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Vancouver · AI visibility
Ask a chatbot for a business in Vancouver and it will answer with two or three names and a sentence about each. If the models hold no clear facts about you, or the wrong ones, you are not in that answer. Fixing it is entity work, crawl rules, and writing pages a model can quote without mangling.
Vancouver · British Columbia · serving the Lower Mainland
Vancouver AI search
Metro Vancouver's municipal patchwork creates a specific problem for models. A business in Burnaby with listings that sometimes say Vancouver, sometimes Burnaby, and sometimes Lower Mainland gives a model conflicting signals about where it even is. Conflicting signals produce a model that declines to name you rather than one that guesses.
The fix is unglamorous and effective: one consistent name, address, and service description everywhere the business appears, with schema on the site that links the profiles together explicitly. That is the entity layer, and most local businesses have never had anyone look at it.
The second Vancouver angle is language. Models answer prompts in the language they were asked, drawing on sources in that language. A business with real Chinese or Punjabi content is a candidate for those answers. One without is not, and almost nobody here has thought about it.
How it works
Full scope on the ai visibility page.
We run a fixed set of prompts about your business across ChatGPT, Claude, Perplexity, and Gemini, then save the answers. That is the baseline. Most small businesses do not appear at all, or appear with the wrong facts. Either way we know the starting point.
robots.txt rules for each major AI crawler, plus an llms.txt and llms-full.txt written for your business. You decide which models are allowed to read the site. Most owners say yes to all of them.
Schema markup that names the business properly: full Organization or LocalBusiness, sameAs links to the Google Business Profile, social profiles, and directory listings. The point is unambiguous proof that the business on the site is the business the model has seen elsewhere.
Rewrite the about and service pages so a model can lift a clean two-sentence answer out of them. Q and A sections where they fit. Plain, sourced facts. Models cite what they can quote without paraphrasing it into nonsense.
Same prompts, same models, four to six weeks later. The before and after lands in a short PDF you keep. Anything still wrong gets a second pass.
What changes locally
A Vancouver AI visibility pass fixes the entity layer first, because in this region that is usually where the confusion is: one consistent name, one address, one clear service description, linked explicitly across the site, the Google Business Profile, and the directories. Crawl rules get set the way you choose, key pages get rewritten to be quotable, and the same prompts get re-run four to six weeks later so you can see what moved.
Note
Every engagement starts with a free written audit, including the Vancouver ones. If we think the budget is better spent somewhere else, we will say so before you commit to anything. See everything we do in Vancouver.
Vancouver ai visibility questions
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