How to prune content using conversion data, not traffic alone: build a URL inventory, apply a keep, improve, merge, noindex or remove matrix, redirect safely and measure the impact.
How to build a revenue keyword set: collect keywords from conversion data, filter for buying intent, score by revenue value and winnability, group by page and keep the top 100.
Search coverage measures the share of your revenue keywords where you rank in the top 3. Here is how to define it, build the keyword set, measure it, model revenue and improve it.
How to build schema markup as one connected graph for AI search: identity, people, offerings, content, industry types such as MedicalEntity, and FAQ, with a JSON LD example and a 90 day plan.
A step by step playbook to fix wrong or outdated facts about your brand in ChatGPT, Gemini, Perplexity and Google AI Overviews: triage, diagnose the source, correct it, report and verify.
How to map the sources ChatGPT, Gemini, Perplexity and AI Overviews cite in your category, find the gaps where only competitors appear, and prioritise where to work first.
AI answers change on every run, so single checks mean little. Here is a sampling method, sample size maths and scoring sheet for measuring LLM mentions per 100 queries reliably.
How to write a brand fact sheet that ChatGPT, Gemini and Perplexity repeat correctly: what to include, seven writing rules, a template, where to publish it and a monthly accuracy test.
A practical guide to building a brand entity Google and AI tools recognise: entity home page, Organization markup with sameAs, profile consistency, Wikidata and knowledge panels.
