Entity clarity · Evidence · Discovery

Make your expertise easy to identify, verify, and cite.

I connect your entity, services, evidence, expert content, and public profiles into one coherent source system. The goal is durable visibility in search and AI answers—not fabricated mentions, bulk directory submissions, or a promise that a platform will cite you.

Map the citation gaps Direct answer

Direct answer

A citation starts with a source worth retrieving.

GEO and SEO citation work makes a business easier for people, search engines, and answer systems to resolve and verify. I establish the canonical entity, align names and claims, connect first-party proof, implement accurate structured data, create useful source pages, and improve legitimate public records. Technical markup can clarify relationships, but it cannot manufacture authority or guarantee inclusion. The strongest system pairs a crawlable website with original expertise, consistent external profiles, and claims that independent sources can support.

Your public knowledge graph

One canonical entity. Every useful relationship made explicit.

The visible page and the structured data should tell the same story. I map the entity first, then connect services, expertise, proof, location, and authoritative profiles through stable identifiers and real links.

Canonical entity David Dacruz Person · daviddacruz.dev/#person

Public records

LinkedIn Professional profile
GitHub Developer profile
DEV Author profile
Stack Overflow Technical profile
Ethereum Stack Exchange Technical profile
Wikimedia Commons Published profile
Instagram Published profile
Project enquiries Canonical contact

The graph is not a collection of keywords. It is a maintained record of real entities, relationships, claims, and supporting URLs.

Related work

One technical problem often crosses several systems.

The capabilities page shows the other ways I can help and the case studies behind them.

Good fit

You have real expertise and evidence, but the public source trail is fragmented.

Your company, founder, product, or service is described differently across the website and public profiles.
You have first-hand expertise, useful data, case studies, or customer evidence that has not been turned into reference material.
Important pages are crawlable but weakly connected, duplicated, outdated, or unclear about who did what.
You can give access to subject-matter experts and approve factual changes to profiles, pages, and structured data.
You want a measured, durable source system that supports both conventional SEO and AI-search discovery.

Not a good fit

You need guaranteed placement, manufactured authority, or volume without evidence.

The brief requires guaranteed rankings, backlinks, knowledge panels, or citations in a named AI answer.
The plan depends on fake reviews, paid editorial links without disclosure, mass directory spam, or invented expert claims.
There is no accountable person who can verify the entity, services, credentials, dates, and outcomes being published.
The only goal is to add schema or an llms.txt file while leaving thin, duplicated, or unsupported content unchanged.
Success is defined only by a vanity visibility score, with no connection to qualified discovery, cited pages, or enquiries.

What the work covers

The service covers the source system around your reputation—not just schema markup.

A focused engagement starts with the highest-value entity or offer. Each deliverable must improve clarity for a human reader and remain accurate enough to publish as machine-readable data.

Entity and citation audit

Inventory names, domains, profiles, services, claims, rankings, cited pages, crawler access, duplicates, and unsupported relationships.

Knowledge graph implementation

Create stable identifiers and accurate Person, Organization, Service, Article, Review, Place, and breadcrumb relationships where the visible content supports them.

Citation-ready source assets

Publish expert pages, service definitions, case studies, original evidence, FAQs, comparison material, and source notes that answer real buyer questions.

External record alignment

Correct owned profiles and legitimate listings, prepare source-led outreach, document earned mentions, and track where the entity is actually referenced.

Compare the options

Each layer has a different job—and a clear limit.

Workstream	What it contributes	What it cannot promise
Technical discovery	Crawl access, canonicals, internal links, sitemaps, performance, and clean indexable pages.	Crawlability does not guarantee indexing, ranking, or selection as a source.
Entity architecture	Consistent identifiers, relationships, structured data, profiles, and claim boundaries.	Schema cannot turn an unsupported statement into an authoritative fact.
Reference content	Original expertise, evidence, clear answers, useful tables, case studies, and maintained source notes.	More pages do not create more authority when the material is repetitive or generic.
Earned citations	Relevant editorial mentions, expert contributions, public records, and third-party corroboration.	No ethical provider controls whether an editor, search engine, or AI system cites the source.

How the work runs

Resolve the entity, prove the claims, publish the source trail, then measure.

Map

Choose the entity, audience, services, prompts, queries, public profiles, competitors, and source gaps in scope.

Verify

Trace every material claim to owned evidence or an independent source; remove ambiguity and unsupported relationships.

Build

Implement the knowledge graph, internal architecture, reference pages, profile corrections, and technically clean discovery paths.

Observe

Track indexing, search visibility, cited URLs, AI referrals, branded answers, corrections, enquiries, and evidence that needs maintenance.

Sources

The method follows current platform guidance, with the limits left intact.

Google Search — generative AI optimization guide

Google says foundational SEO, crawlable technical structure, and unique non-commodity content remain central; it warns against inauthentic mentions and GEO shortcuts.

Google Search — structured data guidelines

Structured data must represent visible, accurate page content. Correct markup enables eligibility, not guaranteed display.

OpenAI — publishers and developers FAQ

OpenAI documents OAI-SearchBot access and ChatGPT referral tracking for publishers that want discoverable, linked search results.

Bing Webmaster — AI Performance

Bing reports cited URLs and grounding queries while distinguishing citation counts from ranking, authority, or placement.

Schema.org — sameAs

The sameAs property links an entity to a page that unambiguously identifies the same thing; it should not be used for merely related pages.

Relevant work

The relevant proof combines technical SEO, content systems, and source discipline.

My public work includes the 42 Portugal search-authority system, structured case studies with claim-level source trails, technical publishing, entity markup, international route architecture, and AI-search measurement. The linked pages show the method and its evidence boundaries rather than presenting citation visibility as a guaranteed outcome.

FAQ

Questions about GEO, SEO citations, and knowledge graphs.

What is a GEO or AI-search citation?

It is a visible source reference or link used to support an AI-generated answer. Different platforms retrieve, present, and measure sources differently. A citation count does not automatically mean a ranking, endorsement, or conversion.

How is this different from traditional SEO?

It is not a replacement for SEO. The work uses the same foundations—crawlability, indexable pages, clear intent, useful original content, reputable links, and measurement—then adds closer attention to entity consistency, source eligibility, answer contexts, and cited-page reporting.

Can you guarantee that ChatGPT, Google, or Copilot will cite us?

No. I can remove technical blockers, improve entity clarity, create stronger source material, and measure what is retrieved or cited. The platform controls crawling, indexing, ranking, answer generation, and source selection.

Is structured data enough to build a knowledge graph?

No. Structured data describes relationships that should already be visible and true. A useful knowledge graph also needs stable identifiers, canonical pages, consistent public records, internal links, evidence, and maintenance when facts change.

Do you submit businesses to citation directories?

Only when a legitimate industry, professional, or local record helps users verify the business. I do not sell bulk directory submissions or treat low-quality listings as authority. Existing records are corrected, deduplicated, and documented before new ones are added.

What content is most likely to become a useful source?

First-hand material that answers a real question and is difficult to replace: original data, precise service definitions, expert explanations, documented methods, case studies, comparisons, and maintained reference pages with clear provenance.

How do you measure progress?

The baseline can include crawl and index coverage, branded result accuracy, ranking queries, cited URLs, grounding queries where available, AI referrals, profile consistency, earned mentions, assisted enquiries, and corrections resolved. We report platform limits instead of merging unlike metrics into one score.

Can this help a local business?

Yes, when local identity is material. The work may include consistent name, address, phone, service area, opening details, maps and business profiles, local evidence, reviews, and location-specific pages. It does not create fake locations or doorway pages.

Start with one entity

Bring the name, offer, or expert that search and AI systems keep getting wrong—or ignore.

I will map the current source trail, identify the weakest relationships, and tell you whether the next useful step is technical cleanup, a knowledge graph, stronger evidence, earned-source work, or no new page at all.

Map the citation gaps