SEO, GEO, and AI visibility playbooks
Long-form guides for teams that want to be found in Google, AI search, answer engines, and LLM-assisted research. Each guide is written around buyer questions, citations, fix plans, and proof checks.
Board-ready AI visibility reporting: what to show, what to omit, and how to avoid overclaiming
A long-form guide to turning AI answer evidence into a report that executives can trust without seeing engineering vocabulary.
The AI answer content system: how to make your brand easier to mention, cite, and recommend
A detailed operating model for building pages, facts, structured data, and third-party proof that AI answer systems can use.
Before-and-after proof playbook: how to show that an AI visibility fix actually worked
A practical guide for proving impact without turning a single answer into an exaggerated claim.
Agency client service packaging: how to sell and operate AI visibility without screenshots
A very detailed service model for agencies that want recurring AI visibility revenue with measurable deliverables.
Brand facts source of truth: how to stop AI answers from repeating stale or unsupported claims
A deep guide to building the factual layer that keeps AI answers, content fixes, and proof checks grounded.
Regional AI visibility playbook: how to measure local buyer answers without global bias
A detailed playbook for brands that sell in specific countries, cities, languages, or regional categories.
API reporting for operators: how to build dashboards around AI visibility evidence
A practical operator guide for using DoneHat reporting data without losing the evidence and limitations that make it trustworthy.
Executive operating rhythm for AI visibility: weekly review, monthly reporting, quarterly strategy
A long guide for leaders who want AI visibility to become a durable business process instead of a one-off audit.
How DoneHat compares to other AI visibility and GEO providers
A direct comparison guide for teams evaluating DoneHat against broad AI platforms, SEO suites, and newer GEO tools.
DoneHat alternatives for AI visibility monitoring: how to compare the real options
A practical alternatives guide that separates AI visibility tools, SEO suites, analytics platforms, and broad enterprise AI vendors.
AI visibility tool with API for custom integrations: what operators should evaluate
A technical buyer guide for teams that need AI visibility evidence inside dashboards, workflows, and reporting systems.
AI visibility platforms for teams needing transparent pricing and proof
A procurement-focused guide for buyers comparing AI visibility tools, price posture, plan limits, and evidence quality.
Compare AI visibility tools for multilingual SEO and regional GEO
A guide for teams measuring AI-search presence across languages, regions, local competitors, and country-specific sources.
AI visibility proof and review signals: where answer engines find trust
A source-quality guide for teams deciding whether to pursue G2, Capterra, YouTube, partner pages, customer stories, or other third-party proof.
ChatGPT brand visibility guide: how to make your company easier to mention accurately
A practical guide to improving how ChatGPT-style answers describe your brand without relying on hacks or unsupported ranking claims.
Perplexity AI visibility and citation guide for B2B software brands
How to build pages that are easier for answer engines with visible citations and source panels to find, quote, and trust.
AI share of voice measurement: how to report brand visibility without overclaiming
A measurement guide for comparing brand mentions, competitors, confidence ranges, and prompt groups in AI answers.
LLM citation readiness checklist: make pages easier for AI answers to quote and trust
A page-level checklist for writing content that AI answer systems can retrieve, summarize, cite, and verify.
AI crawler and robots.txt playbook for brands that want answer visibility
How to think about AI crawler access, robots.txt, sitemap hygiene, and abuse controls without confusing crawl access with guaranteed citations.
SEO vs GEO vs AEO: a practical guide for teams building AI search visibility
A plain-language guide to how classic SEO, generative engine optimization, and answer engine optimization fit together.
How to check your AI visibility by hand with 20–50 buyer questions
A manual method any team can run in a day or two: choose buyer questions by intent, ask each AI engine three times, record what you see, and turn the tally into a rate with an honest range.
GEO vs SEO: what changes and what doesn't
A plain explanation of generative engine optimization for teams that already do SEO: what carries over, what is new, what AI answers tend to cite, and what to measure.
AI visibility tools for beginners under €50 a month
An honest look at entry-level AI visibility tools — Otterly.AI, Peec AI, Semrush and DoneHat — described from their own public pages, with the dates we read them and when you do not need a tool at all.
Want the product workflow instead?
Start with the docs for step-by-step setup, or run a public audit for a real brand.