The Work
A global SEO program lives or dies on its data. For a decade I've run the measurement side of Lenovo's organic channel (Tableau dashboards, SQL, large-dataset analysis, and marketing performance analytics across 30+ countries) and used it to drive the strategic investment decisions that allocate budget and people across markets. Insight-to-action reporting means the analysis ends in a decision, not a slide.
The same discipline shows up at a different scale in my independent work: the 4ort trend engine continuously processes the full GDELT global-news firehose into a ~313GB Postgres-backed knowledge graph, measuring worldwide trending topics in real time and minting new entities within 15 minutes of them appearing in world news. That's data modeling as living infrastructure: ingest, model, surface, act.
Increasingly, the consumer of marketing data isn't a human reading a dashboard; it's an AI agent surfacing the insight directly. The OpenClaw agent I'm building for Lenovo's worldwide eCommerce marketing team does exactly that: surfaces data and reporting insights on demand, no dashboard archaeology required.
Capabilities
- Performance analytics: marketing and SEO measurement frameworks tied to revenue and ROI
- Dashboarding & visualization: Tableau dashboards built for decisions, not decoration
- Large-dataset analysis: SQL and Python across datasets from search consoles to global news firehoses
- Forecasting for investment: modeling organic performance to guide resource allocation across 30+ markets
- Data pipeline engineering: real-time ingest and modeling infrastructure (Postgres, Redis, Elasticsearch)
- AI-surfaced insights: agents that put the answer in front of the stakeholder instead of a report