Crawling & technical audit
How this is scored
Site crawling at real scale: what the crawler finds, how deeply it checks, whether Core Web Vitals and indexation problems are diagnosed rather than merely listed.
0 — No site crawler; the product is keyword data only.
3 — A crawler with a low page cap that reports broken links and missing tags, with no prioritisation and no rendering of JavaScript.
5 — Scheduled crawls at a stated page limit, JavaScript rendering, issue categories with severity, and Core Web Vitals pulled per template.
8 — Log-file or Search Console integration to compare what the crawler sees against what Google fetched, indexation and canonical diagnosis, structured-data validation, and issues prioritised by traffic impact rather than count.
10 — The audit is diagnostic rather than a list: crawl budget analysed, rendering differences surfaced, regressions detected between crawls with the deploy that caused them inferrable, and remediation guidance specific enough for a developer ticket.
The Content Strategist
The strongest-documented part of the product: millions of pages at up to 450 URLs per second, JavaScript rendering on Google's own engine, log-file crawl budget breakdowns, and Source Gap charts that line up what the crawler found against sitemaps, Search Console, analytics and log files — then an AI ticket writer turns findings into developer-ready tasks, with pre-production QA gates that can halt a CI/CD build when metrics dip. That closes the loop from finding to fixing and makes deploy-level attribution plausible. I hold back the last point because canonical and structured-data handling appear only as report categories without documented validation. 1 2 3 9