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Case Study

Google Search Advertising Product Management | SproutVest

Note on this page. This is operating experience from Erick’s full-time role at Google, not a SproutVest client engagement. Erick was a Google employee, Senior Product Manager in Search Advertising, from September 2021 to October 2022. It appears here because the judgment SproutVest sells was built doing this work.

At a glance

Company: Google Advertising
Role: Senior Product Manager, Search Advertising
Industry: Digital Advertising & AI Technology
Tenure: Full-time, 2021–2022
Scope: ML-powered ads insights products, AI integration, data analytics
Headline result: $1.22B in annualized incremental revenue

Context

Google’s advertising organization runs a set of internal analytics products that tell its global sales teams which search trends matter and where advertiser budgets are underperforming. Two of the most important, Search Benchmarks Automated Insights (SBAI) and Search Trends & Benchmarks (STB), were mid-flight when the product manager leading them left the company. Erick joined Search Advertising and took over the portfolio, with a mandate to carry both programs through approval and deployment and extend them with AI capabilities.

The challenge

Stepping into someone else’s roadmap at a critical phase is its own problem, but the structural challenges were larger. The initiatives spanned three divisions, Ads Insights, Ads Planning & PARC, and Connect Sales, each with its own priorities and review gates. Every revenue projection had to survive testing, validation, and approval by internal business councils before anything shipped. And the technical bar was high: the work meant integrating machine learning models into established ad-tech systems, then embedding Google’s internal conversational AI, later launched publicly as Bard, into the Advertiser CRM so that sales teams could get trend predictions and advertiser insights without leaving their workflow.

What Erick did

Erick took product leadership of SBAI first, rebuilding stakeholder alignment across the three divisions and securing the UX, PRD, and experimental design approvals the program had stalled on. In parallel he modernized STB, streamlining how search performance data was extracted, modeled, and visualized for sales teams worldwide.

To satisfy the business councils, he built machine learning forecasts that validated projected revenue against real advertising trends in global ad markets, turning contested projections into approved business cases. With the core programs moving, he led the integration of Google’s internal conversational AI, later launched publicly as Bard, into the Advertiser CRM, training the system to surface trend analysis and advertiser behavior predictions directly inside the sales workflow. A final initiative, Search Trends Highlights, was approved and launched on the strength of the same delivery model.

Results

Over the tenure, every program in the portfolio reached full deployment, and the AI integration shipped inside the Advertiser CRM. The validated revenue impact:

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