How Machine Learning Helped Worten Achieve a 3x Increase in ROAS Using Data Driven Solutions to Boost Performance

“By working with Google and Incubeta and focusing on our automated capabilities, we’ve been able to improve campaign efficiency, and achieve better results – while also aligning ourselves with the strategic needs of the business.”
Ricardo Avelino
Area Coordinator, Digital Acquisition, Worten


With competition hotting up, Worten wanted to test how machine learning could help leverage their data more efficiently, drive propensity to purchase, and acquire more customers.

After a successful proof of concept (POC), the team decided to take things a step further by tackling purchase propensity in individual categories as a way to further boost efficiency. This would also allow them to create specific predictive audiences based on their campaign structure, and convert the website visitors most likely to buy.


Worten used BigQuery, machine learning, and CRMint to automate audience building in Google Ads, and create propensity models for their Sports, Computers and Home categories. The team then segmented recent website users into five types – equally distributed by volume and propensity to buy something on their next visit.

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