Overview Leaderboard Methodology
Industry Report

Subcompact SUVs

Small crossover SUVs that offer higher seating position and cargo flexibility while remaining economical and city-friendly.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Honda
85/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Hyundai
89

Highest score on the LBA metric in this industry.

Authority Leader?
Honda
81

Highest score on the Authority metric in this industry.

TOM Leader?
Mazda
100

Highest score on the TOM metric in this industry.

Honda is the default answer in AI responses for Subcompact SUVs

Honda and Mazda together dominate AI responses for Subcompact SUVs. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 34 Subcompact SUVs 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
 83
81
91
85
2
Mazda
mazdausa.com
 79
64
100
80
3
Hyundai
hyundai.com
 89
62
87
78
4
Subaru
subaru.co.jp
 78
54
83
71
5
Subaru Crosstrek
subaru.com
 86
35
83
64
6
Kia
kia.com
 82
32
80
60
7
Chevrolet
chevrolet.com
 82
19
29
36
8
Nissan Kicks
nissanusa.com
 76
12
34
32
9
Volkswagen
vw.com
 77
8
28
28
10
Buick
buick.com
 76
8
20
24
11
Ford
ford.com
 83
8
8
20
12
Skoda
skoda-auto.com
 83
8
8
20
13
Tata
tatamotors.com
 83
8
8
20
14
Citroen
citroen.com
 77
8
8
19
15
Dacia
dacia.com
 78
8
8
19
16
Jeep
jeep.com
 77
8
8
19
17
MINI
mini.com
 76
8
8
19
18
Perodua
perodua.com.my
 78
8
8
19
19
Mahindra
mahindra.com
 76
8
8
18
20
Opel
opel.com
 74
7
7
18
21
Peugeot
peugeot.com
 76
8
8
18
22
Renault
renault.com
 76
8
8
18
23
Geely
geely.com
 71
7
7
17
24
M
Mitsubishi
mitsubishi-motors.com
 67
7
7
17
25
Suzuki
suzuki.com
 71
7
7
17
26
Fiat
fiat.com
 66
7
7
16
27
Haval
haval-global.com
 66
7
7
16
28
M
MG
mgmotor.com
 64
6
6
16
29
Proton
proton.com
 67
7
7
16
30
C
Chery
cheryinternational.com
 62
6
6
15
31
Crown
toyota.com
 35
3
3
9
32
Eunos
mazda.com
 28
3
3
8
33
Hyundai Evolve+
hyundaiusa.com
 11
1
1
3
34
President
nissan-global.com
 8
1
1
3

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Subcompact SUVs 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 269 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 →