The full operational machinery of how a creator platform manages its portfolio: segmentation criteria, vertical-specific thresholds, portfolio ratios, acquisitions bandwidth, incentive program design for partner-facing teams, OKR governance, headcount planning, and management model design for complex portfolio structures. Built and operated at scale across multiple APAC markets.
The commercial brand partnership model, from design to launch to scaling across markets. Commercial commitment ratio logic, package tier structure, agency contracting, market-specific failure modes. Scaled Brand Deals from 2 pilot markets to 30K+ deals across 8 APAC markets. Meaningful ad revenue generated.
Creator supply vs brand demand sequencing. When to lead with creator supply. When monetization proof needs to precede supply growth. What the flywheel activation looks like and what stalls it. Supply-first failure modes and the intervention design that gets a stalled marketplace moving again.
GTM design for new product feature rollouts across creator and partner ecosystems. Market sequencing, partner readiness assessment, creator adoption playbook, feedback loop design. Five years of this at YouTube, across multiple feature launches across APAC.
Which agencies in each APAC market can actually close commercial deals vs which can only source creators. India's fragmentation, Japan's end-to-end alignment, Indonesia's media-selling gap, Korea's rate premium. Know the difference before contracting, not after.
Designed and launched programs across multiple verticals and use cases: creator acquisition and retention programs, market opportunity sizing, feature rollout GTM, and product feedback systems. Each program came with OKRs designed from scratch, governance processes, and scoring adapted as the program learned. The work spans the full range of what a creator platform needs to build, not a single program type.
Before YouTube, I spent three years in B2B SaaS GTM across LinkedIn and Cloudflare: territory planning, quota-setting, account segmentation and scoring, channel vs direct trade-off analysis, and predictive churn modelling. The structural GTM problems SaaS companies face in APAC are ones I've worked on from the inside, not just diagnosed from the outside: ICP clarity, commercial structure, pipeline conversion.
Designed and scaled YouTube's creator service model across multiple APAC markets: portfolio segmentation, vertical criteria, acquisitions model, incentive program design, OKR governance. Scaled Brand Deals from 2 pilot markets to 30K+ deals across 8 markets. Built the Public Figures vertical in India from scratch. Designed vertical-specific programs across Podcast and Music. Led APAC's Voice of the Market process, synthesising creator and partner product feedback into prioritised requests for global engineering teams. Ran GTM for feature launches across priority markets. Each program came with its own OKR, designed, tracked, and adapted based on learnings.
Built account prioritisation and territory coverage model for APAC sales: scoring, segmentation, channel vs direct trade-off analysis. Partnered with CS to build predictive churn models that surfaced at-risk accounts before renewal conversations.
Territory planning and quota-setting for APAC sales. Competitive intelligence infrastructure for Learning and Talent Solutions across the region.
Strategy engagements for PE and corporate clients across ASEAN: post-merger integration, market entry, due diligence, and financial modelling across TMT, pharma, and financial services.
If the problem isn't what you think it is, I'll say that directly. If the fix you're proposing won't work, I'll explain why. The point of an engagement is not to validate your current direction. It's to surface what's actually breaking and build the system to fix it.
Every missing data point is flagged explicitly with what can't be diagnosed without it. A confident-looking diagnosis built on estimated numbers is worse than a diagnosis that names its gaps and tells you exactly what to go get.
Every deliverable goes through a specific APAC review pass: does this diagnosis map to how that market actually behaves? Korean creator rate dynamics, Japanese agency incentive alignment, Indonesian media-selling gaps. These aren't context. They're the diagnosis.
AI handles the research synthesis, data structuring, and first-draft analysis. The APAC market judgment, the diagnosis, the recommendation, the "this won't work here and here's why": that stays mine. The combination is what makes 5-week work possible in 2 weeks.
If you already know what you need, email. If you want a read on what's actually breaking before we talk, take the diagnostic.
Take the diagnostic →Or email directly.