Overview Leaderboard Methodology
Industry Report

Security Analytics Platforms

Platforms that apply advanced analytics, machine learning, and threat intelligence to large security datasets to prioritize alerts and support investigations.

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
95/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
CrowdStrike
98

Highest score on the LBA metric in this industry.

Authority Leader?
Microsoft
98

Highest score on the Authority metric in this industry.

TOM Leader?
Microsoft
100

Highest score on the TOM metric in this industry.

Microsoft is the default answer in AI responses for Security Analytics Platforms

Microsoft and Splunk together dominate AI responses for Security Analytics 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 Security Analytics Platforms 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
Microsoft
microsoft.com
 88
98
100
95
2
Splunk
splunk.com
 83
82
100
88
3
Elastic
elastic.co
 85
48
65
64
4
IBM
ibm.com
 85
32
76
60
5
Google
google.com
 81
30
80
59
6
CrowdStrike
crowdstrike.com
 98
20
48
47
7
Chronicle
chronicle.security
 68
13
61
39
8
Palo Alto Networks
paloaltonetworks.com
 87
12
48
38
9
Rapid7
rapid7.com
 72
8
56
35
10
Exabeam
exabeam.com
 70
11
39
33
11
LogRhythm
logrhythm.com
 70
7
19
23
12
Securonix
securonix.com
 73
7
16
22
13
Sumo Logic
sumologic.com
 72
7
15
22
14
Fortinet
fortinet.com
 88
9
9
21
15
Vectra AI
vectra.ai
 79
8
8
19
16
AlienVault
att.com
 74
7
7
18
17
Darktrace
darktrace.com
 75
8
8
18
18
Devo
devo.com
 69
7
7
17
19
RSA NetWitness
netwitness.com
 71
7
7
17
20
ArcSight
arcsight.com
 64
6
6
16
21
Coralogix
coralogix.com
 64
6
6
16
22
Graylog
graylog.org
 66
7
7
16
23
ManageEngine ServiceDesk Plus
manageengine.com
 63
6
6
16
24
SOC Prime
socprime.com
 66
7
7
16
25
Stellar Cyber
stellarcyber.ai
 66
7
7
16
26
Anomali
anomali.com
 63
6
6
15
27
LogPoint
logpoint.com
 54
5
5
14
28
Panther
panther.com
 49
5
5
12
29
Blumira
blumira.com
 44
4
4
11
30
Hunters
hunters.security
 41
4
4
11
31
Netsurion
netsurion.com
 40
4
4
10
32
SEKOIA.IO
sekoia.io
 38
4
4
10
33
DNIF
dnif.it
 35
4
4
9

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Security Analytics 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
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 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 →