AI Visibility · Regional Scoreboard

Nissan AI Visibility Baltimore Metro

Nissan dealers across Baltimore

Regional report · 7 sub-markets
AI
VISIBILITY
Find Buy Service
Prepared August 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 18 Nissan 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.

Bob Bell Nissan leads with 17% share of voice (of every time AI named a Nissan dealer in the region) and is named in 79% of all answers. Sheehy Nissan of Glen Burnie and Antwerpen Nissan Security follow. The clearest gap is DARCARS Nissan of College Park, 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 Nissan shopping happens there - measured by its monthly search demand - so a strong showing in high-demand markets like Baltimore and York 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 Nissan 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. Bob Bell Nissan - 17% share of voice, named in 79% of answers, named first 35% of the time; strongest sub-market: Dundalk.
  2. Sheehy Nissan of Glen Burnie - 16% share of voice, named in 71% of answers, named first 16% of the time; strongest sub-market: Annapolis.
  3. Antwerpen Nissan Security - 12% share of voice, named in 57% of answers, named first 17% of the time; strongest sub-market: Baltimore.
  4. Jim Coleman Nissan of Ellicott City - 11% share of voice, named in 54% of answers, named first 35% of the time; strongest sub-market: Columbia.
  5. Nationwide Nissan - 10% share of voice, named in 48% of answers, named first 0% of the time; strongest sub-market: Baltimore.
  6. Jones Bel Air Nissan - 9% share of voice, named in 40% of answers, named first 15% of the time; strongest sub-market: South Bel Air.
  7. Easterns Nissan of White Marsh - 6% share of voice, named in 27% of answers, named first 2% of the time; strongest sub-market: South Bel Air.
  8. Ciocca Nissan of York - 4% share of voice, named in 8% of answers, named first 90% of the time; strongest sub-market: York.
  9. Hanover Nissan - 4% share of voice, named in 8% of answers, named first 11% of the time; strongest sub-market: York.
  10. Annapolis Nissan - 3% share of voice, named in 11% of answers, named first 28% of the time; strongest sub-market: Annapolis.
  11. Ourisman Nissan - 3% share of voice, named in 13% of answers, named first 20% of the time; strongest sub-market: Columbia.
  12. Antwerpen Nissan - 2% share of voice, named in 7% of answers, named first 34% of the time; strongest sub-market: Columbia.
  13. Nissan of Bowie - 2% share of voice, named in 6% of answers, named first 0% of the time; strongest sub-market: Annapolis.
  14. Jim Coleman Nissan of Silver Spring - 1% share of voice, named in 4% of answers, named first 0% of the time; strongest sub-market: Columbia.
  15. Jim Coleman Nissan - 1% share of voice, named in 3% of answers, named first 0% of the time; strongest sub-market: Columbia.
  16. DARCARS Nissan of Rockville - 0% share of voice, named in 0% of answers, named first 0% of the time; strongest sub-market: Columbia.
  17. DARCARS Nissan of College Park - 0% share of voice, named in 0% of answers, named first 0% of the time; strongest sub-market: Dundalk.
  18. Sheehy Nissan of Waldorf - 0% share of voice, named in 0% of answers; strongest sub-market: Dundalk.

Who leads each sub-market, and where

  • Baltimore (population 585,708, 8,750 searches per month) - AI names Bob Bell Nissan most.
  • York (population 43,992, 1,050 searches per month) - AI names Ciocca Nissan of York most.
  • Columbia (population 99,615, 700 searches per month) - AI names Jim Coleman Nissan of Ellicott City most.
  • Glen Burnie (population 67,639, 550 searches per month) - AI names Sheehy Nissan of Glen Burnie most.
  • Annapolis (population 40,812, 470 searches per month) - AI names Annapolis Nissan most.
  • Dundalk (population 63,597, 360 searches per month) - AI names Bob Bell Nissan most.
  • South Bel Air (population 48,828, 190 searches per month) - AI names Jones Bel Air Nissan 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

  • Nissan Rogue - 2,260 searches per month
  • Nissan Altima - 2,020 searches per month
  • Nissan Sentra - 1,310 searches per month
  • Nissan Pathfinder - 1,270 searches per month
  • Nissan Kicks - 1,200 searches per month
  • Nissan Armada - 870 searches per month
  • Nissan Frontier - 840 searches per month
  • Nissan Z - 710 searches per month
  • Nissan Murano - 670 searches per month
  • Nissan Leaf - 550 searches per month

Top Sources

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

  • nissanusa.com - 9.4% of citations
  • sheehynissanglenburnie.com - 9.4% of citations
  • carfax.com - 7.8% of citations
  • bobbellnissan.com - 6.4% of citations
  • annapolisnissan.com - 6.3% of citations
  • dealerrater.com - 6.1% of citations
  • belairnissan.com - 5.5% of citations
  • cioccanissanofyork.com - 4.7% of citations
  • caredge.com - 4.0% of citations
  • cars.com - 3.5% of citations
  • yelp.com - 3.0% of citations
  • ourismannissan.com - 2.9% of citations

Regional Insights

AI gives shoppers a short list of 3 to 4 dealers. AI answers with actual dealership names 98.6% 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.

Dealer ratings run far lower on Yelp than on Google. The tracked dealers average 4.5 stars on Google but only 2.5 on Yelp, and 14 of 17 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.

Baltimore holds most of the demand - and no dealer has a firm lead. Baltimore and York together hold 81% of the region's shopping demand, yet in Baltimore, the busiest market, the most-recommended dealer (Bob Bell Nissan) takes only 20% 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
1Bob Bell NissanDundalk79%
17%
35%
2Sheehy Nissan of Glen BurnieAnnapolis71%
16%
16%
3Antwerpen Nissan SecurityBaltimore57%
12%
17%
4Jim Coleman Nissan of Ellicott CityColumbia54%
11%
35%
5Nationwide NissanBaltimore48%
10%
0%
6Jones Bel Air NissanSouth Bel Air40%
9%
15%
7Easterns Nissan of White MarshSouth Bel Air27%
6%
2%
8Ciocca Nissan of YorkYork8%
4%
90%
9Hanover NissanYork8%
4%
11%
10Annapolis NissanAnnapolis11%
3%
28%
11Ourisman NissanColumbia13%
3%
20%
12Antwerpen NissanColumbia7%
2%
34%
13Nissan of BowieAnnapolis6%
2%
0%
14Jim Coleman Nissan of Silver SpringColumbia4%
1%
0%
15Jim Coleman NissanColumbia3%
1%
0%
16DARCARS Nissan of RockvilleColumbia0%
0%
0%
17DARCARS Nissan of College ParkDundalk0%
0%
0%
18Sheehy Nissan of WaldorfDundalk0%
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. 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 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 Nissan dealer near [city]", "Nissan Rogue inventory near [city]", and "where to service a Nissan 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 Nissan dealership in the region's measured footprint is tracked and scored - 18 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, Baltimore and York together carry about 81% 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.

Get a Custom Report
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
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Nissan
Baltimore
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[{"title":"AI gives shoppers a short list of 3 to 4 dealers","html":"AI answers with actual dealership names 98.6% 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."},{"title":"Dealer ratings run far lower on Yelp than on Google","html":"The tracked dealers average 4.5 stars on Google but only 2.5 on Yelp, and 14 of 17 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."},{"title":"Baltimore holds most of the demand - and no dealer has a firm lead","html":"Baltimore and York together hold 81% of the region's shopping demand, yet in Baltimore, the busiest market, the most-recommended dealer (Bob Bell Nissan) takes only 20% of AI's dealer mentions. AI names a different leading dealer in 6 of the 7 local areas."}]
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