What does the first audit actually inspect?

The opening audit checks the public marketing surface across on-page SEO, technical health, performance, content depth, GEO readiness, and authority signals.

Is the workspace public?

No. Public marketing pages are indexable, but /workspace/* is intentionally blocked from indexing so company-specific diagnostics stay private.

Why combine SEO and GEO?

Traditional ranking still matters, but AI answer engines increasingly choose a small set of citable sources. The same team now needs both search visibility and citation readiness.

What does Full Stack CMO do?

Full Stack CMO audits SEO, GEO, authority, and content depth from one workspace, then turns the highest-impact findings into an execution plan your team can act on.

How is GEO different from SEO?

SEO optimizes for search engine rankings. GEO optimizes for AI answer engines like ChatGPT, Perplexity, and Gemini that need citable, evidence-rich content to reference your brand in generated responses.

Marketing operating system

Understand your market. Fix what matters. Prove it's working.

Full Stack CMO scans your website, tracks your visibility across search and AI, and gives you a weekly action plan with real fixes, content recommendations, and progress proof.

First audit in 30 seconds, with no login required.
Weekly priorities across visibility, content, competitive movement, and digital fixes.
Action-oriented output with issue queues, exports, and proof-ready reporting.
A growing content workspace for drafting, scheduling, and publishing what the market needs next.

Run the first audit Browse the resource library

What the audit covers

On-page

Titles, canonicals, schema, and metadata

The audit checks the crawl layer that search engines and answer engines need before content can perform.

Performance

Speed, bundle weight, and delivery

We look for page-weight waste, caching gaps, and UX bottlenecks that undermine both visibility and conversion quality.

Content

Intent coverage and internal links

Thin landing pages, missing supporting pages, and weak internal linking usually block growth before advanced tactics matter.

GEO

Answer-first structure and evidence density

The public pages need sections, facts, and assets that an AI system can quote without guessing what you meant.

Authority

Category footprint and competitor context

The workspace compares what your category leaders publish so you can see where trust and discoverability are missing.

Execution

Priority queues and next actions

The goal is not just a score. The goal is a visible sequence of fixes your team can actually ship.

Why the content score slips first on small sites

Most B2B sites do not lose discoverability because of one missing tag. They lose it because the public surface is too narrow: a homepage, a pricing page, and a few feature descriptions that never develop into a content system. Search engines need enough page depth to understand the category, and answer engines need sections with enough evidence to quote without guessing. That is why this site now publishes not only a product page, but also operational guides, comparison pages, and a named methodology page.

2.5s Google and web.dev still treat LCP at or below 2.5 seconds as the baseline threshold for good loading.

40% The Princeton GEO study reported visibility lifts of up to roughly 40% when content became easier to cite.

150-200w Evidence density works best when named facts, sources, or dated claims appear every 150 to 200 words.

Working rule: content quality for SEO and GEO is not just “more copy.” It is better structure, clearer intent, stronger internal links, and more named evidence per page.

Resource library for SEO + GEO operators

The public resource library exists to raise the informational surface area of the site. It gives search engines more relevant URLs to crawl and gives buying committees more ways to understand the operating model before they enter a private workspace.

Library

SEO + GEO resource library

Collection page for the public guides, comparison pages, and planning assets behind the workspace.

Checklist

SEO + GEO audit checklist

Field guide for crawlability, content depth, structured data, measurement, and answer-engine readiness.

GEO

How to write pages AI systems can cite

Practical copy guidance for answer-first intros, standalone sections, tables, and named evidence.

Framework

Revenue content coverage map

Original planning asset that maps awareness, consideration, decision, and retention pages to buyer questions.

How the public surface now supports discoverability

Page	Purpose	What search engines can extract
Home	Category page for the SEO + GEO audit workspace	Primary positioning, product scope, internal links, and crawlable summary content
How it works	Explains the audit-to-execution flow	Three-step workflow, outputs, and operational expectations
Methodology	Named evidence asset for SEO and GEO scoring	Framework, scoring axes, source base, and recurring measurement model
Pricing	Clarifies Free, Pro, and Max plan logic	Plan structure, unlock path, and capability progression
FAQ	Answer-first coverage of buyer questions	Direct answers, FAQ schema, and trust-building details
Resources	Hub for public guides and comparison pages	Indexable content cluster with internal links to deeper intent pages
Audit checklist	Informational guide for recurring audit work	Operational checklist, source-backed evidence, and weekly review model
AI citation guide	Practical GEO writing page	Answer-first content rules, evidence patterns, and extraction-friendly structure
Coverage map	Original framework asset	Funnel-stage planning model, page-type coverage, and content-gap diagnosis

Important: `/workspace/*` remains intentionally private. It is blocked in `robots.txt` and also tagged with `X-Robots-Tag: noindex` so live diagnostics do not become indexable clutter.

Source base behind the public content model

The resource layer is grounded in official search documentation and the published GEO research base. These sources shape the content rules used across the site: clean crawl controls, visible metadata, structured data, performance thresholds, and answer-first sections with named evidence.