We measured how often AI assistants (ChatGPT, Google AI Mode, and Google AI Overview) name each of the region's 9 Subaru dealers when shoppers ask where to find, buy, and service - city by city. Here is who is winning AI visibility today, and where the gaps are.
Mike Shaw Subaru leads with 19% share of voice (of every time AI named a Subaru dealer in the region) and is named in 71% of all answers. Schomp Subaru and Groove Subaru follow. The clearest gap is Subaru of Loveland, which AI names less often than its nearby shopper demand would suggest.
How to read this report. This draws on answers from ChatGPT, Google AI Mode, and Google AI Overview. Dealers are never named in the questions, so every dealer is measured the same way. Cities are not counted equally: each city counts toward the regional score in proportion to how much Subaru shopping happens there - measured by its monthly search demand - so a strong showing in high-demand markets like Denver and Aurora moves a dealer's regional standing much more than the same showing in a small one. Every city's own results appear in the sub-market table below. The full method is at the end of this report.
The regional leaderboard
Who AI recommends most across the region. Share of voice: of every time AI named a Subaru dealer in the region, how often it named this one. AI visibility: how often AI names the dealer at all. Named first: how often it is the very first dealer named.
Mike Shaw Subaru - 19% share of voice, named in 71% of answers, named first 21% of the time; strongest sub-market: Thornton.
Schomp Subaru - 19% share of voice, named in 69% of answers, named first 43% of the time; strongest sub-market: Aurora.
Groove Subaru - 17% share of voice, named in 61% of answers, named first 4% of the time; strongest sub-market: Centennial.
AutoNation Subaru Arapahoe - 16% share of voice, named in 57% of answers, named first 14% of the time; strongest sub-market: Centennial.
AutoNation Subaru West - 15% share of voice, named in 57% of answers, named first 40% of the time; strongest sub-market: Lakewood.
Flatirons Subaru - 7% share of voice, named in 28% of answers, named first 18% of the time; strongest sub-market: Boulder.
Valley Subaru of Longmont - 5% share of voice, named in 19% of answers, named first 1% of the time; strongest sub-market: Boulder.
Mike Shaw Subaru Greeley - 1% share of voice, named in 3% of answers, named first 69% of the time; strongest sub-market: Greeley.
Subaru of Loveland - 1% share of voice, named in 3% of answers, named first 3% of the time; strongest sub-market: Greeley.
Who leads each sub-market, and where
Denver (population 729,019, 13,420 searches per month) - AI names Mike Shaw Subaru most.
Aurora (population 359,407, 2,750 searches per month) - AI names Schomp Subaru most.
Lakewood (population 152,597, 1,670 searches per month) - AI names AutoNation Subaru West most.
Centennial (population 109,741, 1,300 searches per month) - AI names AutoNation Subaru Arapahoe most.
Thornton (population 133,451, 1,240 searches per month) - AI names Mike Shaw Subaru most.
Boulder (population 106,803, 1,000 searches per month) - AI names Flatirons Subaru most.
Greeley (population 108,795, 560 searches per month) - AI names Mike Shaw Subaru Greeley most.
The websites AI cited most when answering shopper questions across the region, as a share of all citations:
dealerrater.com - 12.3% of citations
carfax.com - 7.5% of citations
reddit.com - 7.4% of citations
flatironssubaru.com - 6.8% of citations
autonationsubaruwest.com - 5.2% of citations
mikeshawsubaru.com - 5.1% of citations
groovesubaru.com - 4.1% of citations
schompsubaru.com - 4.0% of citations
kbb.com - 4.0% of citations
cargurus.com - 3.8% of citations
caredge.com - 3.7% of citations
valleysubaru.com - 3.5% of citations
Regional Insights
AI gives shoppers a short list of 3 to 4 dealers. AI answers with actual dealership names 99.7% of the time and names only 3 to 4 dealers per answer. A dealer not on that list loses the shopper to one that is.
AI's information comes from review sites and forums, not dealer websites. dealerrater.com alone is cited more than twice as often as any dealer website.
Dealer ratings run far lower on Yelp than on Google. The tracked dealers average 4.6 stars on Google but only 3.2 on Yelp, and 2 of 9 score below 3.0 there. Yelp is one of AI's cited sources in this report, so a weak Yelp profile feeds directly into what AI reads.
Denver holds most of the demand - and no dealer has a firm lead. Denver and Aurora together hold 74% of the region's shopping demand, yet in Denver, the busiest market, the most-recommended dealer (Mike Shaw Subaru) takes only 22% of AI's dealer mentions. AI names a different leading dealer in 6 of the 7 local areas.
Regional footprint
Who leads each sub-market, and where
The dealer AI names most in each sub-market. Each sub-market is measured at its anchor city -
shown with its population - chosen to represent that part of the region; the anchors together
span the metro's major population centers. On the map, each anchor's bubble is sized by its
monthly shopper search demand, so larger circles are the markets with more search activity.
National footprint
The 25 metros, coast to coast
Each bubble is one of America's 25 biggest metro areas, sized by monthly shopper search
demand in its anchor city and numbered by metro rank. The table that follows names the dealer
AI recommends most in each.
Market demand
Where the nation shops
Monthly brand and model searches in each metro's anchor city - the demand AI answers compete
for. Search demand weights and sizes the markets in this report; it is not a sales figure.
Market demand
What the region is searching for
How many shoppers near the region search for each model every month. This is the
demand AI answers compete for, and it sets how much each city counts toward the scores. Search
demand weights the cities in this report; it is not a sales figure.
Metro leaderboard
The National 25 - who AI recommends, metro by metro
The dealer AI assistants recommend most in each of the nation's 25 biggest metros, measured
with identical non-branded Find / Buy / Service questions in each metro's anchor city.
How to read this. Share of voice: of every time AI named
a dealer in this metro, how often it named this one. AI
visibility: how often AI names the dealer at all. Named first: how often it is the very first
dealer named - kept separate from visibility, as always. Bars are scaled to a 50% share.
Regional leaderboard
The regional leaderboard
Who AI recommends most across the region. Share of voice is the headline:
out of every time AI named a dealer, how often it named this one.
AI visibility is how often AI names the dealer at all, and
named first is how often it is the very first dealer named - a dealer can be
named often yet rarely first, so we keep these separate. Cities with more shopper demand count
for more.
#
Dealer
Strongest sub-market
AI visibility
Share of voice
Named first
1
Mike Shaw Subaru
Thornton
71%
19%*
21%
2
Schomp Subaru
Aurora
69%
19%*
43%
3
Groove Subaru
Centennial
61%
17%
4%
4
AutoNation Subaru Arapahoe
Centennial
57%
16%
14%
5
AutoNation Subaru West
Lakewood
57%
15%
40%
6
Flatirons Subaru
Boulder
28%
7%
18%
7
Valley Subaru of Longmont
Boulder
19%
5%
1%
8
Mike Shaw Subaru Greeley
Greeley
3%
1%
69%
9
Subaru of Loveland
Greeley
3%
1%
3%
A share marked * is a near-tie: the dealer ranked next to it is within 1 point, and the ranking follows the unrounded scores.
Winning patterns
The winners are not who you'd expect
The two things dealers invest in as reputation - store size and Google rating - do not
separate the AI leaders from the field. Most metros are led by a store that is not the biggest
in its market, winning under its own local name.
Where AI's winners rank by store size. Every metro's
dealers, ranked by Google review count; the groups below show where each metro's AI leader
falls in that size order.
Dealer scorecard
Dealer ranking scorecard
Read each grade cell as two numbers: a bold 0-100 grade, and in grey the share of voice it
comes from. The grade is relative - the region's strongest dealer scores 100 and every other
dealer is measured against it. Find, Buy and Service are graded on their own and count equally
toward the Weighted overall. "Weighted" means busier cities count for more: each city's result
is scaled by its monthly search demand before the cities are combined, so how a dealer does
where the shoppers are matters most.
AI sources
Top Sources
The websites AI cited most when answering shopper questions across the region - each shown
as its share of all the citations AI made. Getting listed and well-reviewed on the sources that
rank highest here is how a dealer gets into AI answers.
AI sources
What AI reads, nationally
Store size and ratings do not decide who AI recommends. The clearest national pattern is
what AI reads: the same few sources appear in metro after metro. Each website is shown as its
share of all the citations AI made across the 25 measured metros. Getting listed and
well-reviewed on the sources that rank highest here is how a dealer gets into AI answers.
Market opportunity
Most metros are still up for grabs
The small number next to each metro is the leader's share of voice divided
by the runner-up's - 1.0x means the leader and runner-up are tied.
Contested - the runner-up is within striking distanceHeld - the leader is comfortably aheadBubble size = market size (monthly searches)
Leader's share of voice
Of every time AI named a dealer in that metro, the percentage that went to the metro's
#1 dealer.
Runner-up's share of voice
The same measure for the #2 dealer. The closer the two shares, the closer the race;
a leader can never sit below the dashed line, only above it.
Share of voice = a dealer's AI mentions ÷ all dealers' AI mentions in its metro
Striking distance = the runner-up holds at least the leader's share ÷ 1.2
Market opportunity
Share of Voice vs Share of Demand
This chart plots each dealer's Share of Voice (up)
against its Share of Demand (across). The dashed line is break-even, where the
two are equal. Below it, a dealer's Share of Demand is larger than its Share of Voice - the
clearest gaps to close. Bubbles are sized by Google review count.
At or above its opportunityBelow its opportunity (a gap)Bubble size = Google review count
Share of Voice
When AI assistants recommend dealers in this region, the percentage of those
recommendations that go to this dealer.
Share of Demand
This dealer's slice of the region's shoppers, based on distance: each town's shoppers
count toward the stores nearest them, and busier towns count for more.
Share of voice = a dealer's AI mentions ÷ all dealers' AI mentions
Share of demand = a dealer's nearby demand ÷ all dealers' nearby demand
Regional insights
Regional Insights
These patterns stand out when the region's answers are read together. Each one is
computed from the measured runs behind this report.
National insights
National insights
Beyond the headline story, these patterns stand out when all the metros are read together.
Each one is computed from the measured runs - per-metro results are directional, but these
cross-metro patterns rest on the full national sample.
Recommended actions
What To Do
The patterns in this report are national, but the actions they point to are local - and none
of them requires being the biggest store in the market. Five places to start, each grounded in
what this measurement found.
Methodology
Methodology
We asked non-dealer branded questions - for example "best Subaru dealer near [city]", "Subaru Crosstrek inventory near [city]", and "where to service a Subaru near [city]" - against ChatGPT, Google AI Mode, and Google AI Overview, city by city, and recorded which dealers each answer named and in what order. Dealers are never named in the questions, so every dealer in the region is measured the same way and the leaderboard reflects who AI brings up on its own. Search demand comes from Google search volume for in-market shopping terms by model and city; it weights each city and is not a sales figure. Every confirmed Subaru dealership in the region's measured footprint is tracked and scored - 9 dealers in this report.
Position is reported only as "named first". How often AI names a dealer and how early it names them are separate measurements, and this report keeps them separate. Because the weighting follows measured demand, Denver and Aurora together carry about 74% of the regional score; every city's own results are shown in the sub-market table. Search demand: Google search volume. AI visibility: live queries to ChatGPT, Google AI Mode, and Google AI Overview. Dealer ratings: Google Business Profile and Yelp.
Related reports
Related Reports
The national report this regional report belongs to, and sibling regions as they publish.
Regional reports
Regional Reports
Metro-level reports, each ranking the dealers AI
recommends across that metro, city by city.
Next step · For your dealership
Custom Dealer Reports
This regional report shows how AI sees the whole market. A Custom
Dealer Report goes deeper on one dealership: yours.
This national report shows how AI sees dealers across
America's biggest metros. A Custom Dealer Report goes deeper on one dealership: yours.
Every month, CarGenius runs the questions your buyers ask across the major AI engines and
reports how often AI names you versus each competitor, scores your Find, Buy, and Service
visibility, verifies your marketplace presence, and ranks what to fix by effort and impact.
How often AI names each dealer across this month's shopping prompts
Your Dealership
54%
Competitor A
41%
Competitor B
33%
Competitor C
27%
FIND
72/100
BUY
41/100
SERVICE
58/100
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Subaru
Denver
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