Overview Leaderboard Methodology
Industry Report

Compact Cars

Small, fuel-efficient passenger vehicles designed for urban and suburban driving, produced by mass-market manufacturers.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 258
Total responses: 1,320
Top Brand Overall?
Honda
92/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Maruti Suzuki
96

Highest score on the LBA metric in this industry.

Authority Leader?
Honda
92

Highest score on the Authority metric in this industry.

TOM Leader?
Honda
96

Highest score on the TOM metric in this industry.

Honda is the default answer in AI responses for Compact Cars

When users ask ChatGPT, Claude, or Gemini about Compact Cars, Honda is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Hyundai is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 33 Compact Cars brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Honda
honda.com
 89
92
96
92
2
Hyundai
hyundai.com
 80
67
84
77
3
Kia
kia.com
 86
24
78
55
4
Nissan
nissan.com
 70
40
40
48
5
Subaru
subaru.co.jp
 82
10
48
36
6
Volkswagen
vw.com
 88
9
36
32
7
Maruti Suzuki
marutisuzuki.com
 96
10
10
23
8
Opel
opel.com
 78
8
8
19
9
Perodua
perodua.com.my
 79
8
8
19
10
Tata
tatamotors.com
 78
8
8
19
11
Chevrolet
chevrolet.com
 75
7
7
18
12
Citroen
citroen.com
 74
7
7
18
13
Fiat
fiat.com
 74
7
7
18
14
MINI
mini.com
 72
7
7
18
15
Peugeot
peugeot.com
 75
7
7
18
16
Skoda
skoda-auto.com
 76
8
8
18
17
Dacia
dacia.com
 70
7
7
17
18
D
Daihatsu
daihatsu.com
 69
7
7
17
19
Geely
geely.com
 67
7
7
17
20
M
MG
mgmotor.com
 69
7
7
17
21
Proton
proton.com
 70
7
7
17
22
Renault
renault.com
 71
7
7
17
23
SEAT
seat.com
 71
7
7
17
24
Vauxhall
vauxhall.co.uk
 70
7
7
17
25
C
Chery
cheryinternational.com
 64
6
6
16
26
Smart
smart.com
 64
6
6
16
27
Suzuki
suzuki.com
 66
7
7
16
28
M
Mitsubishi
mitsubishi-motors.com
 62
6
6
15
29
Scion
scion.com
 63
6
6
15
30
Eunos
mazda.com
 42
4
4
11
31
Crown
toyota.com
 17
2
2
5
32
Hyundai Evolve+
hyundaiusa.com
 12
1
1
4
33
President
nissan-global.com
 2
0
0
1

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 258 shared Compact Cars prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 258 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →