Initiative 1: GLS Lead Volume & Optimization Framework
In this project, I led the design of a centralized lead volume and quality settings framework, enabling advertisers to explicitly manage the trade-off between lead quantity and lead quality.
Strategic Move: I consolidated previously fragmented controls into a centralized panel, clearly communicating the impact of "Maximize Leads" vs. "Customizable" modes.
Outcome: By aligning advertiser intent with system defaults, the framework improves lead relevance and advertiser retention while supporting scalable optimization across the global platform. (Dec 2025)
Initiative 2: AI-Powered Conversion Intelligence
This project introduced an AI-powered call conversion enhancement, shifting call measurement from duration-based signals to a more accurate assessment of lead quality.
Strategic Move: Leveraging call recordings and intelligent lead classification, I architected a system that allows advertisers to optimize for lead quality rather than just call volume.
Outcome: The solution introduces call recording–based conversion actions as a progressive optimization path, driving higher-quality outcomes for advertisers without call tracking while seamlessly preserving existing advertiser workflows. (Aug 2025)
Staff-Level Synthesis: Leading Through System Complexity
The work across both Oracle and Google represents a critical evolution in my approach to Experience Architecture.
While my work at Oracle was defined by System Abstraction—building a flexible, white-labeled framework to support thousands of unique brand identities—my work within Google Ads focused on System Convergence. Integrating Google Local Services (GLS) into the Google Ads Front End (GAFE) required navigating the profound tension between a niche, high-intent lead model and a generalized, global-scale advertising ecosystem.
While my work at Oracle was defined by System Abstraction—building a flexible, white-labeled framework to support thousands of unique brand identities—my work within Google Ads focused on System Convergence. Integrating Google Local Services (GLS) into the Google Ads Front End (GAFE) required navigating the profound tension between a niche, high-intent lead model and a generalized, global-scale advertising ecosystem.
To insulate the user from underlying technical complexity while delivering a performant, scalable, and human-centered reality.