A website is a collection of URLs. A business is an entity: it has a name, people, services, locations, credentials and relationships that exist beyond one domain. Entity SEO is the work of making those facts consistent enough for search and answer systems to recognize what the organization is and distinguish it from similarly named businesses.
For a Montreal company, that identity is often distributed across French and English pages, Google Business Profile, directories, professional profiles, press coverage and structured data. The objective is not to repeat one keyword everywhere. It is to make every important surface describe the same real-world organization.
Entity SEO is an identity problem before it is a markup problem
Schema.org markup can state that a page represents an Organization, Person, Service or LocalBusiness. It cannot make an unsupported claim credible. The visible page, the structured data and independent sources must agree.
Start with a compact identity record:
- official and public-facing names;
- primary website and canonical profiles;
- people responsible for the work;
- service area and real locations;
- services that can be demonstrated;
- credentials, memberships and publications that can be verified.
This record becomes the reference for titles, author pages, contact information, Organization markup and third-party profiles.
Build one identity across two languages
French and English content should not create two unrelated versions of the company. Each version can use language-specific terminology and examples while preserving stable facts. Reciprocal hreflang, self-referencing canonicals and clear internal links help express that relationship.
Translation alone is not enough. An English page aimed at Canadian buyers should explain the terms they use, answer their questions and link to evidence they can evaluate. The French page can address Quebec terminology and obligations more directly. Both should resolve to the same organization.
Four surfaces to audit
| Surface | Question to ask | Evidence to inspect |
|---|---|---|
| Website | Is the business described consistently? | About, author, contact and service pages |
| Structured data | Does markup match visible content? | Organization, Person, Service and Article nodes |
| External profiles | Can another source confirm the identity? | Business profiles, associations, media and directories |
| Internal graph | Do supporting pages reinforce the main entity? | Contextual links, breadcrumbs and topic clusters |
The audit should record contradictions, not just missing fields. A stale address or inconsistent name is often more damaging to clarity than an absent optional schema property.
Measure recognition, not the existence of code
Shipping JSON-LD is an implementation milestone, not an outcome. Useful indicators include branded-query consistency, correct attribution of authors and services, discovery of authoritative profiles, qualified organic visits and citations in answer systems.
Test representative questions on a repeatable schedule and preserve the prompt, date, market and result. Generative outputs vary; a single screenshot does not establish visibility.
A practical Montreal sequence
- Inventory the business facts and their sources.
- Correct the primary website and author identity.
- Align French and English equivalents without duplicating weak copy.
- Add structured data that reflects the visible page.
- Repair high-value external profiles.
- Connect evidence through contextual internal links.
- Monitor search results and attributed citations over time.
The durable advantage is not a larger volume of pages. It is a smaller amount of ambiguity. When the site, the people behind it and independent references tell the same story, machines and prospective clients have an easier time deciding what the business actually represents.