Overview Leaderboard Methodology
Industry Report

Small Kitchen Appliances

Manufacturers of countertop electrical appliances such as blenders, toasters, coffee makers, mixers, and food processors.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
Breville
76/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Vitamix
90

Highest score on the LBA metric.

Authority Leader?
Ninja
59

Highest score on the Authority metric.

TOM Leader?
Breville
100

Highest score on the TOM metric.

Breville leads the Small Kitchen Appliances category in AI responses

Breville is the most consistently-surfaced brand when users ask AI assistants about Small Kitchen Appliances, but not to the point of monopolising the conversation. Cuisinart and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 37 Small Kitchen Appliances brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Breville
breville.com
 77
56
100
76
2
Cuisinart
cuisinart.com
 83
52
94
74
3
Ninja
ninjakitchen.com
 75
59
83
72
4
KitchenAid
kitchenaid.com
 85
36
91
65
5
Hamilton Beach
hamiltonbeach.com
 71
18
63
43
6
Vitamix
vitamix.com
 90
12
60
40
7
Zojirushi
zojirushi.com
 87
3
42
22
8
Instant Pot
instantpot.com
 88
2
38
20
9
Black+Decker
blackanddecker.com
 62
6
12
17
10
Fellow
fellow.app
 80
3
4
10
11
Instant Brands
instantbrands.com
 72
1
27
10
12
Oster
oster.com
 70
0
14
7
13
D
Dash
dashappliances.com
 70
0
2
4
14
Nespresso
nespresso.com
 85
0
10
3
15
OXO
oxo.com
 73
0
32
3
16
De'Longhi
delonghi.com
 75
0
6
2
17
Miele
miele.com
 85
0
5
2
18
S
SMEG
smeg.com
 73
0
13
2
19
Braun
braunhousehold.com
 84
0
1
1
20
Chefman
chefman.com
 56
1
0
1
21
Dualit
dualit.com
 74
0
2
1
22
Keurig
keurig.com
 74
0
2
1
23
Moccamaster
moccamaster.com
 87
0
3
1
24
NutriBullet
nutribullet.com
 73
0
1
1
25
Proctor Silex
proctorsilex.com
 61
0
1
1
26
Bella
bellakitchenware.com
 52
0
0
0
27
Blendtec
blendtec.com
 80
0
0
0
28
Jura
jura.com
 74
0
0
0
29
Kenwood
kenwoodworld.com
 73
0
0
0
30
Krups
krups.com
 67
0
0
0
31
Magimix
magimix.com
 72
0
0
0
32
Morphy Richards
morphyrichards.com
 67
0
0
0
33
Philips Norelco
philips.com
 25
0
0
0
34
Russell Hobbs
russellhobbs.com
 72
0
0
0
35
Sage
sageappliances.com
 68
0
0
0
36
Toughbook
panasonic.com
 44
0
0
0
37
Wilfa
wilfa.com
 52
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Small Kitchen Appliances 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
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 287 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 →