AI Visibility · Regional Scoreboard

Regional AI Report

Toyota dealers across Charlotte

Regional report · 7 sub-markets
AI
VISIBILITY
Find Buy Service
Prepared July 2026Prepared by CarGenius
Overview

Executive summary

We measured how often AI assistants (ChatGPT, Google AI Mode, and Google AI Overview) name each of the region's 8 Toyota 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.

Scott Clark Toyota leads with 21% share of voice (of every time AI named a Toyota dealer in the region) and is named in 85% of all answers. Toyota of North Charlotte and Hendrick Toyota Concord follow. The clearest gap is Town and Country Toyota, 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 Toyota shopping happens there - measured by its monthly search demand - so a strong showing in high-demand markets like Charlotte and Concord 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 Toyota 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.

  1. Scott Clark Toyota - 21% share of voice, named in 85% of answers, named first 26% of the time; strongest sub-market: Indian Trail.
  2. Toyota of North Charlotte - 21% share of voice, named in 85% of answers, named first 29% of the time; strongest sub-market: Huntersville.
  3. Hendrick Toyota Concord - 20% share of voice, named in 81% of answers, named first 42% of the time; strongest sub-market: Concord.
  4. Town and Country Toyota - 16% share of voice, named in 72% of answers, named first 5% of the time; strongest sub-market: Indian Trail.
  5. Toyota of Gastonia - 9% share of voice, named in 44% of answers, named first 4% of the time; strongest sub-market: Gastonia.
  6. Mike Johnson's Hickory Toyota - 5% share of voice, named in 25% of answers, named first 16% of the time; strongest sub-market: Hickory.
  7. Group 1 Toyota Rock Hill - 4% share of voice, named in 26% of answers, named first 9% of the time; strongest sub-market: Rock Hill.
  8. Cloninger Toyota - 4% share of voice, named in 23% of answers, named first 0% of the time; strongest sub-market: Concord.

Who leads each sub-market, and where

  • Charlotte (population 911,311, 24,800 searches per month) - AI names Scott Clark Toyota most.
  • Concord (population 87,696, 2,030 searches per month) - AI names Hendrick Toyota Concord most.
  • Gastonia (population 74,543, 1,220 searches per month) - AI names Toyota of Gastonia most.
  • Rock Hill (population 71,548, 1,220 searches per month) - AI names Group 1 Toyota Rock Hill most.
  • Huntersville (population 52,704, 960 searches per month) - AI names Toyota of North Charlotte most.
  • Hickory (population 40,374, 850 searches per month) - AI names Mike Johnson's Hickory Toyota most.
  • Indian Trail (population 37,073, 540 searches per month) - AI names Scott Clark Toyota most.

Bubble area is proportional to monthly search demand; the number keys each sub-market to the table. Small dots mark the tracked dealers' locations. Map © OpenStreetMap contributors.

What the region is searching for

  • Toyota Camry - 5,490 searches per month
  • Toyota Highlander - 4,600 searches per month
  • Toyota RAV4 - 4,520 searches per month
  • Toyota Corolla - 3,710 searches per month
  • Toyota Tacoma - 3,120 searches per month
  • Toyota 4Runner - 3,040 searches per month
  • Toyota Sienna - 2,140 searches per month
  • Toyota Tundra - 2,100 searches per month
  • Toyota Corolla Cross - 1,620 searches per month
  • Toyota Prius - 1,280 searches per month

Top Sources

The websites AI cited most when answering shopper questions across the region, as a share of all citations:

  • google.com - 14.6% of citations
  • reddit.com - 9.0% of citations
  • dealerrater.com - 7.8% of citations
  • toyotaofgastonia.com - 7.3% of citations
  • hendricktoyotaconcord.com - 7.0% of citations
  • scottclarkstoyota.com - 4.8% of citations
  • toyota.com - 4.7% of citations
  • toyotaofnorthcharlotte.com - 4.4% of citations
  • townandcountrytoyota.com - 4.2% of citations
  • carfax.com - 3.6% of citations
  • group1toyotarockhill.com - 3.4% of citations
  • caredge.com - 3.2% of citations

Regional Insights

AI gives shoppers a short list of 3 to 5 dealers. AI answers with actual dealership names 98.1% of the time and names only 3 to 5 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. reddit.com alone is cited more often than any dealer website. The most-cited discussion is r/Charlotte's "Best Toyota dealership in Charlotte area?", and 85% of the Reddit discussions AI cites come from this region's own communities.

Dealer ratings run far lower on Yelp than on Google. The tracked dealers average 4.6 stars on Google but only 2.5 on Yelp, and 5 of 6 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.

City "best dealership" lists feed AI's answers. Sites like Yelp publish a "Top 10 Best dealerships" page for each city, and AI cites them - Huntersville's most of all. A dealer's rank on its own city's list affects what AI tells shoppers there.

Charlotte holds most of the demand - and no dealer has a firm lead. Charlotte and Concord together hold 85% of the region's shopping demand, yet in Charlotte, the busiest market, the most-recommended dealer (Scott Clark Toyota) 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.

#DealerStrongest sub-marketAI visibilityShare of voiceNamed first
1Scott Clark ToyotaIndian Trail85%
21%
26%
2Toyota of North CharlotteHuntersville85%
21%
29%
3Hendrick Toyota ConcordConcord81%
20%
42%
4Town and Country ToyotaIndian Trail72%
16%
5%
5Toyota of GastoniaGastonia45%
9%
4%
6Mike Johnson's Hickory ToyotaHickory25%
5%
16%
7Group 1 Toyota Rock HillRock Hill26%
4%
9%
8Cloninger ToyotaConcord23%
4%
0%
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. Sources are ranked by how many of the 25 measured metros have them among their ten most-cited. A source that shows up coast to coast shapes every market at once.

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 distance Held - the leader is comfortably ahead Bubble 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 opportunity Below 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 Toyota dealer near [city]", "Toyota Camry inventory near [city]", and "where to service a Toyota 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 Toyota dealership in the region's measured footprint is tracked and scored - 8 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, Charlotte and Concord together carry about 85% 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.

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.

Custom Dealer Report · sample data

Most-mentioned dealers in your market

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
About CarGenius

About CarGenius

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Connects your DMS, inventory, and pricing directly to AI agents in real time.

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White-glove implementation and AEO reporting, like this report.

Toyota
Charlotte
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Bubble area is proportional to monthly search demand; the number keys each sub-market to the table. Small dots mark the tracked dealers' locations. Map © OpenStreetMap contributors.
Regional