B2B SaaS SEO & Content Strategist β technical SEO, AI search visibility (GEO), and Python automation
I help B2B SaaS teams turn search data into pipeline. I build Python and SQL tooling that automates the tedious half of technical SEO, and I research how AI search engines decide which brands get mentioned β and which get cited.
I am scoring how ChatGPT, Perplexity and Google AI Overviews treat B2B SaaS brands. In the early CRM & Sales sample: 103 AI answers scored, 89 brand mentions, but only 20 owned-domain citations. Brands are being described by AI without being credited as the source.
| Project | What it does | Stack |
|---|---|---|
| AI-Visibility-Research | Benchmark dashboard: are SaaS brands mentioned and cited in AI answers? | Data analysis, HTML |
| seo-automation-toolkit | CLI tools for crawl, Core Web Vitals, indexation, on-page and content-gap audits | Python |
| off-page-seo-toolkit | Guest-post finder, broken-link finder, competitor backlink footprint, outreach automation | Python |
| seo-sql-duplicated-content | DuckDB + GSC BigQuery workflow to catch cannibalization on large sites | SQL, DuckDB |
| portfolio | Case studies and data-driven SEO results | HTML |
| ml-in-banking-and-insurance | Risk-prediction models applied to finance and insurance | Python, scikit-learn |
SEO Google Search Console Β· GA4 Β· Screaming Frog Β· Ahrefs Β· Semrush Β· Core Web Vitals
Data Python Β· pandas Β· SQL Β· DuckDB Β· Jupyter Β· scikit-learn
B2B SaaS SEO, GEO / AI-search visibility, and content strategy engagements.