ai search

A practical framework for measuring AI-search visibility with fixed prompts, repeated tests, separate metrics, retained evidence, and honest reporting.

IndexNow works best when CMS workflows report updates, redirects and removals as well as new pages. Here is how to cover the full content lifecycle.

Google’s AI Search control creates a measurable publishing choice. Test visibility, traffic and leads before changing the setting across your site.

AI-assisted shopping puts more pressure on ecommerce catalog data, feeds, schema, prices, availability, and return-policy governance.

llms.txt can help AI tools read the right parts of a site, but only if it is curated, tested, and maintained like a CMS output.

Google Search is starting to book and call local businesses, which makes hours, service areas, phone routing, and landing-page accuracy part of day-to-day operations.

Google’s AI Overviews are becoming a governance problem as courts and UK regulators press on false summaries, source control, attribution, and authoritative sources.

Wrangler now manages AI Search namespaces, making tenant isolation, bindings, chunking, path filters, and website ingestion part of operational design.

AI shopping depends on clean product data. Here is how ecommerce teams should govern prices, variants, returns, shipping, and AI-generated titles.

Want ChatGPT visibility without opening every door? Align robots.txt, indexing, WAF rules, canonicals and measurement around a clear policy.