lower-funnel campaigns (i.e. retargeting). While Szallas’s team understood the value of upper-funnel awareness campaigns, it was impossible to measure the true impact of such campaigns in hard numbers. 

To overcome this challenge, Szallas’s marketing team decided to partner with SegmentStream and try its AI-driven measurement and optimization platform.  

Solution overview:

SegmentStream is an advanced AI-powered Marketing Mix Optimization Platform that helps marketing teams understand the incremental ROI of each marketing channel & campaign on their total revenue, and make effective budget allocation decisions.

To achieve this, SegmentStream combines the power of Machine Learning & 1st party data to understand how every marketing activity influences the overall revenue, even if direct conversion tracking and attribution are not possible due to modern-day cookie-tracking restrictions and privacy regulations. 

By implementing SegmentStream, the Szallas team was finally able to get unified and deduplicated cross-channel marketing reporting in a single place, and understand the true revenue impact of their digital marketing traffic sources. 

Customer testimonial:

Before partnering with SegmentStream, we experimented with many different attribution models but all of them were not able to show the real impact of our upper-funnel marketing activities. Instead, they’ve always attributed much more credit to lower-funnel channels and campaigns. 

SegmentStream’s approach to marketing attribution was very different from what we have tried before, as it was not dependent on cookies like all other “retrospective” attribution models out there. Thei approach to evaluating marketing performance sounded pretty interesting, so we decided to give it a shot. 

We started with the unification of all our marketing data in Google BigQuery, and visualisation of the cross-channel marketing reporting dashboard. After that, we started to optimise our advertising according to SegmentStream insights. 

SegmentStream’s team not only supported us during the initial implementation phase but also helped us to properly look at attribution data and make better decisions.

We are very happy with our choice, and looking forward to expanding our collaboration by implementing SegmentStream to other websites in Szallas.hu Group later this year.

— Laszlo Benes, Head of Performance Marketing at Szallas.hu