With Apple and Google contributing to make changes via their browsers and operating systems, and with the evolving privacy regulatory landscape, it’s important to acknowledge that digital advertising must become less reliant on individual third party data, and be more privacy safe. Personalization in marketing is the best possible experience for people and business.
In this talk we would like to share the challenges unique to conversion prediction, practical lessons, the evolving privacy landscape, on how it impacts the advertising business in general, general strategies of making the data usage privacy safe, and show how personalization can still remain effective as the industry evolves to become less reliant on the individual third party data, through innovations in modeling and data handling techniques.
Aayush Mudgal is a Senior Machine Learning Engineer at Pinterest, currently leading the efforts around Privacy Aware Conversion Modeling. He has a successful track record of starting and executing 0 to 1 projects, including conversion optimization, video ads ranking, landing page optimization, and evolving the ads ranking from GBDT to DNN stack. His expertise is in large-scale recommendation systems, personalization, and ads marketplaces. Before entering the industry, Aayush conducted research on intelligent tutoring systems, developing data-driven feedback to aid students in learning computer programming. He holds a Master's in Computer Science from Columbia University and a Bachelor of Technology in Computer Science from Indian Institute of Technology Kanpur.