Szallas.hu: 243% revenue increase from Google Ads whilst lowering Cost of Sale by 6%
Learn how Hungary’s #1 accommodation booking portal, Szallas.hu, partnered with SegmentStream to solve its marketing analytics and attribution challenge and achieve better results from the online marketing budget.Request a demo
“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. ”— 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.
#1: Cross-channel marketing reporting
Szallas uses many advertising platforms to promote their hotels — 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.
#2: Google Ads campaign evaluation and optimisation
Google Ads is the main source of website traffic and revenue for Szallas. However, it is not so easy to buy and optimise Google Ads at such scale — as a leading booking company, Szallas has tens of thousands of different hotels on their website, so there is no way to define all possible keywords for the broad targeting in Google Ads.
To overcome this challenge, Szallas’s marketing team relies on keywordless dynamic search ads by automatically matching people’s searches on Google with specific hotel pages on their website.
Example of keywordless campaign
The main goal of such keywordless campaigns is to generate awareness about Szallas and drive users toward the booking in the future, not always immediately. The problem is that due to the nature of such campaigns, it didn’t bring a lot of immediate post-click conversions (hotel bookings), and Google Ads significantly limited the reach of this campaign.
To overcome this issue and get more traffic, Szallas tried to use the Enhanced CPC strategy but it did not give enough flexibility in bid auctions when competing versus giants like Booking.com and other competitors and was not really effective.
To overcome both of these challenges, Szallas’s marketing team decided to partner with SegmentStream and try its AI-driven marketing attribution and optimisation platform.
SegmentStream — AI-driven marketing attribution and optimisation platform built for advanced digital marketing teams. It helps businesses to collect and unify all marketing data, apply cross-device & cross-browser AI-driven multi-touch attribution, and send AI-insights back to advertising tools to optimise their performance in an automated way.
After implementing SegmentStream, customers are able to automate cross-channel marketing reporting, understand the true ROAS of all their traffic sources, and increase revenue across all the channels by applying AI-driven attribution insights.
SegmentStream solution architecture for Szallas.hu
Step 1: Google BigQuery marketing data collection
SegmentStream does not store any customer data on its own servers. Instead, all the data is collected and stored in the client’s own Google BigQuery data warehouse.
In order to build AI-driven multi-touch attribution, unsampled website behavioural events should be collected first. As Szallas already had Google Analytics 360 that supports native raw data export to Google BigQuery, there was no need for any additional implementation — SegmentStream simply connected to the raw GA360 data in Szallas’s BigQuery.
After that, Szallas marketers easily authenticated all additional marketing data sources in the SegmentStream admin panel to automatically import information about clicks, impressions and cost across all advertising platforms. The entire setup process didn’t take more than 30 minutes for the Szallas team.
SegmentStream admin panel with connected data sources
Step 2: Reporting & Attribution
After all the data started to flow into Szallas’s Google BigQuery, it was now possible to implement SegmentStream’s AI-driven attribution to understand the incremental value of each marketing channel and campaign.
In a nutshell, SegmentStream uses the power of machine learning to analyse complex behavioural patterns and attribute the Score to each session that shows how each traffic source moves the user toward the future conversion.
After all the data has been unified and analysed using SegmentStream’s AI-driven multi-touch attribution, everything was ready to prepare a visual Google Data Studio dashboard that shows a true picture of overall marketing performance across all the channels in a single interface.
This automated marketing dashboard saved a lot of time and effort for Szallas’s marketing team, as there was no need to manually go to each advertising platform to calculate the ROAS of each channel and campaign. Also, it helped Szallas to understand the difference in campaign performance by comparing the amount of Last-non-direct-Click conversions versus SegmentStream Score.
While some channels received very few conversions according to Last-non-direct-Click attribution, they’ve generated a lot of Scores - which means that this channel has a very high impact in terms of moving customers toward the conversion that might happen from another channel. This approach helped the Szallas team to understand how to reallocate their advertising budget between multiple channels and campaigns to increase the total amount of conversions and improve overall ROAS across all the channels.
Step 3: Automatic Google Ads optimisation by AI-driven attribution
As we mentioned earlier, Szallas.hu has tens of thousands of hotels on their website, so it is not possible to manually optimise ads by changing budget or bids. Luckily, SegmentStream has an amazing Data Destinations functionality that allows you to automatically send AI-driven attribution conversion (Score) to external advertising tools such as Google Ads, Facebook Ads, and others.
Data Destinations in SegmentStream
After Google Ads Data Destination was enabled, the current post-click conversion (Hotel Booking) was replaced with SegmentStream Score which attributes proper value to each session on the website, and not only to a single session that finished with a final conversion.
This way, instead of optimising for the post-click hotel booking right away, Google Ads was able to optimise for engaged users that will most likely convert in the near future.
Not only was the Szallas team finally able to get a unified and deduplicated cross-channel marketing reporting in a single place, but they were also able to automatically improve the performance of its key marketing channel — Google Ads.
After starting optimising by SegmentStream Score, revenue from keywordless dynamic search ads campaign increased by 242.6% whilst the cost of sale decreased by 5.8%.
Revenue dynamics after optimisation by SegmentStream Score
This result is not a surprise — awareness campaigns are rarely converting customers right away. Instead, they play a huge role in driving customers towards the conversion in the nearest future. That is why it is important not only to measure conversions that happened directly after the click but also to understand how such campaigns influence future conversions from other traffic sources such as organic, direct, and others.
So, when the conversion in Google Ads was replaced from Hotel Booking to SegmentStream Score which evaluates how each session moves the user towards the final conversion, Google Ads started to receive much more quality signals and generate much more traffic at a lower Cost of Sale.
Sure, seasonality and positive after-COVID mood also played a big role in this growth. That’s why we decided to check the dynamics of non-paid traffic. For the same period of time increase in non-paid traffic was only 81%. That clearly demonstrates the incremental impact of campaign optimisation.
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. Instead, SegmentStream’s “predictive” approach to attribution was something new as it analyses actual user behaviour to understand the incremental shift in terms of moving users to the future conversion. This 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 cross-channel marketing reporting in the Google Data Studio dashboard. After that, we started to optimise our ads according to SegmentStream’s attribution. SegmentStream’s team not only supported us during the initial implementation phase but also helped us to properly look at attribution insights and optimise campaigns accordingly. After running optimisation experiments for more than a month, we saw a very positive ROAS improvement, which means that SegmentStream’s attribution actually works and brings business results.
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
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