for LOCOMOTIVE Agency. He has been an SEO since 2011 and was formerly an architectural glass artist. His focus areas are in SEO, machine learning, language, and user experience. jroakes locomotive.agency
▪ Capable of counterfactual reasoning in natural language ▪ Determine necessary/sufficient causes from text descriptions ▪ Capture relevant context and common sense for causal judgments ▪ Complement existing statistical causal methods ▪ Automate parts of causal analysis previously requiring human experts ▪ Enable flexible, natural language interaction for causal tasks 21 Source Causal Reasoning and Large Language Models
Built a tool called Npath, that turns GA4 sequence data into user cohorts, ideals paths, and insights. ▪ Built a tool that takes a company’s ICP information and turns it into tens of thousands of categorized keywords with competitive metrics. ▪ Formalized all competitive gaps to aggregate data based on subjects rather than keywords. ▪ Finalizing a tool to detect anomalies buried in thousands of URLs and segments of URLs.
• Word Count • Heading Structure • Image Count • Schema Markup Page Speed Insights: • Largest Contentful Paint • Cumulative Layout Shift • Interaction to Next Paint • First Contentful Paint • Time to Interactive • Speed Index • Total Blocking Time • Performance Score • First Meaningful Paint Search Engine Performance: • Clicks (from Google Search Console) • Impressions (from Google Search Console) • Click-Through Rate (CTR) • Average Position (in search results) • Ranking Keywords • Top No-Click Queries