The background
Aritaum is a multi-brand beauty retailer that is part of the Amorepacific Beauty and Cosmetics Group, a leader in the K-beauty industry. Aritaum, which has both online and physical stores, carries more than 110 beauty product brands, including Sulwhasoo, Hera, and Laneige.
In the fast-paced beauty industry where consumption was quickly shifting online, the brand realized it had to optimize its digital marketing strategy.
The brand decided to introduce a machine-learning-driven automated bidding strategy to increase the meaningful traffic and drive online product purchases on its website.
Aritaum wanted to run an experiment to discover if a Smart Shopping strategy using maximum conversion value could effectively increase conversions in comparison to its existing enhanced cost per click (eCPC) bidding strategy.
How we set the experiment up
The brand ran a controlled pre-post experiment for 30 days in Korea using the same product feed.
- Control group: Standard Shopping Campaigns with eCPC bidding
- Test group: Smart Shopping Campaigns with Maximize conversion value bidding
To enhance performance in the test group, Aritaum optimized the feed description with product titles to enable machine learning to better understand the product. This helped to increase the ad quality. It also modified the structure of the Shopping campaigns to take into account the different ROAS for each respective brand.
After 30 days, Aritaum compared the ROAS performance of the test group against the control group.