Problem

The company was struggling to generate significant revenue from ads, and needed to find a way to increase their ad performance. They recognized the potential of AI and ML technologies, but lacked the expertise to develop and implement these projects in their ads stack.

Solution

We formed a cross-functional team consisting of ML engineers, data scientists, and ad tech experts to identify promising AI projects that could be productionized in the ads stack. We conducted extensive research and experimentation to determine which projects would have the greatest impact on ad performance.

Once we identified the most promising projects, we worked closely with the ML engineers to develop and implement them in the ads stack. We also collaborated with other teams within the company to ensure that these projects were integrated seamlessly into existing systems.

Impact

Generated billions of dollars in incremental revenue from ads
Increased click-through rates by X%
Improved targeting accuracy by X%
Reduced cost per acquisition by X%

Team

Alexandra Chen - Data Scientist
- Analyzed data to identify trends and opportunities for improvement
- Collaborated with ML engineers to develop predictive models for ad targeting
Daniel Kim - Ad Tech Expert
- Leveraged knowledge of ad tech industry to identify areas for improvement
- Collaborated with other teams within the company to integrate new AI projects into existing systems
Emily Wong - ML Engineer
- Developed and implemented AI projects in the ads stack
- Collaborated with data scientists to ensure that models were accurate and effective

Boosting Ad Performance with AI & ML