Overview Leaderboard Methodology
Industry Report

Endpoint Protection Platforms

Comprehensive solutions that provide antivirus, anti-malware, device control, and policy enforcement to protect endpoints from known and unknown threats.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
Microsoft
99/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Microsoft
97

Highest score on the LBA metric.

Authority Leader?
Microsoft
100

Highest score on the Authority metric.

TOM Leader?
Microsoft
100

Highest score on the TOM metric.

Microsoft is the default answer in AI responses for Endpoint Protection Platforms

Microsoft and CrowdStrike together dominate AI responses for Endpoint Protection Platforms. 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 33 Endpoint Protection Platforms 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
Microsoft
microsoft.com
 97
100
100
99
2
CrowdStrike
crowdstrike.com
 93
99
96
96
3
Sophos
sophos.com
 88
51
82
72
4
SentinelOne
sentinelone.com
 85
45
70
64
5
Trend Micro
trendmicro.com
 87
13
59
40
6
Palo Alto Networks
paloaltonetworks.com
 88
4
18
19
7
C
Carbon Black
carbonblack.com
 71
0
9
5
8
Check Point
checkpoint.com
 79
0
4
2
9
Cisco
cisco.com
 78
0
6
2
10
Symantec
symantec.com
 77
0
9
2
11
Trellix
trellix.com
 68
0
8
2
12
Cylance
cylance.com
 74
0
1
1
13
McAfee
mcafee.com
 80
0
3
1
14
AhnLab
ahnlab.com
 59
0
0
0
15
Bitdefender Anti-Tracker
bitdefender.com
 46
0
0
0
16
Cybereason
cybereason.com
 67
0
0
0
17
Deep Instinct
deepinstinct.com
 61
0
0
0
18
Dr.Web
drweb.com
 62
0
0
0
19
ESET Secure Authentication
eset.com
 59
0
0
0
20
F-Secure
f-secure.com
 74
0
0
0
21
Fortinet
fortinet.com
 76
0
0
0
22
G DATA
gdatasoftware.com
 55
0
0
0
23
HarfangLab
harfanglab.io
 50
0
0
0
24
Heimdal
heimdalsecurity.com
 63
0
0
0
25
K7 Security
k7computing.com
 40
0
0
0
26
Kaspersky
kaspersky.com
 81
0
0
0
27
Malwarebytes Browser Guard
malwarebytes.com
 56
0
0
0
28
Panda Security
pandasecurity.com
 67
0
0
0
29
Seqrite
seqrite.com
 61
0
0
0
30
VIPRE
vipre.com
 54
0
0
0
31
Webroot
webroot.com
 67
0
0
0
32
WithSecure
withsecure.com
 64
0
0
0
33
Xcitium
xcitium.com
 59
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Endpoint Protection Platforms 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 263 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 →