ENTITY / KNOWLEDGE GRAPH GEO

Give AI a clear picture of who your business is.

Connect your organisation, people, services, products, locations and proof so AI systems can understand the relationships behind the brand—not just read isolated pages.

  • Build an entity model before choosing Schema markup or structured data.
  • Align visible copy, Organization, Person, Service, Product and Breadcrumb relationships.
  • Use sameAs, language aliases and external references to reduce brand ambiguity.

Share the site you want us to review.

We start with the questions your buyers already ask, then make the useful evidence on your site easier to find, understand and act on.

Connected data and entity relationship planning on a digital workstation
WHAT THE BUYER NEEDS TO KNOW

When a buyer asks, your website needs somewhere useful to take them.

01Question“What is this company known for, and who is it actually suited to help?”
02Evidencea before/after entity relationship table and a valid schema example tied to visible content
03ActionA clearer answer and a useful next step
AI ANSWER SIGNALSENTITY MODELMARKUPCONSISTENCYACCURACY
ENTITY MODELMARKUPCONSISTENCYACCURACYNEXT STEP

WHY THIS MATTERS TO THE BUSINESS

From disconnected pages to a business identity AI can follow.

That question still needs a good answer: clear facts, credible proof and a page that makes the next step obvious.

01

Entity relationship model

Map organisation, person, service, product, industry, location, partner and proof relationships.

02

Accurate structured data

Use Schema and structured data only when the visible page supports the relationship.

03

Naming and sameAs control

Resolve domains, profiles, social links, language aliases and brand disambiguation.

FROM A QUESTION TO A REAL ENQUIRY

A short answer still depends on four practical checks.

We check four things in order: can the site be read, is the offer clear, is there proof, and can the visitor take the next step?

Connected data and entity relationship planning on a digital workstation
01

Entity relationship model

Map organisation, person, service, product, industry, location, partner and proof relationships.

02

Accurate structured data

Use Schema and structured data only when the visible page supports the relationship.

03

Naming and sameAs control

Resolve domains, profiles, social links, language aliases and brand disambiguation.

04

Entity-to-answer measurement

Retest whether the system describes the business, expertise and fit more accurately.

Connected data and entity relationship planning on a digital workstation

WHAT THE BUYER SEES TODAY

Before we add another page, we find out why the current answer is not doing its job.

First, we put the real buyer questions, current answers, sources and landing pages side by side. That shows whether the problem is visibility, accuracy, proof or the next step.

BUYER PROMPT“What is this company known for, and who is it actually suited to help?”
DiscoveryNo signalThe same service has several names and descriptions
InterpretationMixed signalSchema markup says more than the visible page proves
EvidenceWeak signalPeople, services and locations are not connected
ConversionLost signalThe answer confuses the brand with another entity

HOW THE WORK FITS TOGETHER

Four practical checks from question to enquiry.

GEO is the working link between a buyer’s question and a sales enquiry. Each part has a clear owner and a result to check.

01

Discover

ENTITY MODELMap organisation, person, service, product, industry, location, partner and proof relationships.
02

Interpret

MARKUPUse Schema and structured data only when the visible page supports the relationship.
03

Support

CONSISTENCYResolve domains, profiles, social links, language aliases and brand disambiguation.
04

Convert

ACCURACYRetest whether the system describes the business, expertise and fit more accurately.

THE WORK THAT MOVES THE NEEDLE

entity and knowledge graph GEO

Each part has one job: find the problem, improve the information, strengthen the proof or make the next step easier.

01

Entity relationship model

Map organisation, person, service, product, industry, location, partner and proof relationships.

ENTITY MODEL
Connected data and entity relationship planning on a digital workstation
02

Accurate structured data

Use Schema and structured data only when the visible page supports the relationship.

MARKUP
Connected data and entity relationship planning on a digital workstation
03

Naming and sameAs control

Resolve domains, profiles, social links, language aliases and brand disambiguation.

CONSISTENCY
Connected data and entity relationship planning on a digital workstation
04

Entity-to-answer measurement

Retest whether the system describes the business, expertise and fit more accurately.

ACCURACY
Connected data and entity relationship planning on a digital workstation
Connected data and entity relationship planning on a digital workstation

HOW WE CHECK PROGRESS

A useful report tells you what changed and what to do next.

Use the same prompts, dates and definitions each time. The figures below are planning examples, not client results.

4 → 1Conflicting entity descriptions
Unclear → ClearOrganisation/service relationship
2 → 9Supporting entity sources
4 → 12Qualified AI-referred enquiries

Include Hong Kong office/service relationships and English, Traditional Chinese and Simplified Chinese names only where they are accurate and useful.

THE BUYER DECISION

If the page is unclear, the buyer keeps looking.

BEFORE GEO

The buyer cannot tell whether you are a good fit.

  • The same service has several names and descriptions
  • Schema markup says more than the visible page proves
  • People, services and locations are not connected
  • The answer confuses the brand with another entity
AFTER GEO

The buyer can see why your service fits.

  • Relationships are clear in copy, markup and internal links
  • Structured data supports visible facts
  • Language aliases and profiles reinforce one identity
  • Prompt tests show better entity accuracy

From disconnected pages to a business identity AI can follow.

Illustrative planning frame—not a promised outcome.

WHO WORKS ON IT

One focused team from the buyer question to the enquiry.

Strategy defines the questions, content and search organise the proof, and the website turns interest into an enquiry. The images show working situations, not client endorsements.

Connected data and entity relationship planning on a digital workstation
STRATEGY

Prompt and market direction

Map organisation, person, service, product, industry, location, partner and proof relationships.

Connected data and entity relationship planning on a digital workstation
SEARCH + CONTENT

Evidence people can verify

Use Schema and structured data only when the visible page supports the relationship.

Connected data and entity relationship planning on a digital workstation
WEBSITE + CRO

A useful next step

Resolve domains, profiles, social links, language aliases and brand disambiguation.

START WITH THE REAL QUESTION

Tell us what your buyers are trying to choose.

Share your website and the question, category or comparison that matters. We will use the details to suggest the right next step.

  • Include Hong Kong office/service relationships and English, Traditional Chinese and Simplified Chinese names only where they are accurate and useful.
  • a before/after entity relationship table and a valid schema example tied to visible content
  • English, Traditional Chinese and Simplified Chinese routes are tested only when commercially relevant.

We use your details to understand the marketing and website problem before we suggest next steps.

FAQ

Your next customer may start by asking an AI tool what to choose.

What does entity and knowledge graph GEO GEO actually improve?

We start with the buyer questions that matter for Entity and knowledge graph GEO, then compare the current answer, the pages and sources behind it, and the next page the visitor needs. The focus is practical: what should be clearer, what should change, and how will we check it?

Does Schema markup alone create AI visibility or a knowledge panel?

No. Markup can help machines interpret supported facts, but it does not replace visible content, consistent entities, trusted sources or a clear buyer proposition. It cannot guarantee a knowledge panel or recommendation.

Can you promise a platform will recommend my company?

No. Models, retrieval, sources and answers change. The programme improves evidence quality and measures movement, but it cannot control a final answer or promise inclusion.

What proof should we prepare before the work starts?

a before/after entity relationship table and a valid schema example tied to visible content。

How do we measure whether it is working?

Track mention rate, recommendation frequency, answer accuracy, source coverage, AI-referred visits, qualified enquiries and conversion. Keep dates, prompts, sampling rules and CRM definitions visible. The page-specific reporting frame is: Conflicting entity descriptions; Organisation/service relationship; Supporting entity sources; Qualified AI-referred enquiries.

ENTITY / KNOWLEDGE GRAPH GEO

Start with the buyer question that is already sending people elsewhere.

The goal is simple: make the right information easier to find, trust and use.

See our GEO strategy

GEO strategy · answer visibility · entity clarity · qualified enquiries

WhatsApp Locke Lee