Overview Leaderboard Methodology
Industry Report

Memory Foam Mattresses

Mattresses constructed primarily from memory foam layers designed to contour the body and relieve pressure points.

Brands tracked: 36
Brands analyzed: 36
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 281
Total responses: 1,435
Top Brand Overall?
Nectar
82/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Tempur-Pedic
80

Highest score on the LBA metric.

Authority Leader?
Nectar
76

Highest score on the Authority metric.

TOM Leader?
Tempur-Pedic
100

Highest score on the TOM metric.

Nectar leads the Memory Foam Mattresses category in AI responses

Nectar is the most consistently-surfaced brand when users ask AI assistants about Memory Foam Mattresses, but not to the point of monopolising the conversation. Tempur-Pedic 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 36 Memory Foam Mattresses 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
Nectar
nectarhr.com
 74
76
97
82
2
Tempur-Pedic
tempurpedic.com
 80
67
100
81
3
Saatva
saatva.com
 78
34
77
59
4
Casper
casper.com
 77
9
75
38
5
Leesa
leesa.com
 73
6
54
29
6
Purple
purple.com
 69
3
47
21
7
T
Tuft & Needle
tn.com
 79
2
45
18
8
Zinus
zinus.com
 66
15
5
17
9
Bear
bear.app
 72
4
15
16
10
Amerisleep
amerisleep.com
 72
1
31
13
11
Helix
helixsleep.com
 79
8
3
13
12
Nolah
nolahmattress.com
 60
4
5
11
13
Brooklyn Bedding
brooklynbedding.com
 73
4
3
9
14
LUCID
lucidmattress.com
 58
3
1
6
15
Layla
laylasleep.com
 68
0
12
4
16
DreamCloud
dreamcloudsleep.com
 71
0
10
2
17
Bear Mattress
bearmattress.com
 66
0
0
1
18
GhostBed
ghostbed.com
 62
0
1
1
19
Novilla
novilla.net
 30
0
1
1
20
Puffy
puffy.com
 66
0
2
1
21
C
Classic Brands
classicbrands.com
 45
0
0
0
22
Dormeo
dormeo.com
 53
0
0
0
23
Dynasty Mattress
dynastymattress.com
 35
0
0
0
24
Emma
myemma.com
 65
0
0
0
25
Ergoflex
ergoflex.co.uk
 45
0
0
0
26
Eve Sleep
evesleep.co.uk
 63
0
0
0
27
MLILY
mlily.com
 47
0
0
0
28
M
Molblly
molblly.com
 15
0
0
0
29
Novosbed
novosbed.com
 47
0
0
0
30
OTTY
otty.com
 45
0
0
0
31
REM-Fit
rem-fit.co.uk
 34
0
0
0
32
Siena Sleep
sienasleep.com
 12
0
0
0
33
Sleep Innovations
sleepinnovations.com
 54
0
0
0
34
SweetNight
sweetnight.com
 42
0
0
0
35
Tempflow
tempflow.com
 35
0
0
0
36
V
Vesgantti
vesgantti.com
 30
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 281 shared Memory Foam Mattresses 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 281 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 →