Blended skills unlock campaign performance data.
Longtime Amazon advertiser Philips Domestic Appliances [Versuni] needed to integrate creative optimization with media performance on a large scale. This kind of operation requires deep expertise in machine learning, artificial intelligence, creative production and optimization—a tall order, but no sweat for us. So Philips DA enlisted our help, resulting in the development of an automated tool that identifies key creative elements that drive performance at scale, backed by campaign performance data.
Building on the best in machine learning and artificial intelligence.
Amazon’s robust computer vision and machine learning-powered solutions, combined with our proficiency in constructing automated workflows, meant we had everything we needed to turn Philips DA’s opportunity into reality. We began by demystifying Amazon Media Cockpit data, giving the media team access to enriched user data to assess media performance. Next, we leveraged our deep understanding of AWS APIs to extract labels, metadata and documentation. This set the foundation for a streamlined creative categorization and labelling process while also opening the possibility of integrating metadata as filters in the brand’s digital asset management (DAM) tool.
In partnership with
- Philips Domestic Appliances [Versuni]
In starting this project, optimizing creative at scale for our Amazon ads was a major challenge. Working in partnership with Media.Monks we leveraged machine learning and AI which played a pivotal role in creating a scalable, data-driven solution that can adapt and grow with our ever-changing needs.
Global Amazon Media Lead, Versuni
A custom, automated tool enables creative optimization at scale.
After laying the groundwork, we custom-built a machine learning-powered tool fully tailored and automated for Philips DA’s specific business case. Upon completion of the tool, Philips DA gained a newfound capability to assess the creative aspects of their Amazon advertisements in conjunction with media performance data in a scalable, well-structured method. This breakthrough enabled the identification of numerous opportunities for optimizing ad creatives, while eliminating the need for speculative optimization and manual data engineering work. As a result, the company gained enhanced technical, analytical, operational and financial efficiencies.
First structured analysis on ad creative elements within the organization
700+ automated extraction of ad creative attributes
200+ hours saved with 600x more efficiency through automation versus manual tagging
De-siloed alignment across data, media and content teams