Overview Leaderboard Methodology
Industry Report

Procurement Platforms

Platforms that manage vendor procurement, purchase orders and supplier payments.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
Coupa
90/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Coupa
81

Highest score on the LBA metric.

Authority Leader?
Coupa
91

Highest score on the Authority metric.

TOM Leader?
Coupa
100

Highest score on the TOM metric.

Coupa is the default answer in AI responses for Procurement Platforms

When users ask ChatGPT, Claude, or Gemini about Procurement Platforms, Coupa is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. SAP Ariba 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 37 Procurement Platforms 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
Coupa
coupa.com
 81
91
100
90
2
SAP Ariba
ariba.com
 79
63
100
79
3
Oracle
oracle.com
 76
32
75
57
4
Procurify
procurify.com
 59
38
62
52
5
JAGGAER
jaggaer.com
 72
24
68
49
6
Precoro
precoro.com
 55
33
38
41
7
Zip
ziphq.com
 57
23
49
40
8
Ivalua
ivalua.com
 66
12
51
35
9
GEP
gep.com
 67
6
58
28
10
BILL
bill.com
 67
7
26
24
11
Tipalti
tipalti.com
 65
6
32
23
12
Ramp
ramp.com
 78
2
13
12
13
Zoho
zoho.com
 56
3
7
11
14
ProcurementExpress.com
procurementexpress.com
 37
0
7
5
15
Tradogram
tradogram.com
 30
3
1
4
16
Basware
basware.com
 71
0
8
2
17
Zycus
zycus.com
 69
0
12
2
18
Airbase
airbase.com
 73
0
3
1
19
Kissflow Procurement Cloud
kissflow.com
 47
0
5
1
20
Medius
medius.com
 63
0
2
1
21
Planergy
planergy.com
 41
0
2
1
22
Proactis
proactis.com
 53
0
5
1
23
Tradeshift
tradeshift.com
 71
0
1
1
24
BirchStreet Systems
birchstreetsystems.com
 56
0
0
0
25
Bonfire
gobonfire.com
 32
0
0
0
26
Corcentric
corcentric.com
 54
0
0
0
27
Fairmarkit
fairmarkit.com
 57
0
0
0
28
Lightyear
lightyear.ai
 34
0
0
0
29
Market Dojo
marketdojo.com
 48
0
0
0
30
oboloo
oboloo.com
 30
0
0
0
31
Order.co
order.co
 55
0
0
0
32
Oro
orolabs.ai
 18
0
0
0
33
ProcurEngine
procurengine.com
 0
0
0
0
34
Tropic
tropicapp.io
 46
0
0
0
35
Vendorful
vendorful.com
 24
0
0
0
36
Vroozi
vroozi.com
 32
0
0
0
37
X
Xeeva
xeeva.com
 32
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Procurement 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
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 287 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 →