What we set out to test
Can a value-based auto bidding strategy complement Dynamic Search Ads to reach more valuable customers and drive profitability?
The background
Traveloka is a Southeast Asia’s lifestyle superapp that offers a broad range of products and services spanning across travel, local services, and financial services.
With the evolution of consumer behaviors and expectations, brands need to optimize their online ad strategies to better reach their audiences. Savvy brands are harnessing machine learning and automation in marketing to gain an important competitive advantage. In 2020, 93% of brands in EMEA found it valuable or critical to embed a range of marketing technology over the next few years.1
In order to reach a suitable target market for each of its large variety of products and services, Traveloka has been using Dynamic Search Ads to personalize customer experiences by providing them with the exact products or services they were searching for.
As Indonesia is currently experiencing macroeconomic recovery and growth, especially in travel, Traveloka set out to leverage its existing reach to unlock incremental value and efficiency at scale.
Traveloka decided to shift the focus of its bidding strategy from bookings to return on ad spend (ROAS). In particular, Traveloka was keen to compare the effects of Target CPA (cost-per-action), which was its existing bid strategy, and Target ROAS. Both Smart Bidding strategies use machine learning to optimize for specific business goals:
- Target CPA: Automatically sets bids to help get as many conversions as possible at the target cost-per-action you set.
- Target ROAS: Automatically sets bids to help get as much conversion value as possible at the target return on ad spend you set.
On average, advertisers who switch from Target CPA to the value-based Target ROAS bid strategy see 14% more conversion value with a similar ROAS.2 Hence, Traveloka was keen to try switching its bidding strategy.
Traveloka set out to test if Target ROAS bidding on Search ads, combined with its first-party non-customer profile data, could improve performance and unlock growth in line with the brand’s business objectives.
How we set the experiment up
To compare the effectiveness of Target ROAS bidding compared to Traveloka’s existing strategy of Target CPA bidding, the team set up a search query-based A/B test through custom experiments:
- Control group: Dynamic Search Ads with Target CPA bidding
- Test group: Dynamic Search Ads with Target ROAS bidding
The experiment ran in Indonesia for a total of four weeks. The same budgets were used across both the control and test campaigns. For this test, a conversion referred to a booking made on the Traveloka website or app.
By comparing the control and test groups’ bookings, average booking value, as well as ROAS, Traveloka could then analyze which bidding strategy would be more effective for its business objectives.
Solutions we used
What we learned
Within the experiment period, Traveloka’s test group unlocked tangible performance growth and efficiencies.
The test campaign that combined Target ROAS bidding with a first-party (non-customer profile) data strategy delivered the following findings:
This allowed Traveloka to clearly identify the value of bid-to-value automation.
Following these results, the original experiment campaign has become an important part of Traveloka’s marketing strategy.
“Through our collaboration with Google, we can further leverage our capability to fulfill the lifestyle needs and aspirations of wider consumers - and we’re really looking forward to seeing what our next experiment will bring!”
This case study is part of the Experiment with Google Ads program.
