Named someone elseManitoba
You:“best shop in Winnipeg”
ChatGPT named:McNally Robinson Booksellers, Hudson's Bay, Out of the Blue
No member shop we scored showed up.
Canada · ChatGPT visibility · Province by province
We sampled thousands of main-street businesses across each province.
44%
named at least once
56%
never named
34%
named more than once
9
provinces
When people ask ChatGPT where to eat, shop, or get a haircut, fewer than half of these independent businesses make the answer. Big city or small, the pattern is the same.
Chart 1
Share of scored member businesses that ChatGPT named at least once.
Main-street business districts sampled in each province. Black tick = Canada overall (44%). Bar = % of scored members named at least once. Links to the full studies are at the bottom of the page.
Chart 2
Strong = named in more than one answer. Partial = named once. Not visible = never named in any tested answer.
Canada overall
Strong
34%
named in more than one answer
Partial
10%
named once
Not visible
56%
never named
By province (fewest invisible first)
Right column = % never named. Few businesses sit in the middle: a member is usually either in the answer or missing from it.
Chart 3
Salons, clinics, and gyms do best. Shops do worst.
Combined across every province, rebuilt from each study's rounded category rates, so treat these as approximate. Health, Beauty & Fitness beat its local overall rate in every study where it had enough businesses to count. Shopping fell below its local rate in most. Arts & Entertainment and hotels score high but are small groups.
Chart 4
Members show up more when someone asks for a list (“best café in [city]”) than when they ask ChatGPT who to see.
“Best X in [city]” lists
41%
of members named
“Who should I see for X?”
32%
of members named
Lists beat direct recommendations in every province (gap of 5 to 14 percentage points, right column). ChatGPT is more willing to include a local independent in a list than to recommend it outright.
Chart 5
Each dot is one province, placed by the metro population where its businesses were sampled.
Rank correlation between metro population and named rate: +0.13 (no relationship). Ontario's sampled districts alone run from 36% to 64%, a wider spread than the gap between the top and bottom provinces. The business district and its member mix matter more than the size of the city.
Provinces sampled in more than one city are placed at a weighted average metro population (weighted by businesses scored).
Chart 6
Real answers from the studies. Sometimes a member makes it. Often a chain or a non-member business takes the spot.
You:“best shop in Winnipeg”
No member shop we scored showed up.
You:“best cafe in St. John's”
No member cafe we scored showed up.
You:“Who should I see for hair salon in Vancouver?”
A member business made the answer.
You:“Who should I see for gym in Toronto?”
Chains took the answer. No member gym we scored showed up.
You:“Who should I see for auto repair in Ottawa?”
Chains took the answer. No member garage we scored showed up.
You:“Who should I see for pub in Halifax?”
Member businesses made the answer.
Coming next
Same questions, same scoring rules, Canadian provinces against US states. Canada's side of the board is in. The US side is a placeholder until those runs are done. No US numbers are shown here.
Canada
44%
named · 9 provinces
USA
—
US states: data coming
Placeholder
Point-in-time ChatGPT snapshot, measured recently. Prepared by CLIXERA from its published main-street business district studies. All CLIXERA research