Which scraping backbone should power your SEO data pipeline? A production teardown of Bright Data, Apify, and ScraperAPI across SERP collection, competitor crawling, and structured extraction — with code, failure modes, and a cost-per-record model.
A production programmatic SEO pipeline in n8n + Python: enrichment that creates uniqueness, a quality gate that refuses thin pages, per-page JSON-LD, and an indexing controller that lifted indexation from 30% to 88%.
Treat a competitor’s programmatic SEO site as a black box and take it apart with Python: map the URL footprint from sitemaps, fingerprint the template, reconstruct the internal link graph, and estimate what actually ranks.
Spreadsheets break past a few hundred URLs. Use OpenAI embeddings, Search Console overlap, and an n8n workflow to flag cannibalization across thousands of pages, score severity, and pre-classify each pair as merge, differentiate, or canonical.
A working playbook for getting cited by ChatGPT, Perplexity, and Google AI Overviews — structural patterns that win, plus a five-job automation stack you can ship this week.
Stop losing rankings silently. A Python + n8n pipeline that pulls 16 months of GSC data, scores every URL for decay, and files refresh tickets weekly with a closed-loop verification step.
A teardown of an agentic SEO auditor built on Claude Code that crawls, diffs against history, and files engineering-ready GitHub issues — including architecture, the agent prompt that worked, and eight weeks of real ticket data.
A production-grade n8n + Python workflow that ingests raw server logs, verifies Googlebot via reverse DNS, computes the four metrics that matter, and posts a daily Slack digest.
A practitioner head-to-head on API depth, cost-at-scale, debuggability and AI-SEO fit — plus a working n8n flow for daily query intent clustering.
A Python pipeline that combines Google Search Console with Common Crawl to refresh a competitor content gap report weekly, with priority scoring and the failure modes you will hit in production.