Overview Leaderboard Methodology
Industry Report

Marketing-Focused Customer Data Platforms

CDPs oriented toward marketing teams that centralize customer profiles to power campaign orchestration, personalization, and audience activation across advertising and email channels.

Brands tracked: 36
Brands analyzed: 36
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 281
Total responses: 1,435
Top Brand Overall?
Segment
96/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
HubSpot
91

Highest score on the LBA metric in this industry.

Authority Leader?
Segment
100

Highest score on the Authority metric in this industry.

TOM Leader?
Segment
100

Highest score on the TOM metric in this industry.

Segment is the default answer in AI responses for Marketing-Focused Customer Data Platforms

When users ask ChatGPT, Claude, or Gemini about Marketing-Focused Customer Data Platforms, Segment is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. mParticle is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 36 Marketing-Focused Customer Data 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
Segment
segment.com
 88
100
100
96
2
mParticle
mparticle.com
 75
51
88
70
3
Salesforce
salesforce.com
 89
38
87
67
4
Adobe
adobe.com
 87
36
85
65
5
Tealium
tealium.com
 78
40
77
62
6
Treasure Data
treasuredata.com
 73
14
57
41
7
Hightouch
hightouch.com
 83
30
20
38
8
BlueConic
blueconic.com
 66
9
54
34
9
RudderStack
rudderstack.com
 71
26
20
34
10
Bloomreach
bloomreach.com
 75
8
38
30
11
ActionIQ
actioniq.com
 68
7
35
28
12
HubSpot
hubspot.com
 91
16
9
25
13
Amperity
amperity.com
 67
7
20
23
14
Klaviyo
klaviyo.com
 88
10
9
22
15
Braze
braze.com
 78
12
8
21
16
Snowflake
snowflake.com
 78
8
8
19
17
Blueshift
blueshift.com
 73
7
7
18
18
MoEngage
moengage.com
 76
8
8
18
19
Simon Data
simondata.com
 71
7
9
18
20
Insider
useinsider.com
 71
7
7
17
21
Optimove
optimove.com
 71
7
7
17
22
Zeotap
zeotap.com
 68
7
7
17
23
WebEngage
webengage.com
 67
7
7
16
24
Leadspace
leadspace.com
 61
6
6
15
25
L
Lytics
lytics.com
 62
6
6
15
26
Ortto
ortto.com
 58
6
6
15
27
Ometria
ometria.com
 58
6
6
14
28
Redpoint
redpointglobal.com
 55
6
6
14
29
Celebrus
celebrus.com
 50
5
5
13
30
Commanders Act
commandersact.com
 50
5
5
13
31
CrossEngage
crossengage.io
 52
5
5
13
32
Relay42
relay42.com
 49
5
5
13
33
Lexer
lexer.io
 46
5
5
12
34
NGDATA
ngdata.com
 49
5
5
12
35
FirstHive
firsthive.com
 39
4
4
10
36
Meiro
meiro.io
 36
4
4
10

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 281 shared Marketing-Focused Customer Data 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 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 →