GDPR, CCPA, and the Evolution of Privacy-Centric Advertising Analytics by Varun Chivukula
The digital advertising landscape has experienced a seismic shift over the past two decades, revolutionizing how businesses connect with consumers. The ability to target ads in a personalized way has enabled companies to reach global markets almost instantly, fueling the rapid growth of industries like e-commerce. However, as ad platforms have grown more sophisticated, so too have concerns around data privacy. Striking the delicate balance between personalization and privacy has become one of the industry’s most pressing challenges — and it’s a challenge that Varun Chivukula has dedicated his career to solving.
Varun’s journey into privacy-enhancing technologies (PETs) began at Meta, where he quickly rose to prominence by leading marketing measurement efforts with some of the company’s largest advertisers. His most groundbreaking work came through pioneering industry-wide pilots of PETs, such as multiparty computation and federated learning, to address the growing need for privacy-compliant data practices. “We wanted to prove that it was possible to optimize ad performance without compromising user privacy,” Varun explains. He played a pivotal role in demonstrating the viability of running large-scale user-level randomized control trials without the exchange of personally identifiable information (PII) between advertisers and ad platforms.
One of Varun’s standout contributions was designing a method to calculate match rates while using PETs to perform computations across two parties. This innovation gave advertisers and ad platforms a way to evaluate the representativeness of their computations, uncovering critical insights around effectiveness of PETs. “For example, one of Meta’s largest advertisers initially believed their match rate was around 60%, but we discovered the true rate was closer to 10%,” Varun recalls. This revelation spurred efforts to expand representativeness, ultimately boosting the match rate to over 70% and driving $500 million in incremental revenue for Meta.
He also collaborated with Amazon to help design AWS cleanrooms, incorporating privacy-enhancing technologies into a production product to scale the prototypes his team had developed. These efforts have set the stage for broader adoption of PETs across the digital advertising ecosystem, ensuring that the $700 billion industry can continue to thrive in an era of increasing privacy regulations.
The impact of Varun’s innovations has been profound. By reducing reliance on PII while maintaining ad personalization, his work has not only enhanced consumer privacy but also protected ad platforms from regulatory risks associated with laws like GDPR and CCPA. Additionally, the implementation of these privacy-first solutions has contributed to a 70% improvement in match rates, reducing operational blind spots and empowering advertisers with more accurate data.
Yet, these achievements did not come without hurdles. One of the biggest challenges Varun faced was, understanding the representativeness of data in closed-system PET environments. Without accurate match rates, it was nearly impossible to gauge the effectiveness of the system or make meaningful improvements. “Designing a method to calculate match rates while ensuring privacy of a closed system was retained was a very tricky challenge” he says.
Varun’s insights into the future of digital advertising are both hopeful and cautionary. “Privacy-enhancing technologies offer a path forward, where ad platforms can retain the benefits of personalized targeting and measurement without needing to ingest user identifiers,” he notes. As privacy legislation tightens and user expectations evolve, he envisions a landscape where AI-driven cybersecurity models and predictive threat detection become integral to the advertising ecosystem.
His published research underscores these insights, including works like “Use of Multiparty Computation for Measurement of Ad Performance Without Exchange of Personally Identifiable Information” and “Standardizing Data Formats for Fuel Dispenser and ATG Integration.” These papers have not only contributed to academic discourse but also provided practical frameworks for real-world applications.
Varun Chivukula’s contributions are more than technical achievements; they represent a fundamental shift in how privacy and performance can coexist in digital advertising. As the industry moves towards a future where privacy takes center stage, Varun’s work stands out, guiding the path towards a more secure and user-respecting digital economy.
