Increasing Return on Ad Spend with Smart Search Tools and Value-Based Bidding


As the fifth-largest airline in the United States, Alaska Airlines collects many first-party data points across different repositories. The company turned to us when it needed to bring it all together and securely house it in one location while streamlining processes.


We built a marketing data warehouse using BigQuery in Google Cloud, which tied Alaska’s first-party data together across CRM, media and site analytics. Next, we created predictive lifetime value (pLTV) models using Google Cloud AutoML. Then we fed the predictive scores into the Campaign Manager Conversions API. This connection enabled us to use that data in Search Ads 360 and set up an Auction Time Bid Strategy to quickly, predictively and programmatically bid to pLTV.

Along the way, we uncovered some interesting insights about the values tied to customers’ origin and destination (O&D) airports, travel days, ages, loyalty program membership and more.


Using the advanced infrastructure and modeling has helped Alaska achieve a higher ROAS. In fact, activating the information across its Google platforms led to a 30% increase in ROAS for O&D campaigns and helped the company earn $1 more per paid search click.
"During the lull in travel, the airline built a marketing data warehouse using Google Cloud, which tied together its first-party data across CRM, media and site analytics. Alaska Airlines worked on the project with Adswerve. Machine learning helped the airline predict which media investments would deliver long-term value and better focus its marketing efforts."
Have a Similar Project You’d Like to Talk About?
Contact Us