Overview Leaderboard Methodology
Industry Report

Media Mix Modeling Vendors

Solutions that use statistical modeling to quantify the contribution of channels and guide budget allocation across paid, owned, and earned media.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Analytic Partners
77/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Kantar
77

Highest score on the LBA metric.

Authority Leader?
Analytic Partners
63

Highest score on the Authority metric.

TOM Leader?
Analytic Partners
100

Highest score on the TOM metric.

Analytic Partners leads the Media Mix Modeling Vendors category in AI responses

Analytic Partners is the most consistently-surfaced brand when users ask AI assistants about Media Mix Modeling Vendors, but not to the point of monopolising the conversation. Google and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 34 Media Mix Modeling Vendors 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
Analytic Partners
analyticpartners.com
 73
63
100
77
2
Google
google.com
 70
60
78
69
3
Meta
meta.com
 50
29
61
44
4
Ekimetrics
ekimetrics.com
 64
17
62
41
5
Measured
measured.com
 33
29
39
34
6
Ipsos MMA
ipsos.com
 63
12
45
33
7
Kantar
kantar.com
 77
9
50
32
8
Recast
getrecast.com
 27
16
56
29
9
TransUnion
transunion.com
 22
5
29
14
10
Rockerbox
rockerbox.com
 51
5
9
13
11
Circana
circana.com
 53
5
5
11
12
Northbeam
northbeam.io
 36
1
12
8
13
N
Neustar
neustar.biz
 43
1
13
7
14
Gain Theory
gaintheory.com
 59
0
14
2
15
K
Keen Decision Systems
keendecisionsystems.com
 54
0
10
2
16
Mutinex
mutinex.co
 41
0
20
2
17
Fospha
fospha.com
 40
0
2
1
18
Haus
haus.io
 18
0
7
1
19
Kochava
kochava.com
 48
0
1
1
20
Lifesight
lifesight.io
 30
0
1
1
21
LiftLab
liftlab.com
 3
0
16
1
22
Marketing Evolution
marketingevolution.com
 60
0
2
1
23
NCSolutions
ncsolutions.com
 48
0
4
1
24
Prescient AI
prescientai.com
 33
0
4
1
25
Sellforte
sellforte.com
 33
0
1
1
26
Analytic Edge
analytic-edge.com
 24
0
0
0
27
AppsFlyer
appsflyer.com
 63
0
0
0
28
C3 Metrics
c3metrics.com
 30
0
0
0
29
Data2Decisions
data2decisions.com
 5
0
0
0
30
Incrmntal
incrmntal.com
 2
0
0
0
31
Mass Analytics
mass-analytics.com
 2
0
0
0
32
Nielsen Visual IQ
nielsen.com
 60
0
0
0
33
OptiMine
optimine.com
 17
0
0
0
34
ScanmarQED
scanmarqed.com
 41
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Media Mix Modeling Vendors 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 →