Overview Leaderboard Methodology
Industry Report

Billing & Revenue Management

Enterprise-grade systems that handle complex billing models, pricing catalogs, revenue assurance, and financial reporting for large organizations.

Brands tracked: 40
Brands analyzed: 40
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 305
Total responses: 1,575
Top Brand Overall?
Zuora
67/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Stripe Billing
90

Highest score on the LBA metric.

Authority Leader?
Zuora
47

Highest score on the Authority metric.

TOM Leader?
Zuora
91

Highest score on the TOM metric.

Billing & Revenue Management has no dominant brand in AI responses

Zuora is the top-ranked brand here, but its overall score of 67 reflects a competitive field rather than a dominant player. AI assistants answer category questions about Billing & Revenue Management 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 40 Billing & Revenue Management 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
Zuora
zuora.com
 71
47
91
67
2
Chargebee
chargebee.com
 86
40
80
65
3
Stripe Billing
stripe.com
 90
34
37
48
4
Oracle
oracle.com
 81
12
54
38
5
Recurly
recurly.com
 74
14
55
38
6
Maxio
maxio.com
 66
8
51
30
7
SAP
sap.com
 76
6
51
28
8
Amdocs
amdocs.com
 76
9
13
21
9
Salesforce
salesforce.com
 81
3
20
17
10
Orb
orb.com
 42
10
5
13
11
Sage Intacct
sageintacct.com
 75
1
19
13
12
Netcracker
netcracker.com
 62
3
6
10
13
Xero
xero.com
 67
2
6
10
14
Lago
lago.com
 61
5
2
8
15
Metronome
metronome.com
 60
3
3
8
16
Paddle
paddle.com
 75
0
19
5
17
CSG
csgi.com
 57
0
2
3
18
Aria Systems
ariasystems.com
 64
0
5
2
19
BillingPlatform
billingplatform.com
 61
0
0
2
20
Cerillion
cerillion.com
 54
0
1
1
21
Conga
conga.com
 59
0
4
1
22
m3ter
m3ter.com
 37
0
0
1
23
OneBill
onebillsoftware.com
 44
0
0
1
24
Amberflo
amberflo.io
 43
0
0
0
25
Billsby
billsby.com
 41
0
0
0
26
billwerk
billwerk.plus
 38
0
0
0
27
BluLogix
blulogix.com
 37
0
0
0
28
ChargeOver
chargeover.com
 55
0
0
0
29
EzyPay
ezypay.com
 2
0
0
0
30
Gotransverse
gotransverse.com
 54
0
0
0
31
JustOn
juston.com
 33
0
0
0
32
LogiSense
logisense.com
 23
0
0
0
33
MonetizeNow
monetizenow.io
 0
0
0
0
34
NetSuite CRM
netsuite.com
 68
0
0
0
35
Optiva
optiva.com
 48
0
0
0
36
Ordway
ordwaylabs.com
 33
0
0
0
37
Sequence
sequencehq.com
 23
0
0
0
38
Subskribe
subskribe.com
 32
0
0
0
39
Vindicia
vindicia.com
 56
0
0
0
40
Younium
younium.com
 38
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 305 shared Billing & Revenue Management 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 305 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 →