This paper investigates the use of synthetic data as a viable solution to mitigate the challenge of data scarcity.

Synthetic data, generated through advanced algorithms (GAN), mirrors the statistical properties and patterns of real-world datasets, thus offering a plentiful and diverse data source. By integrating synthetic data, AI-driven platforms can enhance overcome data scarcity that could lead to improved model accuracy and effectiveness despite limited or unevenly distributed real data limitations. This solution also addresses privacy concerns by reducing dependence on actual user data while enabling continuous model training and testing across varied scenarios.

The findings demonstrate that synthetic data not only improves predictive capabilities in marketing strategies but also significantly boosts campaign performance and ROI. This study highlights the potential of synthetic data to resolve data scarcity issues, driving more efficient and responsive AI-driven PPC campaign optimizations.