Personalized Campaign Emails
AI-Driven voter behavior analysis and personalized campaign strategies
During my internship at the Office of Palo Alto Councilmember Greg Tanaka, I worked on analyzing voter data from public social media, HubSpot, and voter profiles to identify behavioral trends within a California congressional district. Using this data, our team developed predictive models to anticipate voting behavior, helping the campaign make more informed strategic decisions.
As part of a team, we utilized advanced Large Language Models (LLMs) to generate personalized campaign emails tailored to voters’ individual concerns and preferences. This AI-driven approach significantly improved campaign efficiency and demonstrated the power of personalized communication in political outreach. The results were compiled into a paper, where we compared the impact of AI-powered communication with traditional methods like lawn signs, highlighting the effectiveness of data-driven strategies in modern political campaigns.
