Overview Leaderboard Methodology
Industry Report

Commerce Customer Data Platforms

CDPs tailored for retail and e-commerce that integrate transactional, behavioral, and loyalty data to drive personalized shopping experiences, recommendations, and lifecycle marketing.

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
90/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Klaviyo
92

Highest score on the LBA metric in this industry.

Authority Leader?
Segment
83

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 Commerce Customer Data Platforms

When users ask ChatGPT, Claude, or Gemini about Commerce Customer Data Platforms, Segment is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Adobe 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 Commerce 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
 89
83
100
90
2
Adobe
adobe.com
 89
44
68
65
3
Salesforce
salesforce.com
 83
46
73
65
4
Bloomreach
bloomreach.com
 73
40
76
61
5
Treasure Data
treasuredata.com
 73
38
63
56
6
mParticle
mparticle.com
 76
22
80
52
7
Tealium
tealium.com
 76
32
50
50
8
Klaviyo
klaviyo.com
 92
25
29
41
9
BlueConic
blueconic.com
 64
12
41
32
10
Amperity
amperity.com
 67
15
29
31
11
RudderStack
rudderstack.com
 68
12
21
27
12
Dynamic Yield
dynamicyield.com
 77
8
9
19
13
Hightouch
hightouch.com
 76
8
8
18
14
ActionIQ
actioniq.com
 63
6
9
17
15
Insider
useinsider.com
 66
7
9
17
16
L
Lytics
lytics.com
 55
5
12
17
17
Nosto
nosto.com
 68
7
7
17
18
Optimove
optimove.com
 67
7
7
17
19
dotdigital
dotdigital.com
 65
6
6
16
20
Emarsys
emarsys.com
 66
7
7
16
21
Ometria
ometria.com
 65
7
7
16
22
Wunderkind
wunderkind.co
 65
7
7
16
23
Listrak
listrak.com
 59
6
6
15
24
Netcore
netcorecloud.com
 61
6
6
15
25
Simon Data
simondata.com
 58
6
6
15
26
Zeotap
zeotap.com
 60
6
6
15
27
SalesManago
salesmanago.com
 58
6
6
14
28
Shopify Tax
shopify.com
 45
4
9
14
29
Synerise
synerise.com
 53
5
5
13
30
Lexer
lexer.io
 47
5
5
12
31
Voyado
voyado.com
 46
5
5
12
32
Datatrics
datatrics.com
 33
3
3
9
33
FirstHive
firsthive.com
 33
3
3
9
34
Custobar
custobar.com
 28
3
3
8
35
Squeezely
squeezely.tech
 21
2
2
6
36
LoyalGuru
loyal.guru
 1
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 281 shared Commerce 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 →