Overview Leaderboard Methodology
Industry Report

Attribution Providers

Platforms that determine how credit for conversions is assigned across touchpoints using models like last-click, multi-touch, and data-driven attribution.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Google
62/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Google
89

Highest score on the LBA metric.

Authority Leader?
Google
47

Highest score on the Authority metric.

TOM Leader?
Northbeam
77

Highest score on the TOM metric.

Attribution Providers has no dominant brand in AI responses

Google is the top-ranked brand here, but its overall score of 62 reflects a competitive field rather than a dominant player. AI assistants answer category questions about Attribution Providers with varied recommendations from query to query - users get a different set of suggestions each time. This is the kind of category where mid-tier brands still have room to move up.

Brand Leaderboard All 34 Attribution Providers 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
Google
google.com
 89
47
59
62
2
AppsFlyer
appsflyer.com
 88
32
59
55
3
Adobe
adobe.com
 79
24
67
51
4
Northbeam
northbeam.io
 58
28
77
50
5
Triple Whale
triplewhale.com
 76
20
71
48
6
Rockerbox
rockerbox.com
 61
23
66
45
7
Adjust
adjust.com
 85
12
52
37
8
Branch
branch.io
 82
13
44
36
9
Dreamdata
dreamdata.io
 68
16
43
36
10
HubSpot
hubspot.com
 82
22
22
34
11
Ruler Analytics
ruleranalytics.com
 62
9
23
23
12
Wicked Reports
wickedreports.com
 51
3
34
17
13
Singular
singular.net
 74
3
21
16
14
HockeyStack
hockeystack.com
 56
3
19
15
15
Kochava
kochava.com
 77
2
14
14
16
Attribution
attributionapp.com
 16
4
15
10
17
Mixpanel
mixpanel.com
 82
3
3
10
18
Segment
segment.com
 83
1
6
7
19
Measured
measured.com
 48
0
5
3
20
CaliberMind
calibermind.com
 51
0
4
1
21
Full Circle Insights
fullcircleinsights.com
 54
0
1
1
22
Hyros
hyros.com
 62
0
4
1
23
Airbridge
airbridge.io
 62
0
0
0
24
A
Appsumer
appsumer.com
 27
0
0
0
25
C3 Metrics
c3metrics.com
 23
0
0
0
26
Everflow
everflow.io
 65
0
0
0
27
Fospha
fospha.com
 43
0
0
0
28
LeadsRx
leadsrx.com
 48
0
0
0
29
Nielsen Visual IQ
nielsen.com
 58
0
0
0
30
OWOX
owox.com
 51
0
0
0
31
RedTrack
redtrack.io
 61
0
0
0
32
Tenjin
tenjin.com
 65
0
0
0
33
TUNE
tune.com
 71
0
0
0
34
Voluum
voluum.com
 67
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Attribution Providers 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 269 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 →